diff --git a/docs/.buildinfo b/docs/.buildinfo
index be12f6c1..f42fac32 100644
--- a/docs/.buildinfo
+++ b/docs/.buildinfo
@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 3a80cd6e0cb0ef91846ca3b8f473a4aa
+config: 13bf4155d1ddbde13c39e6754206c4a7
 tags: 645f666f9bcd5a90fca523b33c5a78b7
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index f80f0302..b3c3ac51 100644
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diff --git a/docs/.doctrees/tutorial_cmd.doctree b/docs/.doctrees/tutorial_cmd.doctree
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diff --git a/docs/_modules/impy/array_api.html b/docs/_modules/impy/array_api.html
index c02ff534..c05dd210 100644
--- a/docs/_modules/impy/array_api.html
+++ b/docs/_modules/impy/array_api.html
@@ -3,7 +3,7 @@
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.array_api &mdash; impy 2.1.3 documentation</title>
+  <title>impy.array_api &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -11,9 +11,8 @@
   <![endif]-->
   
         <script data-url_root="../../" id="documentation_options" src="../../_static/documentation_options.js"></script>
-        <script src="../../_static/jquery.js"></script>
-        <script src="../../_static/underscore.js"></script>
         <script src="../../_static/doctools.js"></script>
+        <script src="../../_static/sphinx_highlight.js"></script>
     <script src="../../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../../genindex.html" />
     <link rel="search" title="Search" href="../../search.html" /> 
@@ -24,14 +23,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.1.3
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -58,9 +61,9 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../index.html">Module code</a> &raquo;</li>
-      <li>impy.array_api</li>
+      <li><a href="../../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../index.html">Module code</a></li>
+      <li class="breadcrumb-item active">impy.array_api</li>
       <li class="wy-breadcrumbs-aside">
       </li>
   </ul>
@@ -144,11 +147,13 @@ <h1>Source code for impy.array_api</h1><div class="highlight"><pre>
         <span class="bp">self</span><span class="o">.</span><span class="n">round</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">round</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">gradient</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">gradient</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">tensordot</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">tensordot</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">concatenate</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">stack</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">stack</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">unravel_index</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">unravel_index</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">argmax</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">argmax</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">argmin</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">argmin</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">pad</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">pad</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">isnan</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">isnan</span>
         
         <span class="bp">self</span><span class="o">.</span><span class="n">state</span> <span class="o">=</span> <span class="s2">&quot;numpy&quot;</span>
         <span class="kn">from</span> <span class="nn">._const</span> <span class="kn">import</span> <span class="n">Const</span>
@@ -213,11 +218,13 @@ <h1>Source code for impy.array_api</h1><div class="highlight"><pre>
         <span class="k">except</span> <span class="ne">AttributeError</span><span class="p">:</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">gradient</span> <span class="o">=</span> <span class="n">_gradient</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">tensordot</span> <span class="o">=</span> <span class="n">cp</span><span class="o">.</span><span class="n">tensordot</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">concatenate</span> <span class="o">=</span> <span class="n">cp</span><span class="o">.</span><span class="n">concatenate</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">stack</span> <span class="o">=</span> <span class="n">cp</span><span class="o">.</span><span class="n">stack</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">unravel_index</span> <span class="o">=</span> <span class="n">cp</span><span class="o">.</span><span class="n">unravel_index</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">argmax</span> <span class="o">=</span> <span class="n">cp</span><span class="o">.</span><span class="n">argmax</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">argmin</span> <span class="o">=</span> <span class="n">cp</span><span class="o">.</span><span class="n">argmin</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">pad</span> <span class="o">=</span> <span class="n">cp</span><span class="o">.</span><span class="n">pad</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">isnan</span> <span class="o">=</span> <span class="n">cp</span><span class="o">.</span><span class="n">isnan</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">state</span> <span class="o">=</span> <span class="s2">&quot;cupy&quot;</span>
         
         <span class="kn">from</span> <span class="nn">._const</span> <span class="kn">import</span> <span class="n">Const</span>
diff --git a/docs/_modules/impy/arrays/axesmixin.html b/docs/_modules/impy/arrays/axesmixin.html
index 424fb768..9a5535eb 100644
--- a/docs/_modules/impy/arrays/axesmixin.html
+++ b/docs/_modules/impy/arrays/axesmixin.html
@@ -3,7 +3,7 @@
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.arrays.axesmixin &mdash; impy 2.2.0 documentation</title>
+  <title>impy.arrays.axesmixin &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../../../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -11,9 +11,8 @@
   <![endif]-->
   
         <script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
-        <script src="../../../_static/jquery.js"></script>
-        <script src="../../../_static/underscore.js"></script>
         <script src="../../../_static/doctools.js"></script>
+        <script src="../../../_static/sphinx_highlight.js"></script>
     <script src="../../../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../../../genindex.html" />
     <link rel="search" title="Search" href="../../../search.html" /> 
@@ -24,14 +23,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../../../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../../../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../../../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -58,9 +61,9 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../../../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../../index.html">Module code</a> &raquo;</li>
-      <li>impy.arrays.axesmixin</li>
+      <li><a href="../../../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../../index.html">Module code</a></li>
+      <li class="breadcrumb-item active">impy.arrays.axesmixin</li>
       <li class="wy-breadcrumbs-aside">
       </li>
   </ul>
@@ -87,20 +90,21 @@ <h1>Source code for impy.arrays.axesmixin</h1><div class="highlight"><pre>
 <span class="kn">from</span> <span class="nn">collections</span> <span class="kn">import</span> <span class="n">namedtuple</span>
 <span class="kn">from</span> <span class="nn">numbers</span> <span class="kn">import</span> <span class="n">Number</span>
 
-<span class="kn">from</span> <span class="nn">..utils.axesop</span> <span class="kn">import</span> <span class="n">switch_slice</span>
-<span class="kn">from</span> <span class="nn">..axes</span> <span class="kn">import</span> <span class="n">Axes</span><span class="p">,</span> <span class="n">ImageAxesError</span><span class="p">,</span> <span class="n">ScaleView</span><span class="p">,</span> <span class="n">AxisLike</span><span class="p">,</span> <span class="n">AxesLike</span><span class="p">,</span> <span class="n">Axis</span>
-<span class="kn">from</span> <span class="nn">.._types</span> <span class="kn">import</span> <span class="n">Slices</span><span class="p">,</span> <span class="n">Dims</span>
+<span class="kn">from</span> <span class="nn">impy.utils.axesop</span> <span class="kn">import</span> <span class="n">switch_slice</span>
+<span class="kn">from</span> <span class="nn">impy.axes</span> <span class="kn">import</span> <span class="n">Axes</span><span class="p">,</span> <span class="n">ImageAxesError</span><span class="p">,</span> <span class="n">ScaleView</span><span class="p">,</span> <span class="n">AxisLike</span><span class="p">,</span> <span class="n">AxesLike</span><span class="p">,</span> <span class="n">Axis</span>
+<span class="kn">from</span> <span class="nn">impy._types</span> <span class="kn">import</span> <span class="n">Slices</span><span class="p">,</span> <span class="n">Dims</span>
 
 <span class="k">if</span> <span class="n">TYPE_CHECKING</span><span class="p">:</span>
     <span class="kn">from</span> <span class="nn">typing_extensions</span> <span class="kn">import</span> <span class="n">Self</span><span class="p">,</span> <span class="n">Literal</span>
 
 <div class="viewcode-block" id="AxesMixin"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.axesmixin.AxesMixin">[docs]</a><span class="k">class</span> <span class="nc">AxesMixin</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;Abstract class with shape, ndim and axes are defined.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Abstract class with shape, ndim and axes are defined.&quot;&quot;&quot;</span>
     
     <span class="n">_INHERIT</span> <span class="o">=</span> <span class="nb">object</span><span class="p">()</span>
     <span class="n">_axes</span><span class="p">:</span> <span class="n">Axes</span>
     <span class="n">ndim</span><span class="p">:</span> <span class="nb">int</span>
     <span class="n">shape</span><span class="p">:</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span>
+    <span class="n">dtype</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">dtype</span>
     <span class="n">value</span><span class="p">:</span> <span class="n">Any</span>
     
     <span class="nd">@property</span>
@@ -114,7 +118,7 @@ <h1>Source code for impy.arrays.axesmixin</h1><div class="highlight"><pre>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">axes</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Axes</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Axes of the array.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Axes of the array.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_axes</span>
     
     <span class="nd">@axes</span><span class="o">.</span><span class="n">setter</span>
@@ -133,7 +137,7 @@ <h1>Source code for impy.arrays.axesmixin</h1><div class="highlight"><pre>
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">metadata</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]:</span>
         <span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">()</span>
-    
+
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">scale</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ScaleView</span><span class="p">:</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">scale</span>
@@ -178,17 +182,17 @@ <h1>Source code for impy.arrays.axesmixin</h1><div class="highlight"><pre>
         <span class="n">html</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;&quot;&quot;</span>
 <span class="s2">        &lt;head&gt;</span>
 <span class="s2">            &lt;style&gt;</span>
-<span class="s2">                #wrapper </span><span class="se">{{</span><span class="s2"></span>
+<span class="s2">                #wrapper </span><span class="se">{{</span>
 <span class="s2">                    height: 140px;</span>
 <span class="s2">                    width: 500px;</span>
 <span class="s2">                    overflow-y: scroll;</span>
-<span class="s2">                </span><span class="se">}}</span><span class="s2"></span>
+<span class="s2">                </span><span class="se">}}</span>
 <span class="s2">            &lt;/style&gt;</span>
 <span class="s2">        &lt;/head&gt;</span>
 
 <span class="s2">        &lt;body&gt;</span>
 <span class="s2">            &lt;div id=&quot;wrapper&quot;&gt;</span>
-<span class="s2">                </span><span class="si">{</span><span class="n">main</span><span class="si">}</span><span class="s2"></span>
+<span class="s2">                </span><span class="si">{</span><span class="n">main</span><span class="si">}</span>
 <span class="s2">            &lt;/div&gt;</span>
 <span class="s2">        &lt;/body&gt;</span>
 <span class="s2">        &quot;&quot;&quot;</span>
@@ -208,7 +212,7 @@ <h1>Source code for impy.arrays.axesmixin</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="nb">tuple</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sizeof</span><span class="p">(</span><span class="n">a</span><span class="p">)</span> <span class="k">for</span> <span class="n">a</span> <span class="ow">in</span> <span class="n">axes</span><span class="p">)</span></div>
     
 <div class="viewcode-block" id="AxesMixin.set_axes"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.axesmixin.AxesMixin.set_axes">[docs]</a>    <span class="k">def</span> <span class="nf">set_axes</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axes</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Set axes of the array and return the updated one.</span>
 
 <span class="sd">        Parameters</span>
@@ -225,7 +229,7 @@ <h1>Source code for impy.arrays.axesmixin</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="bp">self</span></div>
 
 <div class="viewcode-block" id="AxesMixin.set_scale"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.axesmixin.AxesMixin.set_scale">[docs]</a>    <span class="k">def</span> <span class="nf">set_scale</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">unit</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Set scales of each axis.</span>
 
 <span class="sd">        Parameters</span>
@@ -272,6 +276,9 @@ <h1>Source code for impy.arrays.axesmixin</h1><div class="highlight"><pre>
                 <span class="p">{</span><span class="n">a</span><span class="p">:</span> <span class="n">s</span> <span class="k">for</span> <span class="n">a</span><span class="p">,</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">other</span><span class="o">.</span><span class="n">scale</span><span class="o">.</span><span class="n">items</span><span class="p">()</span> <span class="k">if</span> <span class="n">a</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">}</span>  <span class="c1"># type: ignore</span>
             <span class="p">)</span>
         
+        <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">)):</span>
+            <span class="k">for</span> <span class="n">a</span><span class="p">,</span> <span class="n">s</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">,</span> <span class="n">other</span><span class="p">):</span>
+                <span class="n">a</span><span class="o">.</span><span class="n">scale</span> <span class="o">=</span> <span class="n">s</span>
         <span class="k">else</span><span class="p">:</span>
             <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span>
                 <span class="sa">f</span><span class="s2">&quot;&#39;other&#39; must be str or axes supported object, but got </span><span class="si">{</span><span class="nb">type</span><span class="p">(</span><span class="n">other</span><span class="p">)</span><span class="si">}</span><span class="s2">&quot;</span>
@@ -288,7 +295,7 @@ <h1>Source code for impy.arrays.axesmixin</h1><div class="highlight"><pre>
         <span class="o">/</span><span class="p">,</span>
         <span class="o">**</span><span class="n">kwargs</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Set labels to an axis (axes).</span>
 
 <span class="sd">        Parameters</span>
@@ -330,7 +337,7 @@ <h1>Source code for impy.arrays.axesmixin</h1><div class="highlight"><pre>
         <span class="o">...</span>
     
 <div class="viewcode-block" id="AxesMixin.iter"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.axesmixin.AxesMixin.iter">[docs]</a>    <span class="k">def</span> <span class="nf">iter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">israw</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span> <span class="n">exclude</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Iteration along axes. If axes=&quot;tzc&quot;, then equivalent to following pseudo code:</span>
 <span class="sd">        </span>
 <span class="sd">            .. code-block::</span>
diff --git a/docs/_modules/impy/arrays/bases/metaarray.html b/docs/_modules/impy/arrays/bases/metaarray.html
index 8ec5ecba..00e168ed 100644
--- a/docs/_modules/impy/arrays/bases/metaarray.html
+++ b/docs/_modules/impy/arrays/bases/metaarray.html
@@ -3,7 +3,7 @@
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.arrays.bases.metaarray &mdash; impy 2.2.0 documentation</title>
+  <title>impy.arrays.bases.metaarray &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../../../../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../../../../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -11,9 +11,8 @@
   <![endif]-->
   
         <script data-url_root="../../../../" id="documentation_options" src="../../../../_static/documentation_options.js"></script>
-        <script src="../../../../_static/jquery.js"></script>
-        <script src="../../../../_static/underscore.js"></script>
         <script src="../../../../_static/doctools.js"></script>
+        <script src="../../../../_static/sphinx_highlight.js"></script>
     <script src="../../../../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../../../../genindex.html" />
     <link rel="search" title="Search" href="../../../../search.html" /> 
@@ -24,14 +23,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../../../../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../../../../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../../../../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -58,9 +61,9 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../../../../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../../../index.html">Module code</a> &raquo;</li>
-      <li>impy.arrays.bases.metaarray</li>
+      <li><a href="../../../../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../../../index.html">Module code</a></li>
+      <li class="breadcrumb-item active">impy.arrays.bases.metaarray</li>
       <li class="wy-breadcrumbs-aside">
       </li>
   </ul>
@@ -99,7 +102,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
     <span class="n">Mapping</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">SupportOneSlicing</span><span class="p">],</span>
 <span class="p">]</span>
 
-<div class="viewcode-block" id="MetaArray"><a class="viewcode-back" href="../../../../apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray">[docs]</a><span class="k">class</span> <span class="nc">MetaArray</span><span class="p">(</span><span class="n">AxesMixin</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
+<div class="viewcode-block" id="MetaArray"><a class="viewcode-back" href="../../../../apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray">[docs]</a><span class="k">class</span> <span class="nc">MetaArray</span><span class="p">(</span><span class="n">AxesMixin</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">[</span><span class="n">Any</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">dtype</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">number</span><span class="p">]]):</span>
     <span class="n">additional_props</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;_source&quot;</span><span class="p">,</span> <span class="s2">&quot;_metadata&quot;</span><span class="p">,</span> <span class="s2">&quot;_name&quot;</span><span class="p">]</span>
     <span class="n">NP_DISPATCH</span> <span class="o">=</span> <span class="p">{}</span>
     <span class="n">_name</span><span class="p">:</span> <span class="nb">str</span>
@@ -127,7 +130,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">source</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;The source file path.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;The source file path.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_source</span>
     
     <span class="nd">@source</span><span class="o">.</span><span class="n">setter</span>
@@ -139,7 +142,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">name</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Name of the array.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Name of the array.&quot;&quot;&quot;</span>
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_name</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
             <span class="n">source</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">source</span>
             <span class="k">if</span> <span class="n">source</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
@@ -155,7 +158,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">metadata</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]:</span>
-        <span class="sd">&quot;&quot;&quot;Metadata dictionary of the array.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Metadata dictionary of the array.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_metadata</span>
 
     <span class="nd">@metadata</span><span class="o">.</span><span class="n">setter</span>
@@ -166,7 +169,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">value</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Numpy view of the array.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Numpy view of the array.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
     
     <span class="k">def</span> <span class="fm">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span>
@@ -217,7 +220,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__setitem__</span><span class="p">(</span><span class="n">key</span><span class="p">,</span> <span class="n">value</span><span class="p">)</span>
     
 <div class="viewcode-block" id="MetaArray.sel"><a class="viewcode-back" href="../../../../apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.sel">[docs]</a>    <span class="k">def</span> <span class="nf">sel</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">indexer</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">/</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        A label based indexing method, mimicking ``xarray.sel``.</span>
 <span class="sd">        </span>
 <span class="sd">        Example</span>
@@ -242,7 +245,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="bp">self</span><span class="p">[</span><span class="nb">tuple</span><span class="p">(</span><span class="n">slices</span><span class="p">)]</span></div>
     
 <div class="viewcode-block" id="MetaArray.isel"><a class="viewcode-back" href="../../../../apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.isel">[docs]</a>    <span class="k">def</span> <span class="nf">isel</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">indexer</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">/</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        A index based indexing method, mimicking ``xarray.isel``.</span>
 <span class="sd">        </span>
 <span class="sd">        Example</span>
@@ -262,7 +265,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">out</span></div>
     
     <span class="k">def</span> <span class="nf">__array_finalize__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">obj</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Every time an np.ndarray object is made by numpy functions inherited to ImgArray,</span>
 <span class="sd">        this function will be called to set essential attributes. Therefore, you can use</span>
 <span class="sd">        such as img.copy() and img.astype(&quot;int&quot;) without problems (maybe...).</span>
@@ -279,7 +282,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
                 <span class="bp">self</span><span class="o">.</span><span class="n">axes</span> <span class="o">=</span> <span class="kc">None</span>
         
     <span class="k">def</span> <span class="nf">__array_ufunc__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ufunc</span><span class="p">,</span> <span class="n">method</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Every time a numpy universal function (add, subtract, ...) is called,</span>
 <span class="sd">        this function will be called to set/update essential attributes.</span>
 <span class="sd">        &quot;&quot;&quot;</span>
@@ -300,7 +303,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">result</span>
     
     <span class="k">def</span> <span class="nf">__array_function__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">func</span><span class="p">,</span> <span class="n">types</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Every time a numpy function (np.mean...) is called, this function will be called. Essentially numpy</span>
 <span class="sd">        function can be overloaded with this method.</span>
 <span class="sd">        &quot;&quot;&quot;</span>
@@ -331,7 +334,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
 
 <div class="viewcode-block" id="MetaArray.implements"><a class="viewcode-back" href="../../../../apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.implements">[docs]</a>    <span class="nd">@classmethod</span>
     <span class="k">def</span> <span class="nf">implements</span><span class="p">(</span><span class="bp">cls</span><span class="p">,</span> <span class="n">numpy_function</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Add functions to NP_DISPATCH so that numpy functions can be overloaded.</span>
 <span class="sd">        &quot;&quot;&quot;</span>        
         <span class="k">def</span> <span class="nf">decorator</span><span class="p">(</span><span class="n">func</span><span class="p">):</span>
@@ -341,7 +344,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">decorator</span></div>
     
 <div class="viewcode-block" id="MetaArray.sort_axes"><a class="viewcode-back" href="../../../../apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.sort_axes">[docs]</a>    <span class="k">def</span> <span class="nf">sort_axes</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Sort image dimensions to ptzcyx-order</span>
 
 <span class="sd">        Returns</span>
@@ -353,7 +356,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">order</span><span class="p">)</span></div>
 
 <div class="viewcode-block" id="MetaArray.argmax_nd"><a class="viewcode-back" href="../../../../apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.argmax_nd">[docs]</a>    <span class="k">def</span> <span class="nf">argmax_nd</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        N-dimensional version of argmax.</span>
 <span class="sd">        </span>
 <span class="sd">        For instance, if yx-array takes its maximum at (5, 8), this function returns</span>
@@ -368,7 +371,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">tuple</span><span class="p">(</span><span class="n">argmax</span><span class="p">)</span></div>
     
 <div class="viewcode-block" id="MetaArray.split"><a class="viewcode-back" href="../../../../apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.split">[docs]</a>    <span class="k">def</span> <span class="nf">split</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataList</span><span class="p">[</span><span class="n">Self</span><span class="p">]:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Split n-dimensional image into (n-1)-dimensional images.</span>
 
 <span class="sd">        Parameters</span>
@@ -404,7 +407,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="n">args</span><span class="p">:</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">Any</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">kwargs</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Convert array into dask array and run a batch process in parallel. In many cases batch process </span>
 <span class="sd">        in this way is faster than `multiprocess` module.</span>
 
@@ -501,7 +504,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">out</span>
     
 <div class="viewcode-block" id="MetaArray.transpose"><a class="viewcode-back" href="../../../../apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.transpose">[docs]</a>    <span class="k">def</span> <span class="nf">transpose</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        change the order of image dimensions.</span>
 <span class="sd">        &#39;axes&#39; will also be arranged.</span>
 <span class="sd">        &quot;&quot;&quot;</span>
@@ -529,7 +532,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">out</span>
     
     <span class="k">def</span> <span class="nf">_broadcast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="n">Any</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;Broadcasting method used in most of the mathematical operations.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Broadcasting method used in most of the mathematical operations.&quot;&quot;&quot;</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">value</span><span class="p">,</span> <span class="n">MetaArray</span><span class="p">):</span>
             <span class="k">return</span> <span class="n">value</span>
         <span class="n">current_axes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span>
@@ -547,7 +550,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="n">shape</span><span class="p">:</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">],</span> 
         <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Broadcast array to specified shape and axes.</span>
 
 <span class="sd">        Parameters</span>
@@ -603,22 +606,22 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="bp">self</span><span class="p">,</span>
         <span class="n">axis</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
         <span class="n">out</span><span class="p">:</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">keepdims</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">_NoValue</span><span class="p">,</span>
+        <span class="n">keepdims</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">where</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">=</span> <span class="n">_NoValue</span><span class="p">,</span>
     <span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;Minimum value of the array along a given axis.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Minimum value of the array along a given axis.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">min</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="n">axis</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="n">out</span><span class="p">,</span> <span class="n">keepdims</span><span class="o">=</span><span class="n">keepdims</span><span class="p">,</span> <span class="n">where</span><span class="o">=</span><span class="n">where</span><span class="p">)</span></div>
     
 <div class="viewcode-block" id="MetaArray.max"><a class="viewcode-back" href="../../../../apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.max">[docs]</a>    <span class="k">def</span> <span class="nf">max</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">,</span>
         <span class="n">axis</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
         <span class="n">out</span><span class="p">:</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">keepdims</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">_NoValue</span><span class="p">,</span>
+        <span class="n">keepdims</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">where</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">=</span> <span class="n">_NoValue</span><span class="p">,</span>
     <span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;Maximum value of the array along a given axis.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Maximum value of the array along a given axis.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="n">axis</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="n">out</span><span class="p">,</span> <span class="n">keepdims</span><span class="o">=</span><span class="n">keepdims</span><span class="p">,</span> <span class="n">where</span><span class="o">=</span><span class="n">where</span><span class="p">)</span></div>
     
 <div class="viewcode-block" id="MetaArray.mean"><a class="viewcode-back" href="../../../../apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.mean">[docs]</a>    <span class="k">def</span> <span class="nf">mean</span><span class="p">(</span>
@@ -626,11 +629,11 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="n">axis</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
         <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">out</span><span class="p">:</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">keepdims</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">_NoValue</span><span class="p">,</span>
+        <span class="n">keepdims</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">where</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">=</span> <span class="n">_NoValue</span><span class="p">,</span>
     <span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;Mean value of the array along a given axis.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Mean value of the array along a given axis.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="n">axis</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="n">out</span><span class="p">,</span> <span class="n">keepdims</span><span class="o">=</span><span class="n">keepdims</span><span class="p">,</span> <span class="n">where</span><span class="o">=</span><span class="n">where</span><span class="p">)</span></div>
     
 <div class="viewcode-block" id="MetaArray.sum"><a class="viewcode-back" href="../../../../apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.sum">[docs]</a>    <span class="k">def</span> <span class="nf">sum</span><span class="p">(</span>
@@ -638,11 +641,11 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="n">axis</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
         <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">out</span><span class="p">:</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">keepdims</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">_NoValue</span><span class="p">,</span>
+        <span class="n">keepdims</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">where</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">=</span> <span class="n">_NoValue</span><span class="p">,</span>
     <span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;Sum value of the array along a given axis.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Sum value of the array along a given axis.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="n">axis</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="n">out</span><span class="p">,</span> <span class="n">keepdims</span><span class="o">=</span><span class="n">keepdims</span><span class="p">,</span> <span class="n">where</span><span class="o">=</span><span class="n">where</span><span class="p">)</span></div>
     
 <div class="viewcode-block" id="MetaArray.std"><a class="viewcode-back" href="../../../../apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.std">[docs]</a>    <span class="k">def</span> <span class="nf">std</span><span class="p">(</span>
@@ -651,15 +654,15 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">out</span><span class="p">:</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">ddof</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span>
-        <span class="n">keepdims</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">_NoValue</span><span class="p">,</span>
+        <span class="n">keepdims</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">where</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">=</span> <span class="n">_NoValue</span><span class="p">,</span>
     <span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;Standard deviation of the array along a given axis.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Standard deviation of the array along a given axis.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="n">axis</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span> <span class="n">out</span><span class="o">=</span><span class="n">out</span><span class="p">,</span> <span class="n">ddof</span><span class="o">=</span><span class="n">ddof</span><span class="p">,</span> <span class="n">keepdims</span><span class="o">=</span><span class="n">keepdims</span><span class="p">,</span> <span class="n">where</span><span class="o">=</span><span class="n">where</span><span class="p">)</span></div>
 
     <span class="k">def</span> <span class="nf">_dimension_matches</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">array</span><span class="p">:</span> <span class="n">MetaArray</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;Check if dimension satisfies ``self &lt;: array``.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Check if dimension satisfies ``self &lt;: array``.&quot;&quot;&quot;</span>
         <span class="n">img_shape</span> <span class="o">=</span> <span class="n">array</span><span class="o">.</span><span class="n">shape</span>
         <span class="n">label_shape</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">shape</span>
         <span class="k">return</span> <span class="nb">all</span><span class="p">(</span>
@@ -675,7 +678,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="n">clim</span><span class="p">:</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">alpha</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Convert array to an RGBA image with given colormap.</span>
 
 <span class="sd">        Parameters</span>
@@ -819,7 +822,7 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="k">except</span> <span class="n">ImageAxesError</span><span class="p">:</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">axes</span> <span class="o">=</span> <span class="kc">None</span>
         
-        <span class="k">return</span> <span class="kc">None</span>
+        <span class="k">return</span> <span class="bp">self</span>
     
     <span class="k">def</span> <span class="nf">_process_output</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">func</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">):</span>
         <span class="c1"># find the largest MetaArray. Largest because of broadcasting.</span>
@@ -838,12 +841,12 @@ <h1>Source code for impy.arrays.bases.metaarray</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">new_axes</span><span class="o">=</span><span class="n">new_axes</span><span class="p">)</span>
     
     <span class="k">def</span> <span class="nf">_inherit_meta</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">obj</span><span class="p">:</span> <span class="n">AxesMixin</span><span class="p">,</span> <span class="n">ufunc</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Copy axis etc. from obj.</span>
 <span class="sd">        This is called in __array_ufunc__(). Unlike _set_info(), keyword `axis` must be</span>
 <span class="sd">        considered because it changes `ndim`.</span>
 <span class="sd">        &quot;&quot;&quot;</span>
-        <span class="k">if</span> <span class="s2">&quot;axis&quot;</span> <span class="ow">in</span> <span class="n">kwargs</span> <span class="ow">and</span> <span class="s2">&quot;keepdims&quot;</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
+        <span class="k">if</span> <span class="s2">&quot;axis&quot;</span> <span class="ow">in</span> <span class="n">kwargs</span> <span class="ow">and</span> <span class="ow">not</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;keepdims&quot;</span><span class="p">,</span> <span class="kc">False</span><span class="p">):</span>
             <span class="n">new_axes</span> <span class="o">=</span> <span class="n">obj</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">kwargs</span><span class="p">[</span><span class="s2">&quot;axis&quot;</span><span class="p">])</span>
         <span class="k">else</span><span class="p">:</span>
             <span class="n">new_axes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_INHERIT</span>
diff --git a/docs/_modules/impy/arrays/bases/overload.html b/docs/_modules/impy/arrays/bases/overload.html
index 7b8fc893..d77e0985 100644
--- a/docs/_modules/impy/arrays/bases/overload.html
+++ b/docs/_modules/impy/arrays/bases/overload.html
@@ -3,7 +3,7 @@
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.arrays.bases.overload &mdash; impy 2.2.0 documentation</title>
+  <title>impy.arrays.bases.overload &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../../../../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../../../../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -11,9 +11,8 @@
   <![endif]-->
   
         <script data-url_root="../../../../" id="documentation_options" src="../../../../_static/documentation_options.js"></script>
-        <script src="../../../../_static/jquery.js"></script>
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         <script src="../../../../_static/doctools.js"></script>
+        <script src="../../../../_static/sphinx_highlight.js"></script>
     <script src="../../../../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../../../../genindex.html" />
     <link rel="search" title="Search" href="../../../../search.html" /> 
@@ -24,14 +23,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../../../../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../../../../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../../../../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
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   </form>
@@ -58,9 +61,9 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../../../../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../../../index.html">Module code</a> &raquo;</li>
-      <li>impy.arrays.bases.overload</li>
+      <li><a href="../../../../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../../../index.html">Module code</a></li>
+      <li class="breadcrumb-item active">impy.arrays.bases.overload</li>
       <li class="wy-breadcrumbs-aside">
       </li>
   </ul>
@@ -253,6 +256,29 @@ <h1>Source code for impy.arrays.bases.overload</h1><div class="highlight"><pre>
     <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">new_axes</span><span class="o">=</span><span class="n">axes_list</span><span class="p">)</span>
     <span class="k">return</span> <span class="n">out</span>
 
+<span class="c1"># argmax does not support axis as tuple</span>
+<span class="nd">@MetaArray</span><span class="o">.</span><span class="n">implements</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">)</span>
+<span class="k">def</span> <span class="nf">_</span><span class="p">(</span><span class="n">img</span><span class="p">:</span> <span class="n">MetaArray</span><span class="p">,</span> <span class="n">axis</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="n">AxisLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span>
+    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">axis</span><span class="p">,</span> <span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="n">Axis</span><span class="p">)):</span>
+        <span class="n">axis</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">axisof</span><span class="p">(</span><span class="n">axis</span><span class="p">)</span>
+    <span class="n">new_axes</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">axis</span><span class="p">)</span>
+    <span class="n">out</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="n">axis</span><span class="p">)</span>
+    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
+        <span class="n">out</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="vm">__class__</span><span class="p">)</span>
+        <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">new_axes</span><span class="o">=</span><span class="n">new_axes</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">out</span>
+
+<span class="nd">@MetaArray</span><span class="o">.</span><span class="n">implements</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argmin</span><span class="p">)</span>
+<span class="k">def</span> <span class="nf">_</span><span class="p">(</span><span class="n">img</span><span class="p">:</span> <span class="n">MetaArray</span><span class="p">,</span> <span class="n">axis</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="n">AxisLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span>
+    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">axis</span><span class="p">,</span> <span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="n">Axis</span><span class="p">)):</span>
+        <span class="n">axis</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">axisof</span><span class="p">(</span><span class="n">axis</span><span class="p">)</span>
+    <span class="n">new_axes</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">axis</span><span class="p">)</span>
+    <span class="n">out</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">argmin</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="n">axis</span><span class="p">)</span>
+    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
+        <span class="n">out</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="vm">__class__</span><span class="p">)</span>
+        <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">new_axes</span><span class="o">=</span><span class="n">new_axes</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">out</span>
+
 <span class="nd">@MetaArray</span><span class="o">.</span><span class="n">implements</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">cross</span><span class="p">)</span>
 <span class="k">def</span> <span class="nf">_</span><span class="p">(</span>
     <span class="n">img</span><span class="p">:</span> <span class="n">MetaArray</span><span class="p">,</span>
@@ -278,6 +304,41 @@ <h1>Source code for impy.arrays.bases.overload</h1><div class="highlight"><pre>
     <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">new_axes</span><span class="o">=</span><span class="n">img</span><span class="o">.</span><span class="n">axes</span><span class="p">)</span>
     <span class="k">return</span> <span class="n">out</span>
 
+<span class="nd">@MetaArray</span><span class="o">.</span><span class="n">implements</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">diff</span><span class="p">)</span>
+<span class="k">def</span> <span class="nf">_</span><span class="p">(</span>
+    <span class="n">img</span><span class="p">:</span> <span class="n">MetaArray</span><span class="p">,</span>
+    <span class="n">n</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span>
+    <span class="n">axis</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="n">AxisLike</span> <span class="o">=</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span>
+    <span class="n">prepend</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
+    <span class="n">append</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
+<span class="p">):</span>
+    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">axis</span><span class="p">,</span> <span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="n">Axis</span><span class="p">)):</span>
+        <span class="n">axis</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">axisof</span><span class="p">(</span><span class="n">axis</span><span class="p">)</span>
+    <span class="n">kwargs</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="n">n</span><span class="o">=</span><span class="n">n</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="n">axis</span><span class="p">)</span>
+    <span class="k">if</span> <span class="n">prepend</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
+        <span class="n">kwargs</span><span class="p">[</span><span class="s2">&quot;prepend&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">prepend</span>
+    <span class="k">if</span> <span class="n">append</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
+        <span class="n">kwargs</span><span class="p">[</span><span class="s2">&quot;append&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">append</span>
+    <span class="n">out</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">diff</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
+    <span class="n">out</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="vm">__class__</span><span class="p">)</span>
+    <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">new_axes</span><span class="o">=</span><span class="n">img</span><span class="o">.</span><span class="n">axes</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">out</span>
+
+<span class="nd">@MetaArray</span><span class="o">.</span><span class="n">implements</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">gradient</span><span class="p">)</span>
+<span class="k">def</span> <span class="nf">_</span><span class="p">(</span><span class="n">img</span><span class="p">:</span> <span class="n">MetaArray</span><span class="p">,</span> <span class="o">*</span><span class="n">varargs</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">edge_order</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
+    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">axis</span><span class="p">,</span> <span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="n">Axis</span><span class="p">)):</span>
+        <span class="n">axis</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">axisof</span><span class="p">(</span><span class="n">axis</span><span class="p">)</span>
+    <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">axis</span><span class="p">,</span> <span class="n">Axes</span><span class="p">):</span>
+        <span class="n">axis</span> <span class="o">=</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="n">axisof</span><span class="p">(</span><span class="n">ax</span><span class="p">)</span> <span class="k">for</span> <span class="n">ax</span> <span class="ow">in</span> <span class="n">axis</span><span class="p">)</span>
+    <span class="n">out</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">gradient</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="o">*</span><span class="n">varargs</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="n">axis</span><span class="p">,</span> <span class="n">edge_order</span><span class="o">=</span><span class="n">edge_order</span><span class="p">)</span>
+    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
+        <span class="n">out</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="vm">__class__</span><span class="p">)</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">new_axes</span><span class="o">=</span><span class="n">img</span><span class="o">.</span><span class="n">axes</span><span class="p">)</span>
+    <span class="k">else</span><span class="p">:</span>
+        <span class="n">out</span> <span class="o">=</span> <span class="p">[</span><span class="n">arr</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="vm">__class__</span><span class="p">)</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">new_axes</span><span class="o">=</span><span class="n">img</span><span class="o">.</span><span class="n">axes</span><span class="p">)</span> <span class="k">for</span> <span class="n">arr</span> <span class="ow">in</span> <span class="n">out</span><span class="p">]</span>
+        <span class="n">out</span> <span class="o">=</span> <span class="n">DataList</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">out</span>
+
+
 <span class="c1"># This function is ported from numpy.core.numeric.normalize_axis_tuple</span>
 <div class="viewcode-block" id="np_normalize_axis_tuple"><a class="viewcode-back" href="../../../../apidoc/impy.arrays.bases.html#impy.arrays.bases.overload.np_normalize_axis_tuple">[docs]</a><span class="k">def</span> <span class="nf">np_normalize_axis_tuple</span><span class="p">(</span><span class="n">axis</span><span class="p">,</span> <span class="n">ndim</span><span class="p">,</span> <span class="n">argname</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">allow_duplicate</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
     <span class="c1"># Optimization to speed-up the most common cases.</span>
diff --git a/docs/_modules/impy/arrays/imgarray.html b/docs/_modules/impy/arrays/imgarray.html
index 2082a49e..1fb87522 100644
--- a/docs/_modules/impy/arrays/imgarray.html
+++ b/docs/_modules/impy/arrays/imgarray.html
@@ -3,7 +3,7 @@
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.arrays.imgarray &mdash; impy 2.2.0 documentation</title>
+  <title>impy.arrays.imgarray &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../../../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -11,9 +11,8 @@
   <![endif]-->
   
         <script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
-        <script src="../../../_static/jquery.js"></script>
-        <script src="../../../_static/underscore.js"></script>
         <script src="../../../_static/doctools.js"></script>
+        <script src="../../../_static/sphinx_highlight.js"></script>
     <script src="../../../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../../../genindex.html" />
     <link rel="search" title="Search" href="../../../search.html" /> 
@@ -24,14 +23,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../../../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../../../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../../../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -58,9 +61,9 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../../../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../../index.html">Module code</a> &raquo;</li>
-      <li>impy.arrays.imgarray</li>
+      <li><a href="../../../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../../index.html">Module code</a></li>
+      <li class="breadcrumb-item active">impy.arrays.imgarray</li>
       <li class="wy-breadcrumbs-aside">
       </li>
   </ul>
@@ -81,34 +84,34 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
 <span class="kn">from</span> <span class="nn">.label</span> <span class="kn">import</span> <span class="n">Label</span>
 <span class="kn">from</span> <span class="nn">.phasearray</span> <span class="kn">import</span> <span class="n">PhaseArray</span>
 <span class="kn">from</span> <span class="nn">.specials</span> <span class="kn">import</span> <span class="n">PropArray</span>
+<span class="kn">from</span> <span class="nn">.tiled</span> <span class="kn">import</span> <span class="n">TiledAccessor</span>
 
 <span class="kn">from</span> <span class="nn">._utils._skimage</span> <span class="kn">import</span> <span class="n">skexp</span><span class="p">,</span> <span class="n">skfeat</span><span class="p">,</span> <span class="n">skfil</span><span class="p">,</span> <span class="n">skimage</span><span class="p">,</span> <span class="n">skmes</span><span class="p">,</span> <span class="n">skres</span><span class="p">,</span> <span class="n">skseg</span><span class="p">,</span> <span class="n">sktrans</span>
 <span class="kn">from</span> <span class="nn">._utils</span> <span class="kn">import</span> <span class="n">_filters</span><span class="p">,</span> <span class="n">_linalg</span><span class="p">,</span> <span class="n">_deconv</span><span class="p">,</span> <span class="n">_misc</span><span class="p">,</span> <span class="n">_glcm</span><span class="p">,</span> <span class="n">_docs</span><span class="p">,</span> <span class="n">_transform</span><span class="p">,</span> <span class="n">_structures</span><span class="p">,</span> <span class="n">_corr</span>
 
-<span class="kn">from</span> <span class="nn">..utils.axesop</span> <span class="kn">import</span> <span class="n">add_axes</span><span class="p">,</span> <span class="n">switch_slice</span><span class="p">,</span> <span class="n">complement_axes</span><span class="p">,</span> <span class="n">find_first_appeared</span>
-<span class="kn">from</span> <span class="nn">..utils.deco</span> <span class="kn">import</span> <span class="n">check_input_and_output</span><span class="p">,</span> <span class="n">dims_to_spatial_axes</span><span class="p">,</span> <span class="n">same_dtype</span>
-<span class="kn">from</span> <span class="nn">..utils.gauss</span> <span class="kn">import</span> <span class="n">GaussianBackground</span><span class="p">,</span> <span class="n">GaussianParticle</span>
-<span class="kn">from</span> <span class="nn">..utils.misc</span> <span class="kn">import</span> <span class="n">check_nd</span><span class="p">,</span> <span class="n">largest_zeros</span>
-<span class="kn">from</span> <span class="nn">..utils.slicer</span> <span class="kn">import</span> <span class="n">solve_slicer</span>
+<span class="kn">from</span> <span class="nn">impy.utils.axesop</span> <span class="kn">import</span> <span class="n">add_axes</span><span class="p">,</span> <span class="n">switch_slice</span><span class="p">,</span> <span class="n">complement_axes</span><span class="p">,</span> <span class="n">find_first_appeared</span>
+<span class="kn">from</span> <span class="nn">impy.utils.deco</span> <span class="kn">import</span> <span class="n">check_input_and_output</span><span class="p">,</span> <span class="n">dims_to_spatial_axes</span><span class="p">,</span> <span class="n">same_dtype</span>
+<span class="kn">from</span> <span class="nn">impy.utils.gauss</span> <span class="kn">import</span> <span class="n">GaussianBackground</span><span class="p">,</span> <span class="n">GaussianParticle</span>
+<span class="kn">from</span> <span class="nn">impy.utils.misc</span> <span class="kn">import</span> <span class="n">check_nd</span><span class="p">,</span> <span class="n">largest_zeros</span>
+<span class="kn">from</span> <span class="nn">impy.utils.slicer</span> <span class="kn">import</span> <span class="n">solve_slicer</span>
 
-<span class="kn">from</span> <span class="nn">..collections</span> <span class="kn">import</span> <span class="n">DataDict</span>
-<span class="kn">from</span> <span class="nn">..axes</span> <span class="kn">import</span> <span class="n">AxisLike</span><span class="p">,</span> <span class="n">slicer</span><span class="p">,</span> <span class="n">Axes</span><span class="p">,</span> <span class="n">Axis</span>
-<span class="kn">from</span> <span class="nn">.._types</span> <span class="kn">import</span> <span class="n">nDInt</span><span class="p">,</span> <span class="n">nDFloat</span><span class="p">,</span> <span class="n">Dims</span><span class="p">,</span> <span class="n">Coords</span><span class="p">,</span> <span class="n">AxesTargetedSlicer</span><span class="p">,</span> <span class="n">PaddingMode</span>
-<span class="kn">from</span> <span class="nn">.._const</span> <span class="kn">import</span> <span class="n">Const</span>
-<span class="kn">from</span> <span class="nn">..array_api</span> <span class="kn">import</span> <span class="n">xp</span><span class="p">,</span> <span class="n">cupy_dispatcher</span>
+<span class="kn">from</span> <span class="nn">impy.collections</span> <span class="kn">import</span> <span class="n">DataDict</span>
+<span class="kn">from</span> <span class="nn">impy.axes</span> <span class="kn">import</span> <span class="n">AxisLike</span><span class="p">,</span> <span class="n">slicer</span><span class="p">,</span> <span class="n">Axes</span><span class="p">,</span> <span class="n">Axis</span>
+<span class="kn">from</span> <span class="nn">impy._types</span> <span class="kn">import</span> <span class="n">nDInt</span><span class="p">,</span> <span class="n">nDFloat</span><span class="p">,</span> <span class="n">Dims</span><span class="p">,</span> <span class="n">Coords</span><span class="p">,</span> <span class="n">AxesTargetedSlicer</span><span class="p">,</span> <span class="n">PaddingMode</span>
+<span class="kn">from</span> <span class="nn">impy._const</span> <span class="kn">import</span> <span class="n">Const</span>
+<span class="kn">from</span> <span class="nn">impy.array_api</span> <span class="kn">import</span> <span class="n">xp</span><span class="p">,</span> <span class="n">cupy_dispatcher</span>
 
 <span class="k">if</span> <span class="n">TYPE_CHECKING</span><span class="p">:</span>
     <span class="kn">from</span> <span class="nn">..frame</span> <span class="kn">import</span> <span class="n">MarkerFrame</span>
-    <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Literal</span><span class="p">,</span> <span class="n">Union</span>
-    <span class="n">ThreasholdMethod</span> <span class="o">=</span> <span class="n">Union</span><span class="p">[</span>
-        <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;isodata&quot;</span><span class="p">],</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;li&quot;</span><span class="p">],</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;local&quot;</span><span class="p">],</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;mean&quot;</span><span class="p">],</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;min&quot;</span><span class="p">],</span>
-        <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;minimum&quot;</span><span class="p">],</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;niblack&quot;</span><span class="p">],</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;otsu&quot;</span><span class="p">],</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;sauvola&quot;</span><span class="p">],</span> 
-        <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;triangle&quot;</span><span class="p">],</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;yen&quot;</span><span class="p">]</span>
+    <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Literal</span>
+    <span class="n">ThreasholdMethod</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span>
+        <span class="s2">&quot;isodata&quot;</span><span class="p">,</span> <span class="s2">&quot;li&quot;</span><span class="p">,</span> <span class="s2">&quot;local&quot;</span><span class="p">,</span> <span class="s2">&quot;mean&quot;</span><span class="p">,</span> <span class="s2">&quot;min&quot;</span><span class="p">,</span> <span class="s2">&quot;minimum&quot;</span><span class="p">,</span> <span class="s2">&quot;niblack&quot;</span><span class="p">,</span> <span class="s2">&quot;otsu&quot;</span><span class="p">,</span> <span class="s2">&quot;sauvola&quot;</span><span class="p">,</span>
+        <span class="s2">&quot;triangle&quot;</span><span class="p">,</span> <span class="s2">&quot;yen&quot;</span>
     <span class="p">]</span>
     <span class="n">FftShape</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;same&quot;</span><span class="p">,</span> <span class="s2">&quot;square&quot;</span><span class="p">]</span>
 
 <div class="viewcode-block" id="ImgArray"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray">[docs]</a><span class="k">class</span> <span class="nc">ImgArray</span><span class="p">(</span><span class="n">LabeledArray</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    An n-D array for image analysis.</span>
 <span class="sd">    </span>
 <span class="sd">    Attributes</span>
@@ -123,6 +126,8 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
 <span class="sd">    source : Path</span>
 <span class="sd">        Source file of the image.</span>
 <span class="sd">    &quot;&quot;&quot;</span>
+    <span class="n">tiled</span><span class="p">:</span> <span class="n">TiledAccessor</span><span class="p">[</span><span class="n">ImgArray</span><span class="p">]</span> <span class="o">=</span> <span class="n">TiledAccessor</span><span class="p">()</span>
+
 <div class="viewcode-block" id="ImgArray.affine"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.affine">[docs]</a>    <span class="nd">@_docs</span><span class="o">.</span><span class="n">write_docs</span>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@same_dtype</span><span class="p">(</span><span class="n">asfloat</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
@@ -132,7 +137,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">order</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="n">mode</span><span class="p">:</span> <span class="n">PaddingMode</span> <span class="o">=</span> <span class="s2">&quot;constant&quot;</span><span class="p">,</span> <span class="n">cval</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="n">output_shape</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">prefilter</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Convert image by Affine transformation. 2D Affine transformation is written as:</span>
 <span class="sd">        </span>
 <span class="sd">        .. math::</span>
@@ -203,7 +208,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="mi">2</span><span class="p">,</span>
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        2D rotation of an image around a point. Outside will be padded with zero. For n-D images,</span>
 <span class="sd">        this implementation is faster than ``scipy.ndimage.rotate``.</span>
 
@@ -251,7 +256,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">order</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        2D stretching of an image from a point.</span>
 
 <span class="sd">        Parameters</span>
@@ -292,39 +297,53 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@same_dtype</span><span class="p">(</span><span class="n">asfloat</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="k">def</span> <span class="nf">rescale</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">,</span>
-        <span class="n">scale</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mi">1</span><span class="o">/</span><span class="mi">16</span><span class="p">,</span>
+        <span class="n">scale</span><span class="p">:</span> <span class="n">nDFloat</span> <span class="o">=</span> <span class="mi">1</span><span class="o">/</span><span class="mi">16</span><span class="p">,</span>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">order</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">mode</span><span class="p">:</span> <span class="n">PaddingMode</span> <span class="o">=</span> <span class="s2">&quot;reflect&quot;</span><span class="p">,</span>
         <span class="n">cval</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
-<span class="sd">        Rescale image.</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">        Rescale image by applying the diagonal component of Affine matrix.</span>
 
 <span class="sd">        Parameters</span>
 <span class="sd">        ----------</span>
 <span class="sd">        scale : float, optional</span>
-<span class="sd">            scale of the new image.</span>
+<span class="sd">            Relative scale of the new image. scale 1/2 means that the shape of</span>
+<span class="sd">            the output image will be (N/2, ...).</span>
 <span class="sd">        {order}{mode}{cval}{dims}</span>
 <span class="sd">        </span>
 <span class="sd">        Returns</span>
 <span class="sd">        -------</span>
 <span class="sd">        ImgArray</span>
 <span class="sd">            Rescaled image.</span>
-<span class="sd">        &quot;&quot;&quot;</span>        
-        <span class="n">outshape</span> <span class="o">=</span> <span class="n">switch_slice</span><span class="p">(</span>
-            <span class="n">dims</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">,</span> <span class="n">ifin</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span><span class="o">*</span><span class="n">scale</span><span class="p">,</span> <span class="n">ifnot</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span>
-        <span class="p">)</span>
-        <span class="n">gb</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">prod</span><span class="p">(</span><span class="n">outshape</span><span class="p">)</span> <span class="o">*</span> <span class="mi">4</span><span class="o">/</span><span class="mf">1e9</span>
+<span class="sd">        &quot;&quot;&quot;</span>
+        <span class="n">scale_is_seq</span> <span class="o">=</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">scale</span><span class="p">,</span> <span class="s2">&quot;__iter__&quot;</span><span class="p">)</span>
+        
+        <span class="c1"># Check if output is too large.</span>
+        <span class="n">gb</span> <span class="o">=</span> <span class="o">-</span><span class="mi">1</span>
+        <span class="k">if</span> <span class="ow">not</span> <span class="n">scale_is_seq</span> <span class="ow">and</span> <span class="n">scale</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">:</span>
+            <span class="n">gb</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">prod</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span> <span class="o">*</span> <span class="p">(</span><span class="n">scale</span> <span class="o">**</span> <span class="nb">len</span><span class="p">(</span><span class="n">dims</span><span class="p">))</span> <span class="o">/</span> <span class="mf">1e9</span>
+        <span class="k">elif</span> <span class="n">scale_is_seq</span> <span class="ow">and</span> <span class="n">np</span><span class="o">.</span><span class="n">prod</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">scale</span><span class="p">))</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">:</span>
+            <span class="n">gb</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">prod</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">prod</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">scale</span><span class="p">))</span> <span class="o">/</span> <span class="mf">1e9</span>
         <span class="k">if</span> <span class="n">gb</span> <span class="o">&gt;</span> <span class="n">Const</span><span class="p">[</span><span class="s2">&quot;MAX_GB&quot;</span><span class="p">]:</span>
-            <span class="k">raise</span> <span class="ne">MemoryError</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Too large: </span><span class="si">{</span><span class="n">gb</span><span class="si">}</span><span class="s2"> GB&quot;</span><span class="p">)</span>
-        <span class="n">scale_</span> <span class="o">=</span> <span class="p">[</span><span class="n">scale</span> <span class="k">if</span> <span class="n">a</span> <span class="ow">in</span> <span class="n">dims</span> <span class="k">else</span> <span class="mi">1</span> <span class="k">for</span> <span class="n">a</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">]</span>
+            <span class="k">raise</span> <span class="ne">MemoryError</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Output image is too large: </span><span class="si">{</span><span class="n">gb</span><span class="si">}</span><span class="s2"> GB&quot;</span><span class="p">)</span>
+        
+        <span class="k">if</span> <span class="n">scale_is_seq</span><span class="p">:</span>
+            <span class="n">scale</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">scale</span><span class="p">)</span>
+            <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">scale</span><span class="p">)</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">dims</span><span class="p">):</span>
+                <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
+                    <span class="s2">&quot;scale must have the same length as the spatial dimensions.&quot;</span>
+                <span class="p">)</span>
+            <span class="n">it</span> <span class="o">=</span> <span class="nb">iter</span><span class="p">(</span><span class="n">scale</span><span class="p">)</span>
+            <span class="n">scale_</span> <span class="o">=</span> <span class="p">[</span><span class="nb">next</span><span class="p">(</span><span class="n">it</span><span class="p">)</span> <span class="k">if</span> <span class="n">a</span> <span class="ow">in</span> <span class="n">dims</span> <span class="k">else</span> <span class="mi">1</span> <span class="k">for</span> <span class="n">a</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">]</span>
+        <span class="k">else</span><span class="p">:</span>
+            <span class="n">scale_</span> <span class="o">=</span> <span class="p">[</span><span class="n">scale</span> <span class="k">if</span> <span class="n">a</span> <span class="ow">in</span> <span class="n">dims</span> <span class="k">else</span> <span class="mi">1</span> <span class="k">for</span> <span class="n">a</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">]</span>
         <span class="n">out</span> <span class="o">=</span> <span class="n">sktrans</span><span class="o">.</span><span class="n">rescale</span><span class="p">(</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">scale_</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="n">order</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="n">mode</span><span class="p">,</span> <span class="n">cval</span><span class="o">=</span><span class="n">cval</span><span class="p">,</span> <span class="n">anti_aliasing</span><span class="o">=</span><span class="kc">False</span>
         <span class="p">)</span>
-        <span class="n">out</span><span class="p">:</span> <span class="n">ImgArray</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="p">)</span>
-        <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
+        <span class="n">out</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="p">)</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
         <span class="n">out</span><span class="o">.</span><span class="n">axes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
         <span class="n">out</span><span class="o">.</span><span class="n">set_scale</span><span class="p">({</span><span class="n">a</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">scale</span><span class="p">[</span><span class="n">a</span><span class="p">]</span><span class="o">/</span><span class="n">scale</span> <span class="k">for</span> <span class="n">a</span><span class="p">,</span> <span class="n">scale</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">,</span> <span class="n">scale_</span><span class="p">)})</span>
         <span class="k">return</span> <span class="n">out</span></div>
@@ -340,7 +359,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">check_edges</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Binning of images. This function is similar to ``rescale`` but is strictly </span>
 <span class="sd">        binned by :math:`N \times N` blocks. Also, any numpy functions that accept </span>
 <span class="sd">        &quot;axis&quot; argument are supported for reduce functions.</span>
@@ -375,11 +394,11 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="p">)</span>
         
         <span class="n">reshaped_img</span> <span class="o">=</span> <span class="n">img_to_reshape</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">shape</span><span class="p">)</span>
-        <span class="n">axes_to_reduce</span> <span class="o">=</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">i</span><span class="o">*</span><span class="mi">2</span><span class="o">+</span><span class="mi">1</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">ndim</span><span class="p">))</span>
+        <span class="n">axes_to_reduce</span> <span class="o">=</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">i</span> <span class="o">*</span> <span class="mi">2</span> <span class="o">+</span> <span class="mi">1</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">ndim</span><span class="p">))</span>
         <span class="n">out</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">=</span> <span class="n">binfunc</span><span class="p">(</span><span class="n">reshaped_img</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="n">axes_to_reduce</span><span class="p">)</span>
         <span class="n">out</span><span class="p">:</span> <span class="n">ImgArray</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="p">)</span>
         <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
-        <span class="n">out</span><span class="o">.</span><span class="n">axes</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">)</span> <span class="c1"># _set_info does not pass copy so new axes must be defined here.</span>
+        <span class="n">out</span><span class="o">.</span><span class="n">axes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>  <span class="c1"># _set_info does not pass copy so new axes must be defined here.</span>
         <span class="n">out</span><span class="o">.</span><span class="n">set_scale</span><span class="p">(</span>
             <span class="p">{</span><span class="n">a</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">scale</span><span class="p">[</span><span class="n">a</span><span class="p">]</span><span class="o">/</span><span class="n">scale</span> <span class="k">for</span> <span class="n">a</span><span class="p">,</span> <span class="n">scale</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">,</span> <span class="n">scale_</span><span class="p">)}</span>
         <span class="p">)</span>
@@ -390,13 +409,13 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="k">def</span> <span class="nf">radial_profile</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">,</span>
         <span class="n">nbin</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">32</span><span class="p">,</span>
-        <span class="n">center</span><span class="p">:</span> <span class="n">Iterable</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">center</span><span class="p">:</span> <span class="n">Iterable</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">r_max</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> 
         <span class="o">*</span><span class="p">,</span> 
         <span class="n">method</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;mean&quot;</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PropArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Calculate radial profile of images. Scale along each axis will be considered, </span>
 <span class="sd">        i.e., rather ellipsoidal profile will be calculated instead if scales are</span>
 <span class="sd">        different between axes.</span>
@@ -485,7 +504,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">mask</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="s2">&quot;yx&quot;</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Fit the image to 2-D Gaussian background.</span>
 
 <span class="sd">        Parameters</span>
@@ -535,7 +554,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="ImgArray.gauss_correction"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.gauss_correction">[docs]</a>    <span class="nd">@same_dtype</span><span class="p">(</span><span class="n">asfloat</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">gauss_correction</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ref</span><span class="p">:</span> <span class="n">ImgArray</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">scale</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mi">1</span><span class="o">/</span><span class="mi">16</span><span class="p">,</span> <span class="n">median_radius</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mi">15</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Correct unevenly distributed excitation light using Gaussian fitting. This method subtracts</span>
 <span class="sd">        background intensity at the same time. If input image is uint, then output value under 0 will</span>
 <span class="sd">        replaced with 0. If you want to quantify background, it is necessary to first convert input</span>
@@ -590,7 +609,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="ImgArray.hessian_eigval"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.hessian_eigval">[docs]</a>    <span class="nd">@_docs</span><span class="o">.</span><span class="n">write_docs</span>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="k">def</span> <span class="nf">hessian_eigval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sigma</span><span class="p">:</span> <span class="n">nDFloat</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Calculate Hessian&#39;s eigenvalues for each image. </span>
 <span class="sd">        </span>
 <span class="sd">        Parameters</span>
@@ -631,7 +650,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="ImgArray.hessian_eig"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.hessian_eig">[docs]</a>    <span class="nd">@_docs</span><span class="o">.</span><span class="n">write_docs</span>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="k">def</span> <span class="nf">hessian_eig</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sigma</span><span class="p">:</span> <span class="n">nDFloat</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">ImgArray</span><span class="p">,</span> <span class="n">ImgArray</span><span class="p">]:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Calculate Hessian&#39;s eigenvalues and eigenvectors.</span>
 
 <span class="sd">        Parameters</span>
@@ -663,7 +682,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">structure_tensor_eigval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sigma</span><span class="p">:</span> <span class="n">nDFloat</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Calculate structure tensor&#39;s eigenvalues and eigenvectors.</span>
 
 <span class="sd">        Parameters</span>
@@ -697,7 +716,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">structure_tensor_eig</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sigma</span><span class="p">:</span> <span class="n">nDFloat</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span><span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">ImgArray</span><span class="p">,</span> <span class="n">ImgArray</span><span class="p">]:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Calculate structure tensor&#39;s eigenvalues and eigenvectors.</span>
 
 <span class="sd">        Parameters</span>
@@ -738,7 +757,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Sobel filter. This filter is useful for edge detection.</span>
 
 <span class="sd">        Parameters</span>
@@ -776,7 +795,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> 
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Butterworth low-pass filter.</span>
 
 <span class="sd">        Parameters</span>
@@ -822,7 +841,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Butterworth low-pass filter in real space. Butterworth kernel is created first using inverse</span>
 <span class="sd">        Fourier transform of weight function.</span>
 
@@ -855,67 +874,21 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">ker</span> <span class="o">=</span> <span class="n">ker_all</span><span class="p">[</span><span class="nb">tuple</span><span class="p">(</span><span class="n">sl</span><span class="p">)]</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">convolve</span><span class="p">(</span><span class="n">ker</span><span class="p">)</span></div>
     
-<div class="viewcode-block" id="ImgArray.tiled_lowpass_filter"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.tiled_lowpass_filter">[docs]</a>    <span class="nd">@_docs</span><span class="o">.</span><span class="n">write_docs</span>
-    <span class="nd">@dims_to_spatial_axes</span>
-    <span class="nd">@same_dtype</span><span class="p">(</span><span class="n">asfloat</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-    <span class="nd">@check_input_and_output</span>
+<div class="viewcode-block" id="ImgArray.tiled_lowpass_filter"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.tiled_lowpass_filter">[docs]</a>    <span class="nd">@same_dtype</span><span class="p">(</span><span class="n">asfloat</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="k">def</span> <span class="nf">tiled_lowpass_filter</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">,</span>
         <span class="n">cutoff</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.2</span><span class="p">,</span>
         <span class="n">chunks</span> <span class="o">=</span> <span class="s2">&quot;auto&quot;</span><span class="p">,</span>
         <span class="n">order</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">2</span><span class="p">,</span> 
         <span class="n">overlap</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">16</span><span class="p">,</span>
-        <span class="o">*</span><span class="p">,</span>
-        <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
+        <span class="o">**</span><span class="n">kwargs</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
-<span class="sd">        Tile-by-tile Butterworth low-pass filter. This method is an approximation of the standard</span>
-<span class="sd">        low-pass filter, which would be useful when the image is large.</span>
-
-<span class="sd">        Parameters</span>
-<span class="sd">        ----------</span>
-<span class="sd">        cutoff : float or array-like, default is 0.2</span>
-<span class="sd">            Cutoff frequency.</span>
-<span class="sd">        chunks : str or sequence of int</span>
-<span class="sd">            Chunk size of each lowpass filter task.</span>
-<span class="sd">        order : float, default is 2</span>
-<span class="sd">            Steepness of cutoff.</span>
-<span class="sd">        overlap : int, default is 16</span>
-<span class="sd">            Overlapping pixels at the edges of tiles.</span>
-<span class="sd">        {dims}{update}</span>
-
-<span class="sd">        Returns</span>
-<span class="sd">        -------</span>
-<span class="sd">        ImgArray</span>
-<span class="sd">            Filtered image.</span>
-<span class="sd">        &quot;&quot;&quot;</span>        
-        <span class="k">if</span> <span class="n">dims</span> <span class="o">!=</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">:</span>
-            <span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s2">&quot;batch processing not implemented yet.&quot;</span><span class="p">)</span>
-        <span class="kn">from</span> <span class="nn">._utils._skimage</span> <span class="kn">import</span> <span class="n">_get_ND_butterworth_filter</span>
-        <span class="kn">from</span> <span class="nn">dask</span> <span class="kn">import</span> <span class="n">array</span> <span class="k">as</span> <span class="n">da</span>
-
-        <span class="n">ndims</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">dims</span><span class="p">)</span>
-        <span class="n">cutoff</span> <span class="o">=</span> <span class="n">check_nd</span><span class="p">(</span><span class="n">cutoff</span><span class="p">,</span> <span class="n">ndims</span><span class="p">)</span>
-        <span class="k">if</span> <span class="nb">all</span><span class="p">((</span><span class="n">c</span> <span class="o">&gt;=</span> <span class="mf">0.5</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">ndims</span><span class="p">)</span> <span class="ow">or</span> <span class="n">c</span> <span class="o">&lt;=</span> <span class="mi">0</span><span class="p">)</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">cutoff</span><span class="p">):</span>
-            <span class="k">return</span> <span class="bp">self</span>
-        
-        <span class="n">depth</span> <span class="o">=</span> <span class="n">switch_slice</span><span class="p">(</span><span class="n">dims</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">,</span> <span class="n">overlap</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
-        
-        <span class="k">def</span> <span class="nf">func</span><span class="p">(</span><span class="n">arr</span><span class="p">):</span>
-            <span class="n">arr</span> <span class="o">=</span> <span class="n">xp</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="p">)</span>
-            <span class="n">shape</span> <span class="o">=</span> <span class="n">arr</span><span class="o">.</span><span class="n">shape</span>
-            <span class="n">weight</span> <span class="o">=</span> <span class="n">_get_ND_butterworth_filter</span><span class="p">(</span><span class="n">shape</span><span class="p">,</span> <span class="n">cutoff</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="kc">False</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
-            <span class="n">ft</span> <span class="o">=</span> <span class="n">xp</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">weight</span><span class="p">)</span> <span class="o">*</span> <span class="n">xp</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">rfftn</span><span class="p">(</span><span class="n">arr</span><span class="p">)</span>
-            <span class="n">ift</span> <span class="o">=</span> <span class="n">xp</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">irfftn</span><span class="p">(</span><span class="n">ft</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="n">shape</span><span class="p">)</span>
-            <span class="k">return</span> <span class="n">xp</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">(</span><span class="n">ift</span><span class="p">)</span>
-        
-        <span class="nb">input</span> <span class="o">=</span> <span class="n">da</span><span class="o">.</span><span class="n">from_array</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">)</span>
-        <span class="n">out</span> <span class="o">=</span> <span class="n">da</span><span class="o">.</span><span class="n">map_overlap</span><span class="p">(</span>
-            <span class="n">func</span><span class="p">,</span> <span class="nb">input</span><span class="p">,</span> <span class="n">depth</span><span class="o">=</span><span class="n">depth</span><span class="p">,</span> <span class="n">boundary</span><span class="o">=</span><span class="s2">&quot;reflect&quot;</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span>
-        <span class="p">)</span><span class="o">.</span><span class="n">compute</span><span class="p">()</span>
-        
-        <span class="k">return</span> <span class="n">out</span></div>
+        <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span>
+            <span class="s2">&quot;`tiled_lowpass_filter` is deprecated. Please use &quot;</span>
+            <span class="sa">f</span><span class="s2">&quot;`img.tiled(</span><span class="si">{</span><span class="n">chunks</span><span class="si">=}</span><span class="s2">, </span><span class="si">{</span><span class="n">overlap</span><span class="si">=}</span><span class="s2">).lowpass_filter(</span><span class="si">{</span><span class="n">cutoff</span><span class="si">=}</span><span class="s2">, </span><span class="si">{</span><span class="n">order</span><span class="si">=}</span><span class="s2">)` instead.&quot;</span><span class="p">,</span>
+            <span class="ne">DeprecationWarning</span><span class="p">,</span>
+        <span class="p">)</span>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">tiled</span><span class="p">(</span><span class="n">chunks</span><span class="p">,</span> <span class="n">overlap</span><span class="p">)</span><span class="o">.</span><span class="n">lowpass_filter</span><span class="p">(</span><span class="n">cutoff</span><span class="p">,</span> <span class="n">order</span><span class="p">)</span></div>
     
 <div class="viewcode-block" id="ImgArray.highpass_filter"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.highpass_filter">[docs]</a>    <span class="nd">@_docs</span><span class="o">.</span><span class="n">write_docs</span>
     <span class="nd">@dims_to_spatial_axes</span>
@@ -929,7 +902,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> 
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Butterworth high-pass filter.</span>
 
 <span class="sd">        Parameters</span>
@@ -971,7 +944,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> 
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        General linear convolution by running kernel filtering.</span>
 
 <span class="sd">        Parameters</span>
@@ -1006,7 +979,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Morphological erosion. </span>
 <span class="sd">        </span>
 <span class="sd">        If input is binary image, the running function will automatically switched to</span>
@@ -1047,7 +1020,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Morphological dilation. If input is binary image, the running function will automatically switched to</span>
 <span class="sd">        ``binary_dilation`` to speed up calculation.</span>
 
@@ -1086,7 +1059,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Morphological opening. If input is binary image, the running function will automatically switched to</span>
 <span class="sd">        ``binary_opening`` to speed up calculation.</span>
 
@@ -1125,7 +1098,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Morphological closing. </span>
 <span class="sd">        </span>
 <span class="sd">        If input is binary image, the running function will automatically switched to</span>
@@ -1166,7 +1139,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Tophat morphological image processing. This is useful for background subtraction.</span>
 
 <span class="sd">        Parameters</span>
@@ -1199,7 +1172,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Smoothen binary mask image at its edges. This is useful to make a &quot;soft mask&quot;.</span>
 <span class="sd">        </span>
 <span class="sd">        This method applies erosion/dilation to a binary image and then smooth its edges by Gaussian.</span>
@@ -1252,7 +1225,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">cval</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Mean filter. Kernel is filled with same values.</span>
 
 <span class="sd">        Parameters</span>
@@ -1284,7 +1257,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">cval</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Standard deviation filter.</span>
 
 <span class="sd">        Parameters</span>
@@ -1315,7 +1288,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">cval</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Coefficient of variance filter. </span>
 <span class="sd">        </span>
 <span class="sd">        For kernel area X, :math:`\frac{\sqrt{V[X]}}{E[X]}` is calculated. This filter</span>
@@ -1350,7 +1323,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Running multi-dimensional median filter. </span>
 <span class="sd">        </span>
 <span class="sd">        This filter is useful for deleting outliers generated by noise.</span>
@@ -1438,7 +1411,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">entropy_filter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">radius</span><span class="p">:</span> <span class="n">nDFloat</span> <span class="o">=</span> <span class="mi">5</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Running entropy filter. This filter is useful for detecting change in background distribution.</span>
 
 <span class="sd">        Parameters</span>
@@ -1462,7 +1435,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">enhance_contrast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">radius</span><span class="p">:</span><span class="n">nDFloat</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Enhance contrast filter.</span>
 
 <span class="sd">        Parameters</span>
@@ -1494,7 +1467,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">laplacian_filter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">radius</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Edge detection using Laplacian filter. Kernel is made by `skimage`&#39;s function.</span>
 
 <span class="sd">        Parameters</span>
@@ -1524,7 +1497,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">kalman_filter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">gain</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.8</span><span class="p">,</span> <span class="n">noise_var</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.05</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">along</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;t&quot;</span><span class="p">,</span> 
                       <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Kalman filter for image smoothing. This function is same as &quot;Kalman Stack Filter&quot; in ImageJ but support</span>
 <span class="sd">        batch processing. This filter is useful for preprocessing of particle tracking.</span>
 
@@ -1561,7 +1534,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="ImgArray.focus_map"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.focus_map">[docs]</a>    <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">focus_map</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">radius</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="mi">2</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PropArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Compute focus map using variance of Laplacian method. yx-plane with higher variance is likely a</span>
 <span class="sd">        focal plane because sharper image causes higher value of Laplacian on the edges.</span>
 
@@ -1595,7 +1568,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@same_dtype</span><span class="p">(</span><span class="n">asfloat</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">unmix</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">matrix</span><span class="p">,</span> <span class="n">bg</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">along</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;c&quot;</span><span class="p">,</span> <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Unmix fluorescence leakage between channels in a linear way. For example, a blue/green image,</span>
 <span class="sd">        fluorescent leakage can be written as following equation:</span>
 <span class="sd">        </span>
@@ -1643,7 +1616,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="c1"># check matrix and bg</span>
         <span class="n">matrix</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">matrix</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span>
         <span class="k">if</span> <span class="n">matrix</span><span class="o">.</span><span class="n">shape</span> <span class="o">!=</span> <span class="p">(</span><span class="n">n_chn</span><span class="p">,</span> <span class="n">n_chn</span><span class="p">):</span>
-            <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;`map_matrix` must have shape </span><span class="si">{</span><span class="p">(</span><span class="n">n_chn</span><span class="p">,</span> <span class="n">n_chn</span><span class="p">)</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+            <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;`map_matrix` must have shape </span><span class="si">{</span><span class="p">(</span><span class="n">n_chn</span><span class="p">,</span><span class="w"> </span><span class="n">n_chn</span><span class="p">)</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
         <span class="k">if</span> <span class="n">bg</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
             <span class="n">bg</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">n_chn</span><span class="p">)</span>
         <span class="k">else</span><span class="p">:</span>
@@ -1666,7 +1639,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@same_dtype</span><span class="p">(</span><span class="n">asfloat</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">fill_hole</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">thr</span><span class="p">:</span> <span class="nb">float</span><span class="o">|</span><span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;otsu&quot;</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Filling holes. See skimage&#39;s documents </span>
 <span class="sd">        `here &lt;https://scikit-image.org/docs/stable/auto_examples/features_detection/plot_holes_and_peaks.html&gt;`_.</span>
 
@@ -1697,21 +1670,29 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@same_dtype</span><span class="p">(</span><span class="n">asfloat</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="nd">@check_input_and_output</span>
-    <span class="k">def</span> <span class="nf">gaussian_filter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sigma</span><span class="p">:</span> <span class="n">nDFloat</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+    <span class="k">def</span> <span class="nf">gaussian_filter</span><span class="p">(</span>
+        <span class="bp">self</span><span class="p">,</span>
+        <span class="n">sigma</span><span class="p">:</span> <span class="n">nDFloat</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span>
+        <span class="o">*</span><span class="p">,</span>
+        <span class="n">fourier</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
+        <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
+    <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Run Gaussian filter (Gaussian blur).</span>
 <span class="sd">        </span>
 <span class="sd">        Parameters</span>
 <span class="sd">        ----------</span>
-<span class="sd">        {sigma}{dims}{update}</span>
+<span class="sd">        {sigma}{fourier}{dims}{update}</span>
 <span class="sd">            </span>
 <span class="sd">        Returns</span>
 <span class="sd">        -------</span>
 <span class="sd">        ImgArray</span>
 <span class="sd">            Filtered image.</span>
 <span class="sd">        &quot;&quot;&quot;</span>
+        <span class="n">filter_func</span> <span class="o">=</span> <span class="n">_filters</span><span class="o">.</span><span class="n">gaussian_filter_fourier</span> <span class="k">if</span> <span class="n">fourier</span> <span class="k">else</span> <span class="n">_filters</span><span class="o">.</span><span class="n">gaussian_filter</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_apply_dask</span><span class="p">(</span>
-            <span class="n">_filters</span><span class="o">.</span><span class="n">gaussian_filter</span><span class="p">,</span> 
+            <span class="n">filter_func</span><span class="p">,</span> 
             <span class="n">c_axes</span><span class="o">=</span><span class="n">complement_axes</span><span class="p">(</span><span class="n">dims</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">),</span> 
             <span class="n">args</span><span class="o">=</span><span class="p">(</span><span class="n">sigma</span><span class="p">,),</span> 
             <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span>
@@ -1721,8 +1702,15 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="ImgArray.dog_filter"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.dog_filter">[docs]</a>    <span class="nd">@_docs</span><span class="o">.</span><span class="n">write_docs</span>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@check_input_and_output</span>
-    <span class="k">def</span> <span class="nf">dog_filter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">low_sigma</span><span class="p">:</span> <span class="n">nDFloat</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="n">high_sigma</span><span class="p">:</span> <span class="n">nDFloat</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+    <span class="k">def</span> <span class="nf">dog_filter</span><span class="p">(</span>
+        <span class="bp">self</span><span class="p">,</span>
+        <span class="n">low_sigma</span><span class="p">:</span> <span class="n">nDFloat</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span>
+        <span class="n">high_sigma</span><span class="p">:</span> <span class="n">nDFloat</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="o">*</span><span class="p">,</span>
+        <span class="n">fourier</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
+        <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Run Difference of Gaussian filter. This function does not support `update`</span>
 <span class="sd">        argument because intensity can be negative.</span>
 <span class="sd">        </span>
@@ -1732,7 +1720,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
 <span class="sd">            lower standard deviation(s) of Gaussian.</span>
 <span class="sd">        high_sigma : scalar or array of scalars, default is x1.6 of low_sigma.</span>
 <span class="sd">            higher standard deviation(s) of Gaussian.</span>
-<span class="sd">        {dims}</span>
+<span class="sd">        {fourier}{dims}</span>
 <span class="sd">            </span>
 <span class="sd">        Returns</span>
 <span class="sd">        -------</span>
@@ -1742,9 +1730,9 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         
         <span class="n">low_sigma</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">check_nd</span><span class="p">(</span><span class="n">low_sigma</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">dims</span><span class="p">)))</span>
         <span class="n">high_sigma</span> <span class="o">=</span> <span class="n">low_sigma</span> <span class="o">*</span> <span class="mf">1.6</span> <span class="k">if</span> <span class="n">high_sigma</span> <span class="ow">is</span> <span class="kc">None</span> <span class="k">else</span> <span class="n">high_sigma</span>
-        
+        <span class="n">filter_func</span> <span class="o">=</span> <span class="n">_filters</span><span class="o">.</span><span class="n">dog_filter_fourier</span> <span class="k">if</span> <span class="n">fourier</span> <span class="k">else</span> <span class="n">_filters</span><span class="o">.</span><span class="n">dog_filter</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">as_float</span><span class="p">()</span><span class="o">.</span><span class="n">_apply_dask</span><span class="p">(</span>
-            <span class="n">_filters</span><span class="o">.</span><span class="n">dog_filter</span><span class="p">,</span> 
+            <span class="n">filter_func</span><span class="p">,</span> 
             <span class="n">c_axes</span><span class="o">=</span><span class="n">complement_axes</span><span class="p">(</span><span class="n">dims</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">),</span>
             <span class="n">args</span><span class="o">=</span><span class="p">(</span><span class="n">low_sigma</span><span class="p">,</span> <span class="n">high_sigma</span><span class="p">)</span>
         <span class="p">)</span></div>
@@ -1753,7 +1741,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">doh_filter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sigma</span><span class="p">:</span> <span class="n">nDFloat</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Determinant of Hessian filter. This function does not support `update`</span>
 <span class="sd">        argument because output has total different scale of intensity. </span>
 <span class="sd">        </span>
@@ -1782,7 +1770,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">log_filter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sigma</span><span class="p">:</span> <span class="n">nDFloat</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Laplacian of Gaussian filter.</span>
 
 <span class="sd">        Parameters</span>
@@ -1813,7 +1801,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Subtract Background using rolling-ball algorithm.</span>
 
 <span class="sd">        Parameters</span>
@@ -1870,7 +1858,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Rudin-Osher-Fatemi&#39;s total variation denoising.</span>
 
 <span class="sd">        Parameters</span>
@@ -1910,7 +1898,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">shift_steps</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Wavelet denoising. Because it is not shift invariant, ``cycle_spin`` is called inside the </span>
 <span class="sd">        function.</span>
 
@@ -1960,7 +1948,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">angle_order</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">newaxis</span><span class="p">:</span> <span class="n">AxisLike</span> <span class="o">=</span> <span class="s2">&quot;a&quot;</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Split a (2N, 2M)-image into four (N, M)-images for each other pixels.</span>
 <span class="sd">        </span>
 <span class="sd">        Generally, image acquisition with a polarization camera will output </span>
@@ -2052,7 +2040,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">out</span></div>
         
 <div class="viewcode-block" id="ImgArray.stokes"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.stokes">[docs]</a>    <span class="k">def</span> <span class="nf">stokes</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">along</span><span class="p">:</span> <span class="n">AxisLike</span> <span class="o">=</span> <span class="s2">&quot;a&quot;</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Generate stocks images from an image stack with polarized images. </span>
 <span class="sd">        </span>
 <span class="sd">        Currently, Degree of Linear Polarization (DoLP) and Angle of </span>
@@ -2138,7 +2126,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Image inpainting.</span>
 
 <span class="sd">        Parameters</span>
@@ -2180,7 +2168,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">use_labels</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">MarkerFrame</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Find local maxima. This algorithm corresponds to ImageJ&#39;s &#39;Find Maxima&#39; but is more flexible.</span>
 
 <span class="sd">        Parameters</span>
@@ -2257,7 +2245,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span> 
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Calculate Harris response image.</span>
 
 <span class="sd">        Parameters</span>
@@ -2289,7 +2277,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">inf</span><span class="p">:</span> <span class="n">nDInt</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="mi">2</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Voronoi segmentation of an image. </span>
 <span class="sd">        </span>
 <span class="sd">        Image region labeled with $i$ means that all the points in the region are</span>
@@ -2358,7 +2346,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">tolerance</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Flood filling with a list of seed points. By repeating skimage&#39;s ``flood`` function,</span>
 <span class="sd">        this method can perform segmentation of an image.</span>
 
@@ -2414,7 +2402,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">exclude_border</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">MarkerFrame</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Single molecule detection using difference of Gaussian, determinant of Hessian, Laplacian of </span>
 <span class="sd">        Gaussian or normalized cross correlation method.</span>
 
@@ -2490,7 +2478,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="o">**</span><span class="n">find_sm_kwargs</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">MarkerFrame</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Calculate positions of particles in subpixel precision using centroid.</span>
 
 <span class="sd">        Parameters</span>
@@ -2565,7 +2553,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">deg</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="mi">2</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PhaseArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Calculate gradient direction using horizontal and vertical edge operation. Gradient direction</span>
 <span class="sd">        is the direction with maximum gradient, i.e., intensity increase is largest. </span>
 
@@ -2622,7 +2610,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">deg</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="mi">2</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PhaseArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Calculate filament angles using Hessian&#39;s eigenvectors.</span>
 
 <span class="sd">        Parameters</span>
@@ -2666,7 +2654,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">deg</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span> 
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="mi">2</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PhaseArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Calculate filament angles using Gabor filter. For all the candidates of angles, Gabor response is</span>
 <span class="sd">        calculated, and the strongest response is returned as output array.</span>
 
@@ -2735,7 +2723,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">return_imag</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="mi">2</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Make a Gabor kernel and convolve it.</span>
 
 <span class="sd">        Parameters</span>
@@ -2797,7 +2785,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">double_precision</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Fast Fourier transformation. This function returns complex array, which is</span>
 <span class="sd">        inconpatible with some ImgArray functions.</span>
 <span class="sd">        </span>
@@ -2847,7 +2835,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">double_precision</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span> 
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Local discrete Fourier transformation (DFT). This function will be useful </span>
 <span class="sd">        for Fourier transformation of small region of an image with a certain</span>
 <span class="sd">        factor of up-sampling. In general FFT takes :math:`O(N\log{N})` time, much</span>
@@ -2930,7 +2918,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">double_precision</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Return local n-D power spectra of images. See ``local_dft``.</span>
 
 <span class="sd">        Parameters</span>
@@ -2974,7 +2962,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">double_precision</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span> 
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Fast Inverse Fourier transformation. Complementary function with `fft()`.</span>
 <span class="sd">        </span>
 <span class="sd">        Parameters</span>
@@ -3013,11 +3001,13 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="bp">self</span><span class="p">,</span>
         <span class="n">shape</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="n">Iterable</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">|</span> <span class="n">FftShape</span> <span class="o">=</span> <span class="s2">&quot;same&quot;</span><span class="p">,</span>
         <span class="n">norm</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span> 
-        <span class="n">zero_norm</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span>
+        <span class="n">zero_norm</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span> 
+        <span class="o">*</span><span class="p">,</span>
+        <span class="n">shift</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
         <span class="n">double_precision</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Return n-D power spectra of images, which is defined as:</span>
 <span class="sd">        </span>
 <span class="sd">        .. math::</span>
@@ -3034,6 +3024,8 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
 <span class="sd">        norm : bool, default is False</span>
 <span class="sd">            If True, maximum value of power spectra is adjusted to 1.</span>
 <span class="sd">        {double_precision}</span>
+<span class="sd">        shift : bool, default is True</span>
+<span class="sd">            If True, call ``np.fft.fftshift`` at the first.</span>
 <span class="sd">        {dims}</span>
 
 <span class="sd">        Returns</span>
@@ -3045,7 +3037,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
 <span class="sd">        --------</span>
 <span class="sd">        local_power_spectra</span>
 <span class="sd">        &quot;&quot;&quot;</span>        
-        <span class="n">freq</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fft</span><span class="p">(</span><span class="n">dims</span><span class="o">=</span><span class="n">dims</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="n">shape</span><span class="p">,</span> <span class="n">double_precision</span><span class="o">=</span><span class="n">double_precision</span><span class="p">)</span>
+        <span class="n">freq</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fft</span><span class="p">(</span><span class="n">dims</span><span class="o">=</span><span class="n">dims</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="n">shape</span><span class="p">,</span> <span class="n">shift</span><span class="o">=</span><span class="n">shift</span><span class="p">,</span> <span class="n">double_precision</span><span class="o">=</span><span class="n">double_precision</span><span class="p">)</span>
         <span class="n">pw</span> <span class="o">=</span> <span class="n">freq</span><span class="o">.</span><span class="n">real</span><span class="o">**</span><span class="mi">2</span> <span class="o">+</span> <span class="n">freq</span><span class="o">.</span><span class="n">imag</span><span class="o">**</span><span class="mi">2</span>
         <span class="k">if</span> <span class="n">norm</span><span class="p">:</span>
             <span class="n">pw</span> <span class="o">/=</span> <span class="n">pw</span><span class="o">.</span><span class="n">max</span><span class="p">()</span>
@@ -3065,7 +3057,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">order</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">3</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Discrete Radon transformation of 2D or 3D image.</span>
 <span class="sd">        </span>
 <span class="sd">        Radon transformation is a list of projection of a same image from different angles.</span>
@@ -3125,7 +3117,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">window</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;hamming&quot;</span><span class="p">,</span>
         <span class="n">order</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">3</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Inverse Radon transformation (weighted back projection) of a tile series.</span>
 <span class="sd">        </span>
 <span class="sd">        Input array must be a tilt series of 1D or 2D images. They are back-</span>
@@ -3183,8 +3175,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="k">if</span> <span class="n">out</span><span class="o">.</span><span class="n">ndim</span> <span class="o">==</span> <span class="mi">3</span><span class="p">:</span>
             <span class="n">out</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">moveaxis</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
         <span class="n">out</span> <span class="o">=</span> <span class="n">out</span><span class="p">[::</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
-        <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">new_axes</span><span class="p">)</span>
-        <span class="k">return</span> <span class="n">out</span></div>
+        <span class="k">return</span> <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">new_axes</span><span class="p">)</span></div>
 
 <div class="viewcode-block" id="ImgArray.threshold"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.threshold">[docs]</a>    <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">threshold</span><span class="p">(</span>
@@ -3194,7 +3185,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">along</span><span class="p">:</span> <span class="n">AxisLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="o">**</span><span class="n">kwargs</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Apply thresholding to the image and create a binary image.</span>
 <span class="sd">        </span>
 <span class="sd">        The threshold value can be given with a float or a string that indicates what</span>
@@ -3275,7 +3266,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@check_input_and_output</span><span class="p">(</span><span class="n">only_binary</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="k">def</span> <span class="nf">distance_map</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Calculate distance map from binary images.</span>
 <span class="sd">        For instance, ``[1, 1, 1, 0, 0, 0, 1, 1, 1]`` will be converted to </span>
 <span class="sd">        ``[3, 2, 1, 0, 0, 0, 1, 2, 3]``. Note that returned array will be float in n-D </span>
@@ -3304,7 +3295,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span> 
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Template matching using normalized cross correlation (NCC) method. This function is basically</span>
 <span class="sd">        identical to that in `skimage.feature`, but is optimized for batch processing and improved </span>
 <span class="sd">        readability.</span>
@@ -3341,7 +3332,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@check_input_and_output</span><span class="p">(</span><span class="n">only_binary</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="k">def</span> <span class="nf">remove_large_objects</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">radius</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mi">5</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Remove large objects using opening. Those objects that were not removed by opening</span>
 <span class="sd">        will be removed in output.</span>
 
@@ -3370,7 +3361,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@check_input_and_output</span><span class="p">(</span><span class="n">only_binary</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="k">def</span> <span class="nf">remove_fine_objects</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">length</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Remove fine objects using diameter_opening.</span>
 
 <span class="sd">        Parameters</span>
@@ -3399,7 +3390,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@check_input_and_output</span><span class="p">(</span><span class="n">only_binary</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="k">def</span> <span class="nf">convex_hull</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">update</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Compute convex hull image.</span>
 
 <span class="sd">        Parameters</span>
@@ -3421,7 +3412,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@check_input_and_output</span><span class="p">(</span><span class="n">only_binary</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="k">def</span> <span class="nf">skeletonize</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">radius</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">update</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Skeletonize images. Only works for binary images.</span>
 
 <span class="sd">        Parameters</span>
@@ -3457,7 +3448,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">mask</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Count the number or neighbors of binary images. This function can be used for cross section</span>
 <span class="sd">        or branch detection. Only works for binary images.</span>
 
@@ -3506,7 +3497,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Remove certain structure from skeletonized images.</span>
 
 <span class="sd">        Parameters</span>
@@ -3545,7 +3536,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">min_distance</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mi">2</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Label</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Label segmentation using watershed algorithm.</span>
 
 <span class="sd">        Parameters</span>
@@ -3616,7 +3607,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Label</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Random walker segmentation. Only wrapped skimage segmentation. </span>
 <span class="sd">        </span>
 <span class="sd">        ``self.labels`` will be segmented and updated inplace.</span>
@@ -3650,7 +3641,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="o">**</span><span class="n">kwargs</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Label</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Make labels with threshold(). Be sure that keyword argument ``dims`` can be</span>
 <span class="sd">        different (in most cases for &gt;4D images) between threshold() and label().</span>
 <span class="sd">        In this function, both function will have the same ``dims`` for simplicity.</span>
@@ -3677,7 +3668,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span> 
         <span class="n">extra_properties</span><span class="p">:</span> <span class="n">Iterable</span><span class="p">[</span><span class="n">Callable</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataDict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">PropArray</span><span class="p">]:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Multi-dimensional region property quantification.</span>
 <span class="sd">        </span>
 <span class="sd">        Run skimage&#39;s regionprops() function and return the results as PropArray, so</span>
@@ -3754,7 +3745,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">method</span><span class="p">:</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;default&quot;</span><span class="p">,</span> <span class="s2">&quot;ror&quot;</span><span class="p">,</span> <span class="s2">&quot;uniform&quot;</span><span class="p">,</span> <span class="s2">&quot;var&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="s2">&quot;default&quot;</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Local binary pattern feature extraction.</span>
 
 <span class="sd">        Parameters</span>
@@ -3784,7 +3775,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">glcm_props</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">distances</span><span class="p">,</span> <span class="n">angles</span><span class="p">,</span> <span class="n">radius</span><span class="p">:</span><span class="nb">int</span><span class="p">,</span> <span class="n">properties</span><span class="p">:</span><span class="nb">tuple</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> 
                    <span class="o">*</span><span class="p">,</span> <span class="n">bins</span><span class="p">:</span><span class="nb">int</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">rescale_max</span><span class="p">:</span><span class="nb">bool</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Compute properties of &quot;Gray Level Coocurrence Matrix&quot;. This will take long time</span>
 <span class="sd">        because of pure Python for-loop.</span>
 
@@ -3853,7 +3844,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">mask</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="o">**</span><span class="n">kwargs</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Projection along any axis.</span>
 
 <span class="sd">        Parameters</span>
@@ -3904,7 +3895,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
 
 <div class="viewcode-block" id="ImgArray.clip"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.clip">[docs]</a>    <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">clip</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">in_range</span><span class="p">:</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span> <span class="o">|</span> <span class="nb">str</span><span class="p">,</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="s2">&quot;0%&quot;</span><span class="p">,</span> <span class="s2">&quot;100%&quot;</span><span class="p">))</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Saturate low/high intensity using np.clip().</span>
 
 <span class="sd">        Parameters</span>
@@ -3928,7 +3919,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">in_range</span><span class="p">:</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span> <span class="o">|</span> <span class="nb">str</span><span class="p">,</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="s2">&quot;0%&quot;</span><span class="p">,</span> <span class="s2">&quot;100%&quot;</span><span class="p">),</span> 
         <span class="n">dtype</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">uint16</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Rescale the intensity of the image using skimage.exposure.rescale_intensity().</span>
 
 <span class="sd">        Parameters</span>
@@ -3958,7 +3949,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">show_drift</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span> 
         <span class="n">upsample_factor</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">MarkerFrame</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Calculate yx-directional drift using the method equivalent to</span>
 <span class="sd">        ``skimage.registration.phase_cross_correlation``.</span>
 
@@ -4024,7 +4015,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="mi">2</span><span class="p">,</span>
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Drift correction using iterative Affine translation. If translation vectors ``shift``</span>
 <span class="sd">        is not given, then it will be determined using ``track_drift`` method of ImgArray.</span>
 
@@ -4101,9 +4092,8 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
 
 <div class="viewcode-block" id="ImgArray.estimate_sigma"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.estimate_sigma">[docs]</a>    <span class="nd">@_docs</span><span class="o">.</span><span class="n">write_docs</span>
     <span class="nd">@dims_to_spatial_axes</span>
-    <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">estimate_sigma</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">squeeze</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PropArray</span> <span class="o">|</span> <span class="nb">float</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Wavelet-based estimation of Gaussian noise.</span>
 
 <span class="sd">        Parameters</span>
@@ -4133,7 +4123,37 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
             <span class="p">)</span>
             <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">new_axes</span><span class="o">=</span><span class="n">c_axes</span><span class="p">)</span>
         <span class="k">return</span> <span class="n">out</span>       </div>
-        
+
+<div class="viewcode-block" id="ImgArray.center_of_mass"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.center_of_mass">[docs]</a>    <span class="nd">@_docs</span><span class="o">.</span><span class="n">write_docs</span>
+    <span class="nd">@dims_to_spatial_axes</span>
+    <span class="k">def</span> <span class="nf">center_of_mass</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PropArray</span><span class="p">:</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">        Calculate the center of mass of the image.</span>
+
+<span class="sd">        Parameters</span>
+<span class="sd">        ----------</span>
+<span class="sd">        {dims}</span>
+
+<span class="sd">        Returns</span>
+<span class="sd">        -------</span>
+<span class="sd">        PropArray</span>
+<span class="sd">            Center of mass. Axes will be the input axes minus ``dims``, plus a new axis</span>
+<span class="sd">            ``dim`` at the first position, which represents the dimensions of the</span>
+<span class="sd">            results.</span>
+<span class="sd">        &quot;&quot;&quot;</span>        
+        <span class="n">c_axes</span> <span class="o">=</span> <span class="n">complement_axes</span><span class="p">(</span><span class="n">dims</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">)</span>
+        <span class="n">out_shape</span> <span class="o">=</span> <span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">dims</span><span class="p">),</span> <span class="p">)</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">sizesof</span><span class="p">(</span><span class="n">c_axes</span><span class="p">)</span>
+        <span class="n">axis</span> <span class="o">=</span> <span class="n">Axis</span><span class="p">(</span><span class="s2">&quot;dim&quot;</span><span class="p">)</span>
+        <span class="n">axis</span><span class="o">.</span><span class="n">labels</span> <span class="o">=</span> <span class="n">dims</span>
+        <span class="n">out_axes</span> <span class="o">=</span> <span class="p">[</span><span class="n">axis</span><span class="p">]</span> <span class="o">+</span> <span class="n">c_axes</span>
+        <span class="n">out</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">empty</span><span class="p">(</span><span class="n">out_shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span>
+        <span class="k">for</span> <span class="n">sl</span><span class="p">,</span> <span class="n">img</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">iter</span><span class="p">(</span><span class="n">c_axes</span><span class="p">,</span> <span class="n">israw</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">exclude</span><span class="o">=</span><span class="n">dims</span><span class="p">):</span>
+            <span class="n">out</span><span class="p">[(</span><span class="nb">slice</span><span class="p">(</span><span class="kc">None</span><span class="p">),)</span> <span class="o">+</span> <span class="n">sl</span><span class="p">]</span> <span class="o">=</span> <span class="n">ndi</span><span class="o">.</span><span class="n">center_of_mass</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
+        <span class="n">out</span> <span class="o">=</span> <span class="n">PropArray</span><span class="p">(</span>
+            <span class="n">out</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">out_axes</span><span class="p">,</span> <span class="n">propname</span><span class="o">=</span><span class="s2">&quot;center_of_mass&quot;</span>
+        <span class="p">)</span>
+        <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">new_axes</span><span class="o">=</span><span class="n">out_axes</span><span class="p">)</span>
+        <span class="k">return</span> <span class="n">out</span></div>
     
 <div class="viewcode-block" id="ImgArray.pad"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.pad">[docs]</a>    <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@check_input_and_output</span>
@@ -4145,7 +4165,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> 
         <span class="o">**</span><span class="n">kwargs</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Pad image only for spatial dimensions.</span>
 
 <span class="sd">        Parameters</span>
@@ -4180,7 +4200,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="ImgArray.pad_defocus"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.pad_defocus">[docs]</a>    <span class="nd">@same_dtype</span><span class="p">(</span><span class="n">asfloat</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">pad_defocus</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">kernel</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">depth</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">3</span><span class="p">,</span> <span class="n">width</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">6</span><span class="p">,</span> <span class="n">bg</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Make a z-directional padded image by defocusing the original image. This padding is</span>
 <span class="sd">        useful when applying FFT to a 3D image.</span>
 <span class="sd">        </span>
@@ -4267,13 +4287,13 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">wiener</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">,</span>
-        <span class="n">psf</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span>
+        <span class="n">psf</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">|</span> <span class="n">Callable</span><span class="p">[[</span><span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]],</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">],</span>
         <span class="n">lmd</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.1</span><span class="p">,</span>
         <span class="o">*</span><span class="p">,</span> 
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> 
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Classical wiener deconvolution. This algorithm has the serious ringing problem</span>
 <span class="sd">        if parameters are set to wrong values.</span>
 <span class="sd">        </span>
@@ -4285,8 +4305,9 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
 
 <span class="sd">        Parameters</span>
 <span class="sd">        ----------</span>
-<span class="sd">        psf : np.ndarray</span>
-<span class="sd">            Point spread function.</span>
+<span class="sd">        psf : ndarray or callable</span>
+<span class="sd">            Point spread function. If a function is given, `psf(shape)` will be</span>
+<span class="sd">            called to generate the PSF.</span>
 <span class="sd">        lmd : float, default is 0.1</span>
 <span class="sd">            Constant value used in the deconvolution. See Formulation below.</span>
 <span class="sd">        {dims}{update}</span>
@@ -4305,41 +4326,43 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="k">if</span> <span class="n">lmd</span> <span class="o">&lt;=</span> <span class="mi">0</span><span class="p">:</span>
             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;lmd must be positive, but got: </span><span class="si">{</span><span class="n">lmd</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
         
-        <span class="n">psf_ft</span><span class="p">,</span> <span class="n">psf_ft_conj</span> <span class="o">=</span> <span class="n">_deconv</span><span class="o">.</span><span class="n">check_psf</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">psf</span><span class="p">,</span> <span class="n">dims</span><span class="p">)</span>
+        <span class="n">psf_ft</span><span class="p">,</span> <span class="n">psf_ft_conj</span> <span class="o">=</span> <span class="n">_deconv</span><span class="o">.</span><span class="n">check_psf</span><span class="p">(</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">sizesof</span><span class="p">(</span><span class="n">dims</span><span class="p">),</span> <span class="nb">tuple</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">scale</span><span class="p">[</span><span class="n">axis</span><span class="p">]</span> <span class="k">for</span> <span class="n">axis</span> <span class="ow">in</span> <span class="n">dims</span><span class="p">),</span> <span class="n">psf</span><span class="p">,</span>
+        <span class="p">)</span>
         
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_apply_dask</span><span class="p">(</span>
             <span class="n">_deconv</span><span class="o">.</span><span class="n">wiener</span><span class="p">,</span> 
             <span class="n">c_axes</span><span class="o">=</span><span class="n">complement_axes</span><span class="p">(</span><span class="n">dims</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">),</span>
             <span class="n">args</span><span class="o">=</span><span class="p">(</span><span class="n">psf_ft</span><span class="p">,</span> <span class="n">psf_ft_conj</span><span class="p">,</span> <span class="n">lmd</span><span class="p">)</span>
-        <span class="p">)</span></div>
-        
-    
+        <span class="p">)</span>    </div>
+
 <div class="viewcode-block" id="ImgArray.lucy"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.lucy">[docs]</a>    <span class="nd">@_docs</span><span class="o">.</span><span class="n">write_docs</span>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@same_dtype</span><span class="p">(</span><span class="n">asfloat</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">lucy</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">,</span>
-        <span class="n">psf</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span>
+        <span class="n">psf</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">|</span> <span class="n">Callable</span><span class="p">[[</span><span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]],</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">],</span>
         <span class="n">niter</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">50</span><span class="p">,</span>
         <span class="n">eps</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">1e-5</span><span class="p">,</span>
         <span class="o">*</span><span class="p">,</span> 
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> 
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Deconvolution of N-dimensional image, using Richardson-Lucy&#39;s algorithm.</span>
 <span class="sd">        </span>
 <span class="sd">        Parameters</span>
 <span class="sd">        ----------</span>
-<span class="sd">        psf : np.ndarray</span>
-<span class="sd">            Point spread function.</span>
+<span class="sd">        psf : ndarray or callable</span>
+<span class="sd">            Point spread function. If a function is given, `psf(shape)` will be</span>
+<span class="sd">            called to generate the PSF.</span>
 <span class="sd">        niter : int, default is 50.</span>
 <span class="sd">            Number of iterations.</span>
 <span class="sd">        eps : float, default is 1e-5</span>
-<span class="sd">            During deconvolution, division by small values in the convolve image of estimation and </span>
-<span class="sd">            PSF may cause divergence. Therefore, division by values under `eps` is substituted</span>
-<span class="sd">            to zero.</span>
+<span class="sd">            During deconvolution, division by small values in the convolve image </span>
+<span class="sd">            of estimation and PSF may cause divergence. Therefore, division by </span>
+<span class="sd">            values under `eps` is substituted to zero.</span>
 <span class="sd">        {dims}{update}</span>
 <span class="sd">        </span>
 <span class="sd">        Returns</span>
@@ -4353,7 +4376,9 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
 <span class="sd">        wiener</span>
 <span class="sd">        &quot;&quot;&quot;</span>
         
-        <span class="n">psf_ft</span><span class="p">,</span> <span class="n">psf_ft_conj</span> <span class="o">=</span> <span class="n">_deconv</span><span class="o">.</span><span class="n">check_psf</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">psf</span><span class="p">,</span> <span class="n">dims</span><span class="p">)</span>
+        <span class="n">psf_ft</span><span class="p">,</span> <span class="n">psf_ft_conj</span> <span class="o">=</span> <span class="n">_deconv</span><span class="o">.</span><span class="n">check_psf</span><span class="p">(</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">sizesof</span><span class="p">(</span><span class="n">dims</span><span class="p">),</span> <span class="nb">tuple</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">scale</span><span class="p">[</span><span class="n">axis</span><span class="p">]</span> <span class="k">for</span> <span class="n">axis</span> <span class="ow">in</span> <span class="n">dims</span><span class="p">),</span> <span class="n">psf</span><span class="p">,</span>
+        <span class="p">)</span>
 
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_apply_dask</span><span class="p">(</span>
             <span class="n">_deconv</span><span class="o">.</span><span class="n">richardson_lucy</span><span class="p">,</span> 
@@ -4367,7 +4392,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">lucy_tv</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">,</span>
-        <span class="n">psf</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span>
+        <span class="n">psf</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">|</span> <span class="n">Callable</span><span class="p">[[</span><span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]],</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">],</span>
         <span class="n">max_iter</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">50</span><span class="p">,</span>
         <span class="n">lmd</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">1e-3</span><span class="p">,</span>
         <span class="n">tol</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">1e-3</span><span class="p">,</span>
@@ -4376,7 +4401,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Deconvolution of N-dimensional image, using Richardson-Lucy&#39;s algorithm with</span>
 <span class="sd">        total variance regularization (so called RL-TV algorithm). The TV regularization</span>
 <span class="sd">        factor at pixel position :math:`x`, :math:`F_{reg}(x)`, is calculated as:</span>
@@ -4391,8 +4416,9 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
 <span class="sd">        </span>
 <span class="sd">        Parameters</span>
 <span class="sd">        ----------</span>
-<span class="sd">        psf : np.ndarray</span>
-<span class="sd">            Point spread function.</span>
+<span class="sd">        psf : ndarray or callable</span>
+<span class="sd">            Point spread function. If a function is given, `psf(shape)` will be</span>
+<span class="sd">            called to generate the PSF.</span>
 <span class="sd">        max_iter : int, default is 50.</span>
 <span class="sd">            Maximum number of iterations.</span>
 <span class="sd">        lmd : float, default is 1e-3</span>
@@ -4433,14 +4459,35 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
                 <span class="s2">&quot;In Richadson-Lucy with total-variance-regularization, &quot;</span>
                 <span class="s2">&quot;parameter `lmd` must be positive.&quot;</span>
             <span class="p">)</span>
-        <span class="n">psf_ft</span><span class="p">,</span> <span class="n">psf_ft_conj</span> <span class="o">=</span> <span class="n">_deconv</span><span class="o">.</span><span class="n">check_psf</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">psf</span><span class="p">,</span> <span class="n">dims</span><span class="p">)</span>
+        <span class="n">psf_ft</span><span class="p">,</span> <span class="n">psf_ft_conj</span> <span class="o">=</span> <span class="n">_deconv</span><span class="o">.</span><span class="n">check_psf</span><span class="p">(</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">sizesof</span><span class="p">(</span><span class="n">dims</span><span class="p">),</span> <span class="nb">tuple</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">scale</span><span class="p">[</span><span class="n">axis</span><span class="p">]</span> <span class="k">for</span> <span class="n">axis</span> <span class="ow">in</span> <span class="n">dims</span><span class="p">),</span> <span class="n">psf</span>
+        <span class="p">)</span>
 
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_apply_dask</span><span class="p">(</span>
             <span class="n">_deconv</span><span class="o">.</span><span class="n">richardson_lucy_tv</span><span class="p">,</span> 
             <span class="n">c_axes</span><span class="o">=</span><span class="n">complement_axes</span><span class="p">(</span><span class="n">dims</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">),</span>
             <span class="n">args</span><span class="o">=</span><span class="p">(</span><span class="n">psf_ft</span><span class="p">,</span> <span class="n">psf_ft_conj</span><span class="p">,</span> <span class="n">max_iter</span><span class="p">,</span> <span class="n">lmd</span><span class="p">,</span> <span class="n">tol</span><span class="p">,</span> <span class="n">eps</span><span class="p">)</span>
-        <span class="p">)</span></div></div>
+        <span class="p">)</span></div>
 
+<div class="viewcode-block" id="ImgArray.tiled_lucy"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.tiled_lucy">[docs]</a>    <span class="nd">@_docs</span><span class="o">.</span><span class="n">write_docs</span>
+    <span class="nd">@dims_to_spatial_axes</span>
+    <span class="nd">@same_dtype</span><span class="p">(</span><span class="n">asfloat</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+    <span class="nd">@check_input_and_output</span>
+    <span class="k">def</span> <span class="nf">tiled_lucy</span><span class="p">(</span>
+        <span class="bp">self</span><span class="p">,</span>
+        <span class="n">psf</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">|</span> <span class="n">Callable</span><span class="p">[[</span><span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]],</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">],</span>
+        <span class="n">niter</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">50</span><span class="p">,</span>
+        <span class="n">eps</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">1e-5</span><span class="p">,</span>
+        <span class="n">chunks</span> <span class="o">=</span> <span class="s2">&quot;auto&quot;</span><span class="p">,</span>
+        <span class="n">overlap</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">32</span><span class="p">,</span>
+        <span class="o">**</span><span class="n">kwargs</span><span class="p">,</span>
+    <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
+        <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span>
+            <span class="s2">&quot;`tiled_lucy` is deprecated Please use &quot;</span>
+            <span class="sa">f</span><span class="s2">&quot;`img.tiled(</span><span class="si">{</span><span class="n">chunks</span><span class="si">=}</span><span class="s2">, </span><span class="si">{</span><span class="n">overlap</span><span class="si">=}</span><span class="s2">).lucy(...)` instead.&quot;</span><span class="p">,</span>
+            <span class="ne">DeprecationWarning</span><span class="p">,</span>
+        <span class="p">)</span>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">tiled</span><span class="p">(</span><span class="n">chunks</span><span class="p">,</span> <span class="n">overlap</span><span class="p">)</span><span class="o">.</span><span class="n">lucy</span><span class="p">(</span><span class="n">psf</span><span class="p">,</span> <span class="n">niter</span><span class="p">,</span> <span class="n">eps</span><span class="p">)</span></div></div>
 
 <span class="k">def</span> <span class="nf">_check_coordinates</span><span class="p">(</span><span class="n">coords</span><span class="p">,</span> <span class="n">img</span><span class="p">:</span> <span class="n">ImgArray</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span>
     <span class="kn">from</span> <span class="nn">impy.frame</span> <span class="kn">import</span> <span class="n">MarkerFrame</span>
@@ -4495,7 +4542,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="n">centroid</span>
 
 <span class="k">def</span> <span class="nf">_check_clip_range</span><span class="p">(</span><span class="n">in_range</span><span class="p">,</span> <span class="n">img</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">]:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Called in clip_outliers() and rescale_intensity().</span>
 <span class="sd">    &quot;&quot;&quot;</span>    
     <span class="n">lower</span><span class="p">,</span> <span class="n">upper</span> <span class="o">=</span> <span class="n">in_range</span>
@@ -4534,7 +4581,7 @@ <h1>Source code for impy.arrays.imgarray</h1><div class="highlight"><pre>
 
 
 <div class="viewcode-block" id="wave_num"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.wave_num">[docs]</a><span class="k">def</span> <span class="nf">wave_num</span><span class="p">(</span><span class="n">sl</span><span class="p">:</span> <span class="nb">slice</span><span class="p">,</span> <span class="n">s</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">uf</span><span class="p">:</span> <span class="nb">int</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">xp</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    A function that makes wave number vertical vector. Returned vector will</span>
 <span class="sd">    be [k/s, (k + 1/uf)/s, (k + 2/uf)/s, ...] (where k = sl.start)</span>
 
diff --git a/docs/_modules/impy/arrays/labeledarray.html b/docs/_modules/impy/arrays/labeledarray.html
index e28e5d62..10d22a3d 100644
--- a/docs/_modules/impy/arrays/labeledarray.html
+++ b/docs/_modules/impy/arrays/labeledarray.html
@@ -3,7 +3,7 @@
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.arrays.labeledarray &mdash; impy 2.2.0 documentation</title>
+  <title>impy.arrays.labeledarray &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../../../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -11,9 +11,8 @@
   <![endif]-->
   
         <script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
-        <script src="../../../_static/jquery.js"></script>
-        <script src="../../../_static/underscore.js"></script>
         <script src="../../../_static/doctools.js"></script>
+        <script src="../../../_static/sphinx_highlight.js"></script>
     <script src="../../../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../../../genindex.html" />
     <link rel="search" title="Search" href="../../../search.html" /> 
@@ -24,14 +23,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../../../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../../../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../../../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -58,9 +61,9 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../../../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../../index.html">Module code</a> &raquo;</li>
-      <li>impy.arrays.labeledarray</li>
+      <li><a href="../../../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../../index.html">Module code</a></li>
+      <li class="breadcrumb-item active">impy.arrays.labeledarray</li>
       <li class="wy-breadcrumbs-aside">
       </li>
   </ul>
@@ -102,23 +105,23 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
 
 
 <div class="viewcode-block" id="SupportAxesSlicing"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.labeledarray.SupportAxesSlicing">[docs]</a><span class="k">class</span> <span class="nc">SupportAxesSlicing</span><span class="p">(</span><span class="n">Protocol</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;A protocol that covariate objects must follow.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;A protocol that covariate objects must follow.&quot;&quot;&quot;</span>
 
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">axes</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Axes</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Axes object bound to the object.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Axes object bound to the object.&quot;&quot;&quot;</span>
     
     <span class="k">def</span> <span class="nf">_dimension_matches</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">array</span><span class="p">:</span> <span class="n">MetaArray</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Check if self matches array&#39;s shape and axes.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Check if self matches array&#39;s shape and axes.&quot;&quot;&quot;</span>
     
 <div class="viewcode-block" id="SupportAxesSlicing.copy"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.labeledarray.SupportAxesSlicing.copy">[docs]</a>    <span class="k">def</span> <span class="nf">copy</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Shallow copy of the object.&quot;&quot;&quot;</span></div>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Shallow copy of the object.&quot;&quot;&quot;</span></div>
     
     <span class="k">def</span> <span class="fm">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">key</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">SupportAxesSlicing</span> <span class="o">|</span> <span class="kc">None</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Slice object.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Slice object.&quot;&quot;&quot;</span>
     
     <span class="k">def</span> <span class="nf">_slice_by</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">key</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">SupportAxesSlicing</span> <span class="o">|</span> <span class="kc">None</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Slice object.&quot;&quot;&quot;</span></div>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Slice object.&quot;&quot;&quot;</span></div>
 
 <span class="k">def</span> <span class="nf">_fmt_slice</span><span class="p">(</span><span class="n">k</span><span class="p">,</span> <span class="n">length</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span>
     <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">k</span><span class="p">,</span> <span class="nb">slice</span><span class="p">):</span>
@@ -127,7 +130,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">k</span>
 
 <div class="viewcode-block" id="ArrayCovariates"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.labeledarray.ArrayCovariates">[docs]</a><span class="k">class</span> <span class="nc">ArrayCovariates</span><span class="p">(</span><span class="n">MutableMapping</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">SupportAxesSlicing</span><span class="p">]):</span>
-    <span class="sd">&quot;&quot;&quot;A dictionary of covariate objects for a MetaArray.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;A dictionary of covariate objects for a MetaArray.&quot;&quot;&quot;</span>
 
     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">SupportAxesSlicing</span><span class="p">],</span> <span class="n">parent</span><span class="p">:</span> <span class="n">MetaArray</span><span class="p">):</span>
         <span class="kn">import</span> <span class="nn">weakref</span>
@@ -136,7 +139,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">parent</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;Return the parent MetaArray object&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Return the parent MetaArray object&quot;&quot;&quot;</span>
         <span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_parent_ref</span><span class="p">()</span>
         <span class="k">if</span> <span class="n">out</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;Parent LabeledArray is deleted.&quot;</span><span class="p">)</span>
@@ -247,17 +250,17 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
 
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">range</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">]:</span>
-        <span class="sd">&quot;&quot;&quot;Return min/max range of the array.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Return min/max range of the array.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">min</span><span class="p">(),</span> <span class="bp">self</span><span class="o">.</span><span class="n">max</span><span class="p">()</span>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">covariates</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ArrayCovariates</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Get all the covariates.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Get all the covariates.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_covariates</span>
 
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">labels</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Label</span> <span class="o">|</span> <span class="kc">None</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;The label of the image.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;The label of the image.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">covariates</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;labels&quot;</span><span class="p">)</span>
     
     <span class="nd">@labels</span><span class="o">.</span><span class="n">setter</span>
@@ -278,7 +281,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
                 <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span>
                     <span class="sa">f</span><span class="s2">&quot;Input label must be unsigned int but has wrong dtype </span><span class="si">{</span><span class="n">arr</span><span class="o">.</span><span class="n">dtype</span><span class="si">}</span><span class="s2">.&quot;</span>
                 <span class="p">)</span>
-            <span class="n">axes</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">)[</span><span class="o">-</span><span class="n">arr</span><span class="o">.</span><span class="n">ndim</span><span class="p">:]</span>
+            <span class="n">axes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">[</span><span class="o">-</span><span class="n">arr</span><span class="o">.</span><span class="n">ndim</span><span class="p">:]</span>
             <span class="n">value</span> <span class="o">=</span> <span class="n">Label</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">)</span><span class="o">.</span><span class="n">optimize</span><span class="p">()</span>
         
         <span class="k">if</span> <span class="ow">not</span> <span class="n">value</span><span class="o">.</span><span class="n">_dimension_matches</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
@@ -294,7 +297,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">rois</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">RoiList</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;ROIs of the image.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;ROIs of the image.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">covariates</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;rois&quot;</span><span class="p">)</span>
     
     <span class="nd">@rois</span><span class="o">.</span><span class="n">setter</span>
@@ -314,12 +317,12 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
     <span class="k">def</span> <span class="nf">rois</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">covariates</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s2">&quot;rois&quot;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
     
-<div class="viewcode-block" id="LabeledArray.set_scale"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.set_scale">[docs]</a>    <span class="k">def</span> <span class="nf">set_scale</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-        <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">set_scale</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
+<div class="viewcode-block" id="LabeledArray.set_scale"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.set_scale">[docs]</a>    <span class="k">def</span> <span class="nf">set_scale</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">unit</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
+        <span class="n">out</span> <span class="o">=</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">set_scale</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">unit</span><span class="o">=</span><span class="n">unit</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
         <span class="k">for</span> <span class="n">cov</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">covariates</span><span class="o">.</span><span class="n">values</span><span class="p">():</span>
             <span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">cov</span><span class="p">,</span> <span class="s2">&quot;set_scale&quot;</span><span class="p">):</span>
                 <span class="n">cov</span><span class="o">.</span><span class="n">set_scale</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
-        <span class="k">return</span> <span class="kc">None</span></div>
+        <span class="k">return</span> <span class="n">out</span></div>
         
         
     <span class="k">def</span> <span class="nf">_repr_dict_</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
@@ -346,7 +349,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
         <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">overwrite</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Save image at the same directory as the original image by default. </span>
 <span class="sd">        </span>
 <span class="sd">        For tif file format, if the image contains wrong axes for ImageJ (= except for tzcyx), </span>
@@ -409,6 +412,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
     <span class="k">def</span> <span class="nf">_set_info</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="n">Self</span><span class="p">,</span> <span class="n">new_axes</span><span class="p">:</span> <span class="n">Any</span> <span class="o">=</span> <span class="n">MetaArray</span><span class="o">.</span><span class="n">_INHERIT</span><span class="p">):</span>
         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">new_axes</span><span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">_inherit_covariates</span><span class="p">(</span><span class="n">other</span><span class="p">)</span>
+        <span class="k">return</span> <span class="bp">self</span>
     
     <span class="k">def</span> <span class="nf">_inherit_covariates</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">other</span><span class="p">:</span> <span class="n">Self</span><span class="p">):</span>
         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">other</span><span class="p">,</span> <span class="n">LabeledArray</span><span class="p">):</span>
@@ -513,7 +517,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
     <span class="c1"># # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #</span>
 
 <div class="viewcode-block" id="LabeledArray.hist"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.hist">[docs]</a>    <span class="k">def</span> <span class="nf">hist</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">contrast</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;Show intensity profile.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Show intensity profile.&quot;&quot;&quot;</span>
         <span class="kn">from</span> <span class="nn">._utils</span> <span class="kn">import</span> <span class="n">_plot</span> <span class="k">as</span> <span class="n">_plt</span>
         <span class="n">_plt</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">contrast</span><span class="p">)</span>
 
@@ -533,15 +537,16 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="k">def</span> <span class="nf">map_coordinates</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">,</span>
-        <span class="n">coordinates</span><span class="p">,</span>
+        <span class="n">coordinates</span><span class="p">:</span> <span class="n">ArrayLike</span><span class="p">,</span>
         <span class="o">*</span><span class="p">,</span> 
         <span class="n">mode</span><span class="p">:</span> <span class="n">PaddingMode</span> <span class="o">=</span> <span class="s2">&quot;constant&quot;</span><span class="p">,</span>
         <span class="n">cval</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span>
         <span class="n">order</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">3</span><span class="p">,</span>
         <span class="n">prefilter</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">has_nan</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Coordinate mapping in the image. See ``scipy.ndimage.map_coordinates``.</span>
 
 <span class="sd">        Parameters</span>
@@ -552,6 +557,8 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
 <span class="sd">        prefilter : bool, optional</span>
 <span class="sd">            Spline prefilter applied to the array. By default set to True if ``order`` is larger</span>
 <span class="sd">            than 1.</span>
+<span class="sd">        has_nan : bool, default is False</span>
+<span class="sd">            If true, nan values will be masked out.</span>
 <span class="sd">        {dims}</span>
 
 <span class="sd">        Returns</span>
@@ -563,14 +570,16 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
         <span class="n">c_axes</span> <span class="o">=</span> <span class="n">complement_axes</span><span class="p">(</span><span class="n">dims</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">)</span>
         
         <span class="k">if</span> <span class="n">coords</span><span class="o">.</span><span class="n">ndim</span> <span class="o">!=</span> <span class="mi">2</span><span class="p">:</span>
-            <span class="n">drop_axis</span> <span class="o">=</span> <span class="p">[]</span>
+            <span class="n">drop_axis</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
         <span class="k">else</span><span class="p">:</span>
             <span class="n">drop_axis</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">axisof</span><span class="p">(</span><span class="n">a</span><span class="p">)</span> <span class="k">for</span> <span class="n">a</span> <span class="ow">in</span> <span class="n">dims</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span>
         
         <span class="k">if</span> <span class="n">prefilter</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
             <span class="n">prefilter</span> <span class="o">=</span> <span class="n">order</span> <span class="o">&gt;</span> <span class="mi">1</span>
+        
+        <span class="n">fn</span> <span class="o">=</span> <span class="n">_map_coordinates_with_nan</span> <span class="k">if</span> <span class="n">has_nan</span> <span class="k">else</span> <span class="n">_map_coordinates</span>
         <span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_apply_dask</span><span class="p">(</span>
-            <span class="n">_map_coordinates</span><span class="p">,</span>
+            <span class="n">fn</span><span class="p">,</span>
             <span class="n">c_axes</span><span class="p">,</span>
             <span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
             <span class="n">drop_axis</span><span class="o">=</span><span class="n">drop_axis</span><span class="p">,</span>
@@ -595,7 +604,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
 
 <div class="viewcode-block" id="LabeledArray.pointprops"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.pointprops">[docs]</a>    <span class="nd">@_docs</span><span class="o">.</span><span class="n">write_docs</span>
     <span class="k">def</span> <span class="nf">pointprops</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">coords</span><span class="p">:</span> <span class="n">Coords</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">order</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">3</span><span class="p">,</span> <span class="n">squeeze</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PropArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Measure interpolated intensity at points with float coordinates.</span>
 <span class="sd">        </span>
 <span class="sd">        This method is essentially identical to :func:`map_coordinates` but is</span>
@@ -644,7 +653,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
         <span class="n">order</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">3</span><span class="p">,</span>
         <span class="n">prefilter</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PropArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Measure line profile (kymograph) iteratively for every slice of image. This </span>
 <span class="sd">        function is almost same as `skimage.measure.profile_line`, but can reslice</span>
 <span class="sd">        3D-images. The argument `linewidth` is not implemented here because it is</span>
@@ -711,7 +720,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span> 
         <span class="n">order</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataDict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">PropArray</span><span class="p">]:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Measure line property using func(line_scan) for each functions in properties.</span>
 
 <span class="sd">        Parameters</span>
@@ -795,7 +804,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
     <span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Run spline filter.</span>
 <span class="sd">        </span>
 <span class="sd">        Parameters</span>
@@ -825,7 +834,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
     <span class="nd">@check_input_and_output</span>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="k">def</span> <span class="nf">crop_center</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">scale</span><span class="p">:</span> <span class="n">nDFloat</span> <span class="o">=</span> <span class="mf">0.5</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Crop out the center of an image. </span>
 <span class="sd">        </span>
 <span class="sd">        Parameters</span>
@@ -877,7 +886,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
     
 <div class="viewcode-block" id="LabeledArray.crop_kernel"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.crop_kernel">[docs]</a>    <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">crop_kernel</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">radius</span><span class="p">:</span> <span class="n">nDInt</span> <span class="o">=</span> <span class="mi">2</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Make a kernel from an image by cropping out the center region. </span>
 <span class="sd">        This function is useful especially in `ImgArray.defocus()`.</span>
 
@@ -909,7 +918,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
     <span class="nd">@check_input_and_output</span>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="k">def</span> <span class="nf">remove_edges</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">pixel</span><span class="p">:</span> <span class="n">nDInt</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Remove pixels from the edges.</span>
 
 <span class="sd">        Parameters</span>
@@ -940,7 +949,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
     <span class="nd">@check_input_and_output</span>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="k">def</span> <span class="nf">rotated_crop</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">origin</span><span class="p">,</span> <span class="n">dst1</span><span class="p">,</span> <span class="n">dst2</span><span class="p">,</span> <span class="n">dims</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Crop the image at four courners of an rotated rectangle. Currently only supports rotation within </span>
 <span class="sd">        yx-plane. An rotated rectangle is specified with positions of a origin and two destinations `dst1`</span>
 <span class="sd">        and `dst2`, i.e., vectors (dst1-origin) and (dst2-origin) represent a rotated rectangle. Let </span>
@@ -995,7 +1004,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="k">def</span> <span class="nf">specify</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">center</span><span class="p">:</span> <span class="n">Coords</span><span class="p">,</span> <span class="n">radius</span><span class="p">:</span> <span class="n">Coords</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> 
                 <span class="n">labeltype</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;square&quot;</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Label</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Make rectangle or ellipse labels from points.</span>
 <span class="sd">        </span>
 <span class="sd">        Parameters</span>
@@ -1075,7 +1084,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">connectivity</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Label</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Label image using skimage&#39;s label().</span>
 <span class="sd">        </span>
 <span class="sd">        Label image using `ref_image` as reference image, or image itself. If </span>
@@ -1210,7 +1219,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
     
 <div class="viewcode-block" id="LabeledArray.append_label"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.append_label">[docs]</a>    <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">append_label</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">label_image</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">new</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Label</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Append new labels from an array. This function works for boolean or signed int arrays.</span>
 
 <span class="sd">        Parameters</span>
@@ -1288,7 +1297,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
     
 <div class="viewcode-block" id="LabeledArray.proj_labels"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.proj_labels">[docs]</a>    <span class="nd">@check_input_and_output</span><span class="p">(</span><span class="n">need_labels</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="k">def</span> <span class="nf">proj_labels</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">forbid_overlap</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Label</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Label projection. This function is useful when zyx-labels are drawn but you want to reduce the </span>
 <span class="sd">        dimension.</span>
 
@@ -1308,7 +1317,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">labels</span></div>
     
 <div class="viewcode-block" id="LabeledArray.split"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.split">[docs]</a>    <span class="k">def</span> <span class="nf">split</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataList</span><span class="p">[</span><span class="n">Self</span><span class="p">]:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Split n-dimensional image into (n-1)-dimensional images. This function is different from</span>
 <span class="sd">        `np.split`, which split an array into smaller pieces (n-D to n-D).</span>
 
@@ -1343,7 +1352,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
         <span class="n">along</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">order</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Tile images in a certain order.</span>
 
 <span class="sd">        Parameters</span>
@@ -1426,7 +1435,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
     
 <div class="viewcode-block" id="LabeledArray.for_each_channel"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.for_each_channel">[docs]</a>    <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">for_each_channel</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">func</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">along</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;c&quot;</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Self</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Apply same function with different parameters for each channel. This function will be useful</span>
 <span class="sd">        when the parameters are dependent on channels, like wave length.</span>
 
@@ -1453,7 +1462,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
     
 <div class="viewcode-block" id="LabeledArray.for_params"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.for_params">[docs]</a>    <span class="nd">@check_input_and_output</span>
     <span class="k">def</span> <span class="nf">for_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">func</span><span class="p">:</span> <span class="n">Callable</span><span class="o">|</span><span class="nb">str</span><span class="p">,</span> <span class="n">var</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Iterable</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataList</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Apply same function with different parameters with same input. This function will be useful</span>
 <span class="sd">        when you want to try different conditions to the same image.</span>
 
@@ -1511,7 +1520,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
     
 <div class="viewcode-block" id="LabeledArray.extract"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.extract">[docs]</a>    <span class="nd">@check_input_and_output</span><span class="p">(</span><span class="n">need_labels</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="k">def</span> <span class="nf">extract</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">label_ids</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">filt</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">cval</span><span class="p">:</span><span class="nb">float</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataList</span><span class="p">[</span><span class="n">Self</span><span class="p">]:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Extract certain regions of the image and substitute others to `cval`.</span>
 
 <span class="sd">        Parameters</span>
@@ -1569,7 +1578,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
 
 
 <span class="k">def</span> <span class="nf">_iter_tile_yx</span><span class="p">(</span><span class="n">ymax</span><span class="p">,</span> <span class="n">xmax</span><span class="p">,</span> <span class="n">imgy</span><span class="p">,</span> <span class="n">imgx</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    +--+--+--+</span>
 <span class="sd">    | 0| 1| 2|</span>
 <span class="sd">    +--+--+--+</span>
@@ -1584,7 +1593,7 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
         <span class="k">yield</span> <span class="o">...</span><span class="p">,</span> <span class="n">sly</span><span class="p">,</span> <span class="n">slx</span>
 
 <span class="k">def</span> <span class="nf">_iter_tile_xy</span><span class="p">(</span><span class="n">ymax</span><span class="p">,</span> <span class="n">xmax</span><span class="p">,</span> <span class="n">imgy</span><span class="p">,</span> <span class="n">imgx</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    +--+--+--+</span>
 <span class="sd">    | 0| 3| 6|</span>
 <span class="sd">    +--+--+--+</span>
@@ -1654,6 +1663,29 @@ <h1>Source code for impy.arrays.labeledarray</h1><div class="highlight"><pre>
         <span class="n">cval</span><span class="o">=</span><span class="n">cval</span><span class="p">,</span>
         <span class="n">prefilter</span><span class="o">=</span><span class="n">prefilter</span><span class="p">,</span>
     <span class="p">)</span>
+
+<span class="k">def</span> <span class="nf">_map_coordinates_with_nan</span><span class="p">(</span><span class="nb">input</span><span class="p">,</span> <span class="n">coordinates</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="n">mode</span><span class="p">,</span> <span class="n">cval</span><span class="p">,</span> <span class="n">prefilter</span><span class="p">):</span>
+    <span class="n">nans</span> <span class="o">=</span> <span class="n">xp</span><span class="o">.</span><span class="n">isnan</span><span class="p">(</span><span class="nb">input</span><span class="p">)</span>
+    <span class="nb">input</span> <span class="o">=</span> <span class="n">xp</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="nb">input</span><span class="p">,</span> <span class="n">copy</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+    <span class="nb">input</span><span class="p">[</span><span class="n">nans</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
+    <span class="n">mapped</span> <span class="o">=</span> <span class="n">xp</span><span class="o">.</span><span class="n">ndi</span><span class="o">.</span><span class="n">map_coordinates</span><span class="p">(</span>
+        <span class="nb">input</span><span class="p">,</span>
+        <span class="n">xp</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">coordinates</span><span class="p">),</span>
+        <span class="n">order</span><span class="o">=</span><span class="n">order</span><span class="p">,</span>
+        <span class="n">mode</span><span class="o">=</span><span class="n">mode</span><span class="p">,</span>
+        <span class="n">cval</span><span class="o">=</span><span class="n">cval</span><span class="p">,</span>
+        <span class="n">prefilter</span><span class="o">=</span><span class="n">prefilter</span><span class="p">,</span>
+    <span class="p">)</span>
+    <span class="n">mapped_nans</span> <span class="o">=</span> <span class="n">xp</span><span class="o">.</span><span class="n">ndi</span><span class="o">.</span><span class="n">map_coordinates</span><span class="p">(</span>
+        <span class="n">nans</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">xp</span><span class="o">.</span><span class="n">float32</span><span class="p">),</span>
+        <span class="n">xp</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">coordinates</span><span class="p">),</span>
+        <span class="n">order</span><span class="o">=</span><span class="n">order</span><span class="p">,</span>
+        <span class="n">mode</span><span class="o">=</span><span class="n">mode</span><span class="p">,</span>
+        <span class="n">cval</span><span class="o">=</span><span class="n">cval</span><span class="p">,</span>
+        <span class="n">prefilter</span><span class="o">=</span><span class="n">prefilter</span><span class="p">,</span>
+    <span class="p">)</span> <span class="o">&gt;</span> <span class="mf">0.5</span>
+    <span class="n">mapped</span><span class="p">[</span><span class="n">mapped_nans</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
+    <span class="k">return</span> <span class="n">mapped</span>
 </pre></div>
 
            </div>
diff --git a/docs/_modules/impy/arrays/lazy.html b/docs/_modules/impy/arrays/lazy.html
index 5e92efad..cb79c304 100644
--- a/docs/_modules/impy/arrays/lazy.html
+++ b/docs/_modules/impy/arrays/lazy.html
@@ -3,7 +3,7 @@
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.arrays.lazy &mdash; impy 2.2.0 documentation</title>
+  <title>impy.arrays.lazy &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../../../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -11,9 +11,8 @@
   <![endif]-->
   
         <script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
-        <script src="../../../_static/jquery.js"></script>
-        <script src="../../../_static/underscore.js"></script>
         <script src="../../../_static/doctools.js"></script>
+        <script src="../../../_static/sphinx_highlight.js"></script>
     <script src="../../../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../../../genindex.html" />
     <link rel="search" title="Search" href="../../../search.html" /> 
@@ -24,14 +23,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../../../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../../../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../../../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -58,9 +61,9 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../../../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../../index.html">Module code</a> &raquo;</li>
-      <li>impy.arrays.lazy</li>
+      <li><a href="../../../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../../index.html">Module code</a></li>
+      <li class="breadcrumb-item active">impy.arrays.lazy</li>
       <li class="wy-breadcrumbs-aside">
       </li>
   </ul>
@@ -75,6 +78,7 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
 <span class="kn">import</span> <span class="nn">itertools</span>
 <span class="kn">from</span> <span class="nn">pathlib</span> <span class="kn">import</span> <span class="n">Path</span>
 <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Any</span><span class="p">,</span> <span class="n">Callable</span><span class="p">,</span> <span class="n">TYPE_CHECKING</span><span class="p">,</span> <span class="n">Sequence</span>
+<span class="kn">import</span> <span class="nn">warnings</span>
 <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
 <span class="kn">from</span> <span class="nn">numpy.typing</span> <span class="kn">import</span> <span class="n">ArrayLike</span><span class="p">,</span> <span class="n">DTypeLike</span>
 <span class="kn">from</span> <span class="nn">warnings</span> <span class="kn">import</span> <span class="n">warn</span>
@@ -84,6 +88,7 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
 <span class="kn">from</span> <span class="nn">.labeledarray</span> <span class="kn">import</span> <span class="n">LabeledArray</span>
 <span class="kn">from</span> <span class="nn">.imgarray</span> <span class="kn">import</span> <span class="n">ImgArray</span>
 <span class="kn">from</span> <span class="nn">.axesmixin</span> <span class="kn">import</span> <span class="n">AxesMixin</span>
+<span class="kn">from</span> <span class="nn">.tiled</span> <span class="kn">import</span> <span class="n">TiledAccessor</span>
 <span class="kn">from</span> <span class="nn">._utils</span> <span class="kn">import</span> <span class="n">_misc</span><span class="p">,</span> <span class="n">_transform</span><span class="p">,</span> <span class="n">_structures</span><span class="p">,</span> <span class="n">_filters</span><span class="p">,</span> <span class="n">_deconv</span><span class="p">,</span> <span class="n">_corr</span><span class="p">,</span> <span class="n">_docs</span>
 
 <span class="kn">from</span> <span class="nn">impy.utils.axesop</span> <span class="kn">import</span> <span class="n">slice_axes</span><span class="p">,</span> <span class="n">switch_slice</span><span class="p">,</span> <span class="n">complement_axes</span><span class="p">,</span> <span class="n">find_first_appeared</span>
@@ -100,10 +105,11 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
 
 <span class="k">if</span> <span class="n">TYPE_CHECKING</span><span class="p">:</span>
     <span class="kn">from</span> <span class="nn">dask.array.core</span> <span class="kn">import</span> <span class="n">Array</span> <span class="k">as</span> <span class="n">DaskArray</span>
-
+    <span class="kn">from</span> <span class="nn">impy.axes</span> <span class="kn">import</span> <span class="n">AxesTuple</span>
 
 <div class="viewcode-block" id="LazyImgArray"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.big.LazyImgArray">[docs]</a><span class="k">class</span> <span class="nc">LazyImgArray</span><span class="p">(</span><span class="n">AxesMixin</span><span class="p">):</span>
     <span class="n">additional_props</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;_source&quot;</span><span class="p">,</span> <span class="s2">&quot;_metadata&quot;</span><span class="p">,</span> <span class="s2">&quot;_name&quot;</span><span class="p">]</span>
+    <span class="n">tiled</span><span class="p">:</span> <span class="n">TiledAccessor</span><span class="p">[</span><span class="n">LazyImgArray</span><span class="p">]</span> <span class="o">=</span> <span class="n">TiledAccessor</span><span class="p">()</span>
     
     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">,</span>
@@ -124,7 +130,7 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
         
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">source</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;The source file path.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;The source file path.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_source</span>
     
     <span class="nd">@source</span><span class="o">.</span><span class="n">setter</span>
@@ -136,7 +142,7 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">name</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Name of the array.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Name of the array.&quot;&quot;&quot;</span>
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_name</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
             <span class="n">source</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">source</span>
             <span class="k">if</span> <span class="n">source</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
@@ -152,42 +158,42 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">metadata</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]:</span>
-        <span class="sd">&quot;&quot;&quot;Metadata dictionary of the array.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Metadata dictionary of the array.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_metadata</span>
 
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">ndim</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">int</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Number of dimensions of the array.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Number of dimensions of the array.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="o">.</span><span class="n">ndim</span>
     
     <span class="nd">@property</span>
-    <span class="k">def</span> <span class="nf">shape</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;Shape of the array.&quot;&quot;&quot;</span>
+    <span class="k">def</span> <span class="nf">shape</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">AxesTuple</span><span class="p">[</span><span class="nb">int</span><span class="p">]:</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Shape of the array.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">tuple</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
         
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">dtype</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;Data type of the array&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Data type of the array&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="o">.</span><span class="n">dtype</span>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">size</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">int</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Total number of elements in the array.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Total number of elements in the array.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="o">.</span><span class="n">size</span>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">itemsize</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;Size of each element in bytes.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Size of each element in bytes.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="o">.</span><span class="n">itemsize</span>
     
     <span class="nd">@property</span>
-    <span class="k">def</span> <span class="nf">chunksize</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;Chunk size of the array.&quot;&quot;&quot;</span>
+    <span class="k">def</span> <span class="nf">chunksize</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">AxesTuple</span><span class="p">[</span><span class="nb">int</span><span class="p">]:</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Chunk size of the array.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">tuple</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="o">.</span><span class="n">chunksize</span><span class="p">)</span>
         
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">GB</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Return the array size in GB.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Return the array size in GB.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="o">.</span><span class="n">nbytes</span> <span class="o">/</span> <span class="mf">1e9</span>
     
     <span class="n">gb</span> <span class="o">=</span> <span class="n">GB</span>  <span class="c1"># alias</span>
@@ -216,7 +222,7 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">out</span>
     
     <span class="k">def</span> <span class="fm">__neg__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Invert array.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Invert array.&quot;&quot;&quot;</span>
         <span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="p">(</span><span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">)</span>
         <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
         <span class="k">return</span> <span class="n">out</span>
@@ -362,7 +368,7 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
     
     
 <div class="viewcode-block" id="LazyImgArray.compute"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.big.LazyImgArray.compute">[docs]</a>    <span class="k">def</span> <span class="nf">compute</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ignore_limit</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Compute all the task and convert the result into ImgArray. If image size overwhelms MAX_GB</span>
 <span class="sd">        then MemoryError is raised.</span>
 <span class="sd">        &quot;&quot;&quot;</span>        
@@ -378,7 +384,7 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">img</span></div>
     
 <div class="viewcode-block" id="LazyImgArray.release"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.big.LazyImgArray.release">[docs]</a>    <span class="k">def</span> <span class="nf">release</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Compute all the tasks and store the data in memory map, and read it as a dask array</span>
 <span class="sd">        again.</span>
 <span class="sd">        &quot;&quot;&quot;</span>
@@ -386,11 +392,11 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
 
         <span class="k">with</span> <span class="n">tempfile</span><span class="o">.</span><span class="n">NamedTemporaryFile</span><span class="p">()</span> <span class="k">as</span> <span class="n">ntf</span><span class="p">:</span>
             <span class="n">mmap</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">memmap</span><span class="p">(</span><span class="n">ntf</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;w+&quot;</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
-            <span class="n">da</span><span class="o">.</span><span class="n">store</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">mmap</span><span class="p">,</span> <span class="n">compute</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+            <span class="n">da</span><span class="o">.</span><span class="n">store</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="o">.</span><span class="n">map_blocks</span><span class="p">(</span><span class="n">xp</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">),</span> <span class="n">mmap</span><span class="p">,</span> <span class="n">compute</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
             <span class="n">mmap</span><span class="o">.</span><span class="n">flush</span><span class="p">()</span>
         
         <span class="n">img</span> <span class="o">=</span> <span class="n">da</span><span class="o">.</span><span class="n">from_array</span><span class="p">(</span><span class="n">mmap</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">chunksize</span><span class="p">)</span><span class="o">.</span><span class="n">map_blocks</span><span class="p">(</span>
-            <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">,</span> <span class="n">meta</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([],</span> <span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
+            <span class="n">xp</span><span class="o">.</span><span class="n">array</span><span class="p">,</span> <span class="n">meta</span><span class="o">=</span><span class="n">xp</span><span class="o">.</span><span class="n">array</span><span class="p">([],</span> <span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span>
         <span class="p">)</span>
         <span class="k">if</span> <span class="n">update</span><span class="p">:</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">=</span> <span class="n">img</span>
@@ -445,7 +451,7 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
         <span class="n">balance</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> 
         <span class="n">update</span><span class="o">=</span><span class="kc">False</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Rechunk the bound dask array.</span>
 
 <span class="sd">        Parameters</span>
@@ -471,7 +477,7 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
             <span class="k">return</span> <span class="n">out</span></div>
         
 <div class="viewcode-block" id="LazyImgArray.apply_dask_func"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.big.LazyImgArray.apply_dask_func">[docs]</a>    <span class="k">def</span> <span class="nf">apply_dask_func</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">funcname</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Apply dask array function to the connected dask array.</span>
 
 <span class="sd">        Parameters</span>
@@ -504,7 +510,7 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
         <span class="n">dask_wrap</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
         <span class="n">args</span><span class="p">:</span> <span class="nb">tuple</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Rechunk array in a correct shape and apply function using `map_blocks`. This function is similar</span>
 <span class="sd">        to the `apply_dask` function in `MetaArray` while returns dask array bound LazyImgArray.</span>
 
@@ -611,10 +617,11 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
         <span class="n">depth</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">16</span><span class="p">,</span>
         <span class="n">boundary</span><span class="o">=</span><span class="s2">&quot;reflect&quot;</span><span class="p">,</span>
         <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">args</span><span class="p">:</span> <span class="nb">tuple</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">kwargs</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
+        <span class="n">args</span><span class="p">:</span> <span class="nb">tuple</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">kwargs</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DaskArray</span><span class="p">:</span>
         <span class="kn">from</span> <span class="nn">dask</span> <span class="kn">import</span> <span class="n">array</span> <span class="k">as</span> <span class="n">da</span>
+
         <span class="k">if</span> <span class="n">args</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
             <span class="n">args</span> <span class="o">=</span> <span class="p">()</span>
         <span class="k">if</span> <span class="n">kwargs</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
@@ -1056,11 +1063,11 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">pw</span></div>
     
 <div class="viewcode-block" id="LazyImgArray.chunksizeof"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.big.LazyImgArray.chunksizeof">[docs]</a>    <span class="k">def</span> <span class="nf">chunksizeof</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="p">:</span><span class="nb">str</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;Get the chunk size of the given axis&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Get the chunk size of the given axis&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="o">.</span><span class="n">chunksize</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="n">axis</span><span class="p">)]</span></div>
     
 <div class="viewcode-block" id="LazyImgArray.chunksizesof"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.big.LazyImgArray.chunksizesof">[docs]</a>    <span class="k">def</span> <span class="nf">chunksizesof</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axes</span><span class="p">:</span><span class="nb">str</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;Get the chunk sizes of the given axes&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Get the chunk sizes of the given axes&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="nb">tuple</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">chunksizeof</span><span class="p">(</span><span class="n">a</span><span class="p">)</span> <span class="k">for</span> <span class="n">a</span> <span class="ow">in</span> <span class="n">axes</span><span class="p">)</span></div>
         
 <div class="viewcode-block" id="LazyImgArray.transpose"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.big.LazyImgArray.transpose">[docs]</a>    <span class="nd">@_docs</span><span class="o">.</span><span class="n">copy_docs</span><span class="p">(</span><span class="n">ImgArray</span><span class="o">.</span><span class="n">transpose</span><span class="p">)</span>
@@ -1103,31 +1110,18 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
         
         <span class="k">return</span> <span class="n">out</span></div>
     
-<div class="viewcode-block" id="LazyImgArray.tiled_lowpass_filter"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.big.LazyImgArray.tiled_lowpass_filter">[docs]</a>    <span class="nd">@_docs</span><span class="o">.</span><span class="n">copy_docs</span><span class="p">(</span><span class="n">ImgArray</span><span class="o">.</span><span class="n">tiled_lowpass_filter</span><span class="p">)</span>
-    <span class="nd">@dims_to_spatial_axes</span>
+<div class="viewcode-block" id="LazyImgArray.tiled_lowpass_filter"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.big.LazyImgArray.tiled_lowpass_filter">[docs]</a>    <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@check_input_and_output_lazy</span>
     <span class="k">def</span> <span class="nf">tiled_lowpass_filter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">cutoff</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.2</span><span class="p">,</span> <span class="n">order</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">2</span><span class="p">,</span> <span class="n">overlap</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">16</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span>
                              <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
-        <span class="kn">from</span> <span class="nn">._utils._skimage</span> <span class="kn">import</span> <span class="n">_get_ND_butterworth_filter</span>
-        <span class="bp">self</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">as_float</span><span class="p">()</span>
-        <span class="n">c_axes</span> <span class="o">=</span> <span class="n">complement_axes</span><span class="p">(</span><span class="n">dims</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">)</span>
-        <span class="n">ndims</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">dims</span><span class="p">)</span>
-        <span class="n">cutoff</span> <span class="o">=</span> <span class="n">check_nd</span><span class="p">(</span><span class="n">cutoff</span><span class="p">,</span> <span class="n">ndims</span><span class="p">)</span>
-        <span class="k">if</span> <span class="nb">all</span><span class="p">((</span><span class="n">c</span> <span class="o">&gt;=</span> <span class="mf">0.5</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">ndims</span><span class="p">)</span> <span class="ow">or</span> <span class="n">c</span> <span class="o">&lt;=</span> <span class="mi">0</span><span class="p">)</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">cutoff</span><span class="p">):</span>
-            <span class="k">return</span> <span class="bp">self</span>
-        
-        <span class="n">depth</span> <span class="o">=</span> <span class="n">switch_slice</span><span class="p">(</span><span class="n">dims</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">,</span> <span class="n">overlap</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
-        
-        <span class="k">def</span> <span class="nf">func</span><span class="p">(</span><span class="n">arr</span><span class="p">):</span>
-            <span class="n">arr</span> <span class="o">=</span> <span class="n">xp</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="p">)</span>
-            <span class="n">shape</span> <span class="o">=</span> <span class="n">arr</span><span class="o">.</span><span class="n">shape</span>
-            <span class="n">weight</span> <span class="o">=</span> <span class="n">_get_ND_butterworth_filter</span><span class="p">(</span><span class="n">shape</span><span class="p">,</span> <span class="n">cutoff</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="kc">False</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
-            <span class="n">ft</span> <span class="o">=</span> <span class="n">xp</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">weight</span><span class="p">)</span> <span class="o">*</span> <span class="n">xp</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">rfftn</span><span class="p">(</span><span class="n">arr</span><span class="p">)</span>
-            <span class="n">ift</span> <span class="o">=</span> <span class="n">xp</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">irfftn</span><span class="p">(</span><span class="n">ft</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="n">shape</span><span class="p">)</span>
-            <span class="k">return</span> <span class="n">ift</span>
-        
-        <span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_apply_map_overlap</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">c_axes</span><span class="o">=</span><span class="n">c_axes</span><span class="p">,</span> <span class="n">depth</span><span class="o">=</span><span class="n">depth</span><span class="p">,</span> <span class="n">boundary</span><span class="o">=</span><span class="s2">&quot;reflect&quot;</span><span class="p">)</span>
-        <span class="k">return</span> <span class="n">out</span></div>
+        <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span>
+            <span class="s2">&quot;`tiled_lowpass_filter` is deprecated. Please use &quot;</span>
+            <span class="sa">f</span><span class="s2">&quot;`img.tiled(</span><span class="si">{</span><span class="n">overlap</span><span class="si">=}</span><span class="s2">).lowpass_filter(</span><span class="si">{</span><span class="n">cutoff</span><span class="si">=}</span><span class="s2">, </span><span class="si">{</span><span class="n">order</span><span class="si">=}</span><span class="s2">)` instead.&quot;</span><span class="p">,</span>
+            <span class="ne">DeprecationWarning</span><span class="p">,</span>
+        <span class="p">)</span>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">tiled</span><span class="p">(</span>
+            <span class="n">chunks</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">chunksizesof</span><span class="p">(</span><span class="n">dims</span><span class="p">),</span> <span class="n">overlap</span><span class="o">=</span><span class="n">overlap</span><span class="p">,</span> <span class="n">dims</span><span class="o">=</span><span class="n">dims</span><span class="p">,</span>
+        <span class="p">)</span><span class="o">.</span><span class="n">lowpass_filter</span><span class="p">(</span><span class="n">cutoff</span><span class="p">,</span> <span class="n">order</span><span class="p">)</span></div>
     
 <div class="viewcode-block" id="LazyImgArray.proj"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.big.LazyImgArray.proj">[docs]</a>    <span class="nd">@_docs</span><span class="o">.</span><span class="n">copy_docs</span><span class="p">(</span><span class="n">ImgArray</span><span class="o">.</span><span class="n">proj</span><span class="p">)</span>
     <span class="nd">@same_dtype</span>
@@ -1138,7 +1132,7 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
         <span class="k">elif</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">axis</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span>
             <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s2">&quot;`axis` must be str.&quot;</span><span class="p">)</span>
         <span class="n">axisint</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">axisof</span><span class="p">(</span><span class="n">a</span><span class="p">)</span> <span class="k">for</span> <span class="n">a</span> <span class="ow">in</span> <span class="n">axis</span><span class="p">]</span>
-        
+
         <span class="k">if</span> <span class="n">method</span> <span class="o">==</span> <span class="s2">&quot;mean&quot;</span><span class="p">:</span>
             <span class="n">projection</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">da</span><span class="p">,</span> <span class="n">method</span><span class="p">)(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="nb">tuple</span><span class="p">(</span><span class="n">axisint</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span>
         <span class="k">else</span><span class="p">:</span>
@@ -1170,7 +1164,7 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
         <span class="n">out</span> <span class="o">=</span> <span class="n">binfunc</span><span class="p">(</span><span class="n">reshaped_img</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="n">axes_to_reduce</span><span class="p">)</span>
         <span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>
         <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
-        <span class="n">out</span><span class="o">.</span><span class="n">axes</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">)</span> <span class="c1"># _set_info does not pass copy so new axes must be defined here.</span>
+        <span class="n">out</span><span class="o">.</span><span class="n">axes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>  <span class="c1"># _set_info does not pass copy so new axes must be defined here.</span>
         <span class="n">out</span><span class="o">.</span><span class="n">set_scale</span><span class="p">({</span><span class="n">a</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">scale</span><span class="p">[</span><span class="n">a</span><span class="p">]</span><span class="o">/</span><span class="n">scale</span> <span class="k">for</span> <span class="n">a</span><span class="p">,</span> <span class="n">scale</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">,</span> <span class="n">scale_</span><span class="p">)})</span>
         <span class="k">return</span> <span class="n">out</span></div>
     
@@ -1432,7 +1426,7 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
         <span class="p">)</span></div>
     
     <span class="k">def</span> <span class="nf">__array_function__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">func</span><span class="p">,</span> <span class="n">types</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Every time a numpy function (np.mean...) is called, this function will be called. Essentially numpy</span>
 <span class="sd">        function can be overloaded with this method.</span>
 <span class="sd">        &quot;&quot;&quot;</span>
@@ -1598,7 +1592,7 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
         <span class="k">except</span> <span class="n">ImageAxesError</span><span class="p">:</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">axes</span> <span class="o">=</span> <span class="kc">None</span>
         
-        <span class="k">return</span> <span class="kc">None</span></div>
+        <span class="k">return</span> <span class="bp">self</span></div>
     
 
 <span class="k">def</span> <span class="nf">_replace_inputs</span><span class="p">(</span><span class="n">img</span><span class="p">:</span> <span class="n">LazyImgArray</span><span class="p">,</span> <span class="n">args</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">):</span>
@@ -1648,16 +1642,16 @@ <h1>Source code for impy.arrays.lazy</h1><div class="highlight"><pre>
 <span class="c1"># numpy and cupy.</span>
 <span class="nd">@lru_cache</span>
 <span class="k">def</span> <span class="nf">_get_fft_func</span><span class="p">(</span><span class="n">resource</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Callable</span><span class="p">[[</span><span class="n">DaskArray</span><span class="p">],</span> <span class="n">DaskArray</span><span class="p">]:</span>
-    <span class="sd">&quot;&quot;&quot;Get the scipy FFT function for dask.&quot;&quot;&quot;</span>
-    <span class="kn">from</span> <span class="nn">array_api</span> <span class="kn">import</span> <span class="n">scipy_fft</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Get the scipy FFT function for dask.&quot;&quot;&quot;</span>
+    <span class="kn">from</span> <span class="nn">impy.array_api</span> <span class="kn">import</span> <span class="n">scipy_fft</span>
     <span class="kn">from</span> <span class="nn">dask</span> <span class="kn">import</span> <span class="n">array</span> <span class="k">as</span> <span class="n">da</span>
     
     <span class="k">return</span> <span class="n">da</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">fft_wrap</span><span class="p">(</span><span class="n">scipy_fft</span><span class="o">.</span><span class="n">fftn</span><span class="p">)</span>
 
 <span class="nd">@lru_cache</span>
 <span class="k">def</span> <span class="nf">_get_ifft_func</span><span class="p">(</span><span class="n">resource</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Callable</span><span class="p">[[</span><span class="n">DaskArray</span><span class="p">],</span> <span class="n">DaskArray</span><span class="p">]:</span>
-    <span class="sd">&quot;&quot;&quot;Get the scipy IFFT function for dask.&quot;&quot;&quot;</span>
-    <span class="kn">from</span> <span class="nn">array_api</span> <span class="kn">import</span> <span class="n">scipy_fft</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Get the scipy IFFT function for dask.&quot;&quot;&quot;</span>
+    <span class="kn">from</span> <span class="nn">impy.array_api</span> <span class="kn">import</span> <span class="n">scipy_fft</span>
     <span class="kn">from</span> <span class="nn">dask</span> <span class="kn">import</span> <span class="n">array</span> <span class="k">as</span> <span class="n">da</span>
     
     <span class="k">return</span> <span class="n">da</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">fft_wrap</span><span class="p">(</span><span class="n">scipy_fft</span><span class="o">.</span><span class="n">ifftn</span><span class="p">)</span>
diff --git a/docs/_modules/impy/arrays/phasearray.html b/docs/_modules/impy/arrays/phasearray.html
index 7321799c..cbc55d27 100644
--- a/docs/_modules/impy/arrays/phasearray.html
+++ b/docs/_modules/impy/arrays/phasearray.html
@@ -3,7 +3,7 @@
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.arrays.phasearray &mdash; impy 2.1.3 documentation</title>
+  <title>impy.arrays.phasearray &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../../../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -11,9 +11,8 @@
   <![endif]-->
   
         <script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
-        <script src="../../../_static/jquery.js"></script>
-        <script src="../../../_static/underscore.js"></script>
         <script src="../../../_static/doctools.js"></script>
+        <script src="../../../_static/sphinx_highlight.js"></script>
     <script src="../../../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../../../genindex.html" />
     <link rel="search" title="Search" href="../../../search.html" /> 
@@ -24,14 +23,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../../../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../../../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.1.3
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../../../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -58,9 +61,9 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../../../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../../index.html">Module code</a> &raquo;</li>
-      <li>impy.arrays.phasearray</li>
+      <li><a href="../../../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../../index.html">Module code</a></li>
+      <li class="breadcrumb-item active">impy.arrays.phasearray</li>
       <li class="wy-breadcrumbs-aside">
       </li>
   </ul>
@@ -160,19 +163,19 @@ <h1>Source code for impy.arrays.phasearray</h1><div class="highlight"><pre>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">periodicity</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Return the periodicity of current border.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Return the periodicity of current border.&quot;&quot;&quot;</span>
         <span class="n">a</span><span class="p">,</span> <span class="n">b</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">border</span>
         <span class="k">return</span> <span class="n">b</span> <span class="o">-</span> <span class="n">a</span>
     
     <span class="k">def</span> <span class="nf">_fix_border</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Considering periodic boundary condition, fix the values by `__mod__` method.</span>
 <span class="sd">        &quot;&quot;&quot;</span>        
         <span class="bp">self</span><span class="p">[:]</span> <span class="o">=</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">border</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">%</span> <span class="bp">self</span><span class="o">.</span><span class="n">periodicity</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">border</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
         <span class="k">return</span> <span class="kc">None</span>
     
 <div class="viewcode-block" id="PhaseArray.set_border"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.set_border">[docs]</a>    <span class="k">def</span> <span class="nf">set_border</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">a</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span> <span class="n">b</span><span class="p">:</span> <span class="nb">float</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Set new border safely.</span>
 
 <span class="sd">        Parameters</span>
@@ -222,7 +225,7 @@ <h1>Source code for impy.arrays.phasearray</h1><div class="highlight"><pre>
         <span class="n">out</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">angle</span><span class="p">(</span><span class="n">out</span><span class="p">)</span><span class="o">/</span><span class="n">a</span>
         <span class="n">out</span><span class="p">:</span> <span class="n">PhaseArray</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="p">)</span>
         <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
-        <span class="n">out</span><span class="o">.</span><span class="n">axes</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">)</span> <span class="c1"># _set_info does not pass copy so new axes must be defined here.</span>
+        <span class="n">out</span><span class="o">.</span><span class="n">axes</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>  <span class="c1"># _set_info does not pass copy so new axes must be defined here.</span>
         <span class="n">out</span><span class="o">.</span><span class="n">set_scale</span><span class="p">({</span><span class="n">a</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">scale</span><span class="p">[</span><span class="n">a</span><span class="p">]</span><span class="o">/</span><span class="n">scale</span> <span class="k">for</span> <span class="n">a</span><span class="p">,</span> <span class="n">scale</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">,</span> <span class="n">scale_</span><span class="p">)})</span>
         <span class="k">return</span> <span class="n">out</span></div>
     
@@ -230,7 +233,7 @@ <h1>Source code for impy.arrays.phasearray</h1><div class="highlight"><pre>
     <span class="nd">@dims_to_spatial_axes</span>
     <span class="nd">@same_dtype</span><span class="p">(</span><span class="n">asfloat</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
     <span class="k">def</span> <span class="nf">mean_filter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">radius</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">update</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PhaseArray</span><span class="p">:</span>
-        <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Mean filter using phase averaging method:</span>
 <span class="sd">        </span>
 <span class="sd">        :math:`\arg{\sum_{k}{e^{i X_k}}}`</span>
@@ -264,7 +267,7 @@ <h1>Source code for impy.arrays.phasearray</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">label</span><span class="o">=</span><span class="n">label</span><span class="p">,</span> <span class="n">dims</span><span class="o">=</span><span class="n">dims</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="n">alpha</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div>
     
 <div class="viewcode-block" id="PhaseArray.reslice"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.reslice">[docs]</a>    <span class="k">def</span> <span class="nf">reslice</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">src</span><span class="p">,</span> <span class="n">dst</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">order</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PropArray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Measure line profile iteratively for every slice of image. </span>
 <span class="sd">        </span>
 <span class="sd">        Because input is phase, we can not apply standard interpolation to calculate</span>
@@ -296,7 +299,7 @@ <h1>Source code for impy.arrays.phasearray</h1><div class="highlight"><pre>
     
 <div class="viewcode-block" id="PhaseArray.regionprops"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.regionprops">[docs]</a>    <span class="k">def</span> <span class="nf">regionprops</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">properties</span><span class="p">:</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span><span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">=</span> <span class="p">(</span><span class="s2">&quot;phase_mean&quot;</span><span class="p">,),</span> <span class="o">*</span><span class="p">,</span> 
                     <span class="n">extra_properties</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataDict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">PropArray</span><span class="p">]:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Measure region properties.</span>
 <span class="sd">        </span>
 <span class="sd">        Run ``skimage``&#39;s ``regionprops()`` function and return the results as PropArray, so</span>
@@ -398,7 +401,7 @@ <h1>Source code for impy.arrays.phasearray</h1><div class="highlight"><pre>
         <span class="n">prefilter</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">):</span>
-        <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Coordinate mapping in the image. See ``scipy.ndimage.map_coordinates``.</span>
 <span class="sd">        </span>
 <span class="sd">        For a ``PhaseArray``, standard interpolation does not work because of its specific</span>
diff --git a/docs/_modules/impy/arrays/tiled.html b/docs/_modules/impy/arrays/tiled.html
new file mode 100644
index 00000000..c7ec67da
--- /dev/null
+++ b/docs/_modules/impy/arrays/tiled.html
@@ -0,0 +1,325 @@
+<!DOCTYPE html>
+<html class="writer-html5" lang="en" >
+<head>
+  <meta charset="utf-8" />
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+           <div itemprop="articleBody">
+             
+  <h1>Source code for impy.arrays.tiled</h1><div class="highlight"><pre>
+<span></span><span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="n">annotations</span>
+<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">TYPE_CHECKING</span><span class="p">,</span> <span class="n">Any</span><span class="p">,</span> <span class="n">Callable</span><span class="p">,</span> <span class="n">Generic</span><span class="p">,</span> <span class="n">Literal</span><span class="p">,</span> <span class="n">TypeVar</span>
+<span class="kn">import</span> <span class="nn">weakref</span>
+
+<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="kn">from</span> <span class="nn">impy.utils.axesop</span> <span class="kn">import</span> <span class="n">switch_slice</span>
+<span class="kn">from</span> <span class="nn">impy.utils.misc</span> <span class="kn">import</span> <span class="n">check_nd</span>
+<span class="kn">from</span> <span class="nn">impy.array_api</span> <span class="kn">import</span> <span class="n">xp</span>
+<span class="kn">from</span> <span class="nn">impy.arrays.axesmixin</span> <span class="kn">import</span> <span class="n">AxesMixin</span>
+<span class="kn">from</span> <span class="nn">impy._types</span> <span class="kn">import</span> <span class="n">Dims</span>
+<span class="kn">from</span> <span class="nn">._utils</span> <span class="kn">import</span> <span class="n">_deconv</span><span class="p">,</span> <span class="n">_filters</span>
+<span class="kn">from</span> <span class="nn">._utils._skimage</span> <span class="kn">import</span> <span class="n">_get_ND_butterworth_filter</span>
+
+<span class="kn">from</span> <span class="nn">dask</span> <span class="kn">import</span> <span class="n">array</span> <span class="k">as</span> <span class="n">da</span>
+
+<span class="n">_T</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s2">&quot;_T&quot;</span><span class="p">,</span> <span class="n">bound</span><span class="o">=</span><span class="n">AxesMixin</span><span class="p">)</span>
+<span class="n">Boundary</span> <span class="o">=</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;reflect&quot;</span><span class="p">,</span> <span class="s2">&quot;periodic&quot;</span><span class="p">,</span> <span class="s2">&quot;nearest&quot;</span><span class="p">,</span> <span class="s2">&quot;none&quot;</span><span class="p">]</span>
+
+<div class="viewcode-block" id="TiledAccessor"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.TiledAccessor">[docs]</a><span class="k">class</span> <span class="nc">TiledAccessor</span><span class="p">(</span><span class="n">Generic</span><span class="p">[</span><span class="n">_T</span><span class="p">]):</span>
+    <span class="k">def</span> <span class="fm">__get__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">instance</span><span class="p">:</span> <span class="n">_T</span><span class="p">,</span> <span class="n">owner</span><span class="p">:</span> <span class="nb">type</span><span class="p">[</span><span class="n">_T</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="n">_PartialTiledImage</span><span class="p">[</span><span class="n">_T</span><span class="p">]:</span>
+        <span class="k">if</span> <span class="n">instance</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="k">return</span> <span class="bp">self</span>
+        <span class="k">return</span> <span class="n">_PartialTiledImage</span><span class="p">(</span><span class="n">instance</span><span class="p">)</span></div>
+
+
+<span class="k">class</span> <span class="nc">_PartialTiledImage</span><span class="p">(</span><span class="n">Generic</span><span class="p">[</span><span class="n">_T</span><span class="p">]):</span>
+    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">img</span><span class="p">:</span> <span class="n">_T</span><span class="p">):</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">_img</span> <span class="o">=</span> <span class="n">weakref</span><span class="o">.</span><span class="n">ref</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
+    
+    <span class="k">def</span> <span class="fm">__call__</span><span class="p">(</span>
+        <span class="bp">self</span><span class="p">,</span> 
+        <span class="n">chunks</span><span class="p">:</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;auto&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="s2">&quot;auto&quot;</span><span class="p">,</span> 
+        <span class="n">overlap</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">=</span> <span class="mi">32</span><span class="p">,</span>
+        <span class="n">boundary</span><span class="p">:</span> <span class="n">Boundary</span> <span class="o">|</span> <span class="nb">list</span><span class="p">[</span><span class="n">Boundary</span><span class="p">]</span> <span class="o">=</span> <span class="s2">&quot;reflect&quot;</span><span class="p">,</span>
+        <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">TiledImage</span><span class="p">:</span>
+        <span class="n">img</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_img</span><span class="p">()</span>
+        <span class="k">if</span> <span class="n">img</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s2">&quot;Image has been deleted&quot;</span><span class="p">)</span>
+        <span class="k">if</span> <span class="n">dims</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="n">dims</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">a</span> <span class="k">for</span> <span class="n">a</span> <span class="ow">in</span> <span class="s2">&quot;zyx&quot;</span> <span class="k">if</span> <span class="n">a</span> <span class="ow">in</span> <span class="n">img</span><span class="o">.</span><span class="n">axes</span><span class="p">)</span>
+        <span class="n">depth</span> <span class="o">=</span> <span class="n">switch_slice</span><span class="p">(</span><span class="n">dims</span><span class="p">,</span> <span class="n">img</span><span class="o">.</span><span class="n">axes</span><span class="p">,</span> <span class="n">overlap</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
+        <span class="k">return</span> <span class="n">TiledImage</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">chunks</span><span class="p">,</span> <span class="n">depth</span><span class="p">,</span> <span class="n">boundary</span><span class="p">)</span>
+
+
+<div class="viewcode-block" id="TiledImage"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.TiledImage">[docs]</a><span class="k">class</span> <span class="nc">TiledImage</span><span class="p">(</span><span class="n">Generic</span><span class="p">[</span><span class="n">_T</span><span class="p">]):</span>
+    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
+        <span class="bp">self</span><span class="p">,</span>
+        <span class="n">img</span><span class="p">:</span> <span class="n">_T</span><span class="p">,</span>
+        <span class="n">chunks</span><span class="p">:</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;auto&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="s2">&quot;auto&quot;</span><span class="p">,</span>
+        <span class="n">depth</span><span class="p">:</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">32</span><span class="p">,</span>
+        <span class="n">boundary</span><span class="p">:</span> <span class="n">Boundary</span> <span class="o">|</span> <span class="nb">list</span><span class="p">[</span><span class="n">Boundary</span><span class="p">]</span> <span class="o">=</span> <span class="s2">&quot;reflect&quot;</span><span class="p">,</span>
+    <span class="p">):</span>
+        <span class="k">if</span> <span class="n">img</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s2">&quot;Image has been deleted&quot;</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">_img</span> <span class="o">=</span> <span class="n">weakref</span><span class="o">.</span><span class="n">ref</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">_chunks</span> <span class="o">=</span> <span class="n">chunks</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">_depth</span> <span class="o">=</span> <span class="n">depth</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">_boundary</span> <span class="o">=</span> <span class="n">boundary</span>
+
+    <span class="nd">@property</span>
+    <span class="k">def</span> <span class="nf">chunks</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]:</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Chunksize of the tiled image.&quot;&quot;&quot;</span>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_chunks</span>
+
+    <span class="nd">@property</span>
+    <span class="k">def</span> <span class="nf">depth</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]:</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Depth of overlaps&quot;&quot;&quot;</span>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_depth</span>
+
+    <span class="nd">@property</span>
+    <span class="k">def</span> <span class="nf">boundary</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;How to handle the boundary of the image.&quot;&quot;&quot;</span>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_boundary</span>
+
+    <span class="k">def</span> <span class="fm">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span>
+        <span class="n">img</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_img</span><span class="p">()</span>
+        <span class="k">if</span> <span class="n">img</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="n">img_repr</span> <span class="o">=</span> <span class="s2">&quot;&lt;deleted image&gt;&quot;</span>
+        <span class="k">else</span><span class="p">:</span>
+            <span class="n">img_repr</span> <span class="o">=</span> <span class="nb">repr</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
+        <span class="k">return</span> <span class="sa">f</span><span class="s2">&quot;TiledImage&lt;chunks=</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">chunks</span><span class="si">}</span><span class="s2">, depth=</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">depth</span><span class="si">}</span><span class="s2">, boundary=</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">boundary</span><span class="si">}</span><span class="s2">&gt; of </span><span class="se">\n</span><span class="si">{</span><span class="n">img_repr</span><span class="si">}</span><span class="s2">&quot;</span>
+    
+    <span class="k">def</span> <span class="nf">_deref_image</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">_T</span><span class="p">:</span>
+        <span class="n">img</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_img</span><span class="p">()</span>
+        <span class="k">if</span> <span class="n">img</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s2">&quot;Image has been deleted&quot;</span><span class="p">)</span>
+        <span class="k">return</span> <span class="n">img</span>
+    
+    <span class="k">def</span> <span class="nf">_map_overlap</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">func</span><span class="p">:</span> <span class="n">Callable</span><span class="p">[[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">],</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">],</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
+        <span class="kn">from</span> <span class="nn">.imgarray</span> <span class="kn">import</span> <span class="n">ImgArray</span>
+        <span class="kn">from</span> <span class="nn">.lazy</span> <span class="kn">import</span> <span class="n">LazyImgArray</span>
+
+        <span class="n">img</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_deref_image</span><span class="p">()</span>
+        <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">ImgArray</span><span class="p">):</span>
+            <span class="nb">input</span> <span class="o">=</span> <span class="n">da</span><span class="o">.</span><span class="n">from_array</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">_chunks</span><span class="p">)</span>
+            <span class="n">out</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">=</span> <span class="n">xp</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">(</span>
+                <span class="n">da</span><span class="o">.</span><span class="n">map_overlap</span><span class="p">(</span>
+                    <span class="n">func</span><span class="p">,</span> 
+                    <span class="nb">input</span><span class="p">,</span>
+                    <span class="o">*</span><span class="n">args</span><span class="p">,</span>
+                    <span class="n">depth</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">depth</span><span class="p">,</span>
+                    <span class="n">boundary</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">boundary</span><span class="p">,</span>
+                    <span class="n">dtype</span><span class="o">=</span><span class="n">img</span><span class="o">.</span><span class="n">dtype</span><span class="p">,</span>
+                    <span class="o">**</span><span class="n">kwargs</span><span class="p">,</span>
+                <span class="p">)</span><span class="o">.</span><span class="n">compute</span><span class="p">()</span>
+            <span class="p">)</span>
+            <span class="n">out</span> <span class="o">=</span> <span class="n">out</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="vm">__class__</span><span class="p">)</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">img</span><span class="o">.</span><span class="n">axes</span><span class="p">)</span>
+        <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">LazyImgArray</span><span class="p">):</span>
+            <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_chunks</span> <span class="o">!=</span> <span class="s2">&quot;auto&quot;</span><span class="p">:</span>
+                <span class="n">img</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">rechunk</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_chunks</span><span class="p">)</span>
+            <span class="n">out</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">_apply_map_overlap</span><span class="p">(</span>
+                <span class="n">func</span><span class="p">,</span>
+                <span class="n">c_axes</span><span class="o">=</span><span class="s2">&quot;&quot;</span><span class="p">,</span>
+                <span class="n">depth</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">depth</span><span class="p">,</span>
+                <span class="n">boundary</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">boundary</span><span class="p">,</span> 
+                <span class="n">args</span><span class="o">=</span><span class="n">args</span><span class="p">,</span>
+                <span class="n">kwargs</span><span class="o">=</span><span class="n">kwargs</span><span class="p">,</span>
+            <span class="p">)</span>
+            <span class="n">out</span> <span class="o">=</span> <span class="n">LazyImgArray</span><span class="p">(</span><span class="n">out</span><span class="p">)</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
+        <span class="k">else</span><span class="p">:</span>
+            <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Cannot tile </span><span class="si">{</span><span class="nb">type</span><span class="p">(</span><span class="n">img</span><span class="p">)</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
+        <span class="k">return</span> <span class="n">out</span>
+
+<div class="viewcode-block" id="TiledImage.lowpass_filter"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.TiledImage.lowpass_filter">[docs]</a>    <span class="k">def</span> <span class="nf">lowpass_filter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">cutoff</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.2</span><span class="p">,</span> <span class="n">order</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">2</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">_T</span><span class="p">:</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">        Tile-wise butterworth lowpass filter.</span>
+
+<span class="sd">        Parameters</span>
+<span class="sd">        ----------</span>
+<span class="sd">        cutoff : float or array-like, default is 0.2</span>
+<span class="sd">            Cutoff frequency.</span>
+<span class="sd">        order : float, default is 2</span>
+<span class="sd">            Steepness of cutoff.</span>
+<span class="sd">        &quot;&quot;&quot;</span>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_map_overlap</span><span class="p">(</span><span class="n">_lowpass</span><span class="p">,</span> <span class="n">cutoff</span><span class="o">=</span><span class="n">cutoff</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="n">order</span><span class="p">)</span></div>
+    
+<div class="viewcode-block" id="TiledImage.lucy"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.TiledImage.lucy">[docs]</a>    <span class="k">def</span> <span class="nf">lucy</span><span class="p">(</span>
+        <span class="bp">self</span><span class="p">,</span>
+        <span class="n">psf</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">|</span> <span class="n">Callable</span><span class="p">[[</span><span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]],</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">],</span>
+        <span class="n">niter</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">50</span><span class="p">,</span>
+        <span class="n">eps</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">1e-5</span><span class="p">,</span>
+    <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">_T</span><span class="p">:</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">        Deconvolution of N-dimensional image, using Richardson-Lucy&#39;s algorithm.</span>
+<span class="sd">        </span>
+<span class="sd">        Parameters</span>
+<span class="sd">        ----------</span>
+<span class="sd">        psf : ndarray or callable</span>
+<span class="sd">            Point spread function. If a function is given, `psf(shape)` will be</span>
+<span class="sd">            called to generate the PSF.</span>
+<span class="sd">        niter : int, default is 50.</span>
+<span class="sd">            Number of iterations.</span>
+<span class="sd">        eps : float, default is 1e-5</span>
+<span class="sd">            During deconvolution, division by small values in the convolve image </span>
+<span class="sd">            of estimation and PSF may cause divergence. Therefore, division by </span>
+<span class="sd">            values under `eps` is substituted to zero.</span>
+<span class="sd">        &quot;&quot;&quot;</span>
+        <span class="n">img</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_deref_image</span><span class="p">()</span>
+        <span class="n">scale</span> <span class="o">=</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="n">scale</span><span class="o">.</span><span class="n">values</span><span class="p">())</span>
+        
+        <span class="k">def</span> <span class="nf">func</span><span class="p">(</span><span class="n">arr</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
+            <span class="n">psf_ft</span><span class="p">,</span> <span class="n">psf_ft_conj</span> <span class="o">=</span> <span class="n">_deconv</span><span class="o">.</span><span class="n">check_psf</span><span class="p">(</span><span class="n">arr</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">scale</span><span class="p">,</span> <span class="n">psf</span><span class="p">)</span>
+            <span class="k">return</span> <span class="n">_deconv</span><span class="o">.</span><span class="n">richardson_lucy</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">psf_ft</span><span class="p">,</span> <span class="n">psf_ft_conj</span><span class="p">,</span> <span class="n">niter</span><span class="p">,</span> <span class="n">eps</span><span class="p">)</span>
+            
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_map_overlap</span><span class="p">(</span><span class="n">func</span><span class="p">)</span></div>
+    
+<div class="viewcode-block" id="TiledImage.gaussian_filter"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.TiledImage.gaussian_filter">[docs]</a>    <span class="k">def</span> <span class="nf">gaussian_filter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sigma</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">1.0</span><span class="p">,</span> <span class="n">fourier</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">_T</span><span class="p">:</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">        Run Gaussian filter (Gaussian blur).</span>
+<span class="sd">        </span>
+<span class="sd">        Parameters</span>
+<span class="sd">        ----------</span>
+<span class="sd">        {sigma}{fourier}</span>
+<span class="sd">        &quot;&quot;&quot;</span>
+        <span class="n">filter_func</span> <span class="o">=</span> <span class="n">_filters</span><span class="o">.</span><span class="n">gaussian_filter_fourier</span> <span class="k">if</span> <span class="n">fourier</span> <span class="k">else</span> <span class="n">_filters</span><span class="o">.</span><span class="n">gaussian_filter</span>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_map_overlap</span><span class="p">(</span><span class="n">filter_func</span><span class="p">,</span> <span class="n">sigma</span><span class="o">=</span><span class="n">sigma</span><span class="p">)</span></div>
+    
+<div class="viewcode-block" id="TiledImage.dog_filter"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.TiledImage.dog_filter">[docs]</a>    <span class="k">def</span> <span class="nf">dog_filter</span><span class="p">(</span>
+        <span class="bp">self</span><span class="p">,</span>
+        <span class="n">low_sigma</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">1.0</span><span class="p">,</span>
+        <span class="n">high_sigma</span><span class="p">:</span> <span class="nb">float</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">fourier</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
+    <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">_T</span><span class="p">:</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">        Run Difference of Gaussian filter. This function does not support `update`</span>
+<span class="sd">        argument because intensity can be negative.</span>
+<span class="sd">        </span>
+<span class="sd">        Parameters</span>
+<span class="sd">        ----------</span>
+<span class="sd">        low_sigma : scalar or array of scalars, default is 1.</span>
+<span class="sd">            lower standard deviation(s) of Gaussian.</span>
+<span class="sd">        high_sigma : scalar or array of scalars, default is x1.6 of low_sigma.</span>
+<span class="sd">            higher standard deviation(s) of Gaussian.</span>
+<span class="sd">        {fourier}</span>
+<span class="sd">        &quot;&quot;&quot;</span>        
+        <span class="k">if</span> <span class="n">high_sigma</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="n">high_sigma</span> <span class="o">=</span> <span class="n">low_sigma</span> <span class="o">*</span> <span class="mf">1.6</span>
+        <span class="n">filter_func</span> <span class="o">=</span> <span class="n">_filters</span><span class="o">.</span><span class="n">dog_filter_fourier</span> <span class="k">if</span> <span class="n">fourier</span> <span class="k">else</span> <span class="n">_filters</span><span class="o">.</span><span class="n">dog_filter</span>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_map_overlap</span><span class="p">(</span><span class="n">filter_func</span><span class="p">,</span> <span class="n">low_sigma</span><span class="o">=</span><span class="n">low_sigma</span><span class="p">,</span> <span class="n">high_sigma</span><span class="o">=</span><span class="n">high_sigma</span><span class="p">)</span></div>
+
+<div class="viewcode-block" id="TiledImage.log_filter"><a class="viewcode-back" href="../../../apidoc/impy.arrays.html#impy.arrays.imgarray.TiledImage.log_filter">[docs]</a>    <span class="k">def</span> <span class="nf">log_filter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sigma</span><span class="p">:</span> <span class="nb">float</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">_T</span><span class="p">:</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">        Laplacian of Gaussian filter.</span>
+
+<span class="sd">        Parameters</span>
+<span class="sd">        ----------</span>
+<span class="sd">        {sigma}</span>
+<span class="sd">        &quot;&quot;&quot;</span>
+        <span class="k">return</span> <span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">_map_overlap</span><span class="p">(</span><span class="n">_filters</span><span class="o">.</span><span class="n">gaussian_laplace</span><span class="p">,</span> <span class="n">sigma</span><span class="o">=</span><span class="n">sigma</span><span class="p">)</span></div></div>
+
+
+<span class="k">def</span> <span class="nf">_lowpass</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">cutoff</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="mi">2</span><span class="p">):</span>
+    <span class="n">arr</span> <span class="o">=</span> <span class="n">xp</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="p">)</span>
+    <span class="n">shape</span> <span class="o">=</span> <span class="n">arr</span><span class="o">.</span><span class="n">shape</span>
+    <span class="n">_cutoff</span> <span class="o">=</span> <span class="n">check_nd</span><span class="p">(</span><span class="n">cutoff</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">shape</span><span class="p">))</span>
+    <span class="n">weight</span> <span class="o">=</span> <span class="n">_get_ND_butterworth_filter</span><span class="p">(</span><span class="n">shape</span><span class="p">,</span> <span class="n">_cutoff</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="kc">False</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
+    <span class="n">ft</span> <span class="o">=</span> <span class="n">xp</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">weight</span><span class="p">)</span> <span class="o">*</span> <span class="n">xp</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">rfftn</span><span class="p">(</span><span class="n">arr</span><span class="p">)</span>
+    <span class="n">ift</span> <span class="o">=</span> <span class="n">xp</span><span class="o">.</span><span class="n">fft</span><span class="o">.</span><span class="n">irfftn</span><span class="p">(</span><span class="n">ft</span><span class="p">,</span> <span class="n">s</span><span class="o">=</span><span class="n">shape</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">xp</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">(</span><span class="n">ift</span><span class="p">)</span>
+</pre></div>
+
+           </div>
+          </div>
+          <footer>
+
+  <hr/>
+
+  <div role="contentinfo">
+    <p>&#169; Copyright 2021, Hanjin Liu.</p>
+  </div>
+
+  Built with <a href="https://www.sphinx-doc.org/">Sphinx</a> using a
+    <a href="https://github.com/readthedocs/sphinx_rtd_theme">theme</a>
+    provided by <a href="https://readthedocs.org">Read the Docs</a>.
+   
+
+</footer>
+        </div>
+      </div>
+    </section>
+  </div>
+  <script>
+      jQuery(function () {
+          SphinxRtdTheme.Navigation.enable(true);
+      });
+  </script> 
+
+</body>
+</html>
\ No newline at end of file
diff --git a/docs/_modules/impy/core.html b/docs/_modules/impy/core.html
index 5f174948..7e3411ff 100644
--- a/docs/_modules/impy/core.html
+++ b/docs/_modules/impy/core.html
@@ -3,7 +3,7 @@
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.core &mdash; impy 2.2.0 documentation</title>
+  <title>impy.core &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -11,9 +11,8 @@
   <![endif]-->
   
         <script data-url_root="../../" id="documentation_options" src="../../_static/documentation_options.js"></script>
-        <script src="../../_static/jquery.js"></script>
-        <script src="../../_static/underscore.js"></script>
         <script src="../../_static/doctools.js"></script>
+        <script src="../../_static/sphinx_highlight.js"></script>
     <script src="../../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../../genindex.html" />
     <link rel="search" title="Search" href="../../search.html" /> 
@@ -24,14 +23,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -58,9 +61,9 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../index.html">Module code</a> &raquo;</li>
-      <li>impy.core</li>
+      <li><a href="../../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../index.html">Module code</a></li>
+      <li class="breadcrumb-item active">impy.core</li>
       <li class="wy-breadcrumbs-aside">
       </li>
   </ul>
@@ -76,19 +79,17 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
 <span class="kn">import</span> <span class="nn">re</span>
 <span class="kn">import</span> <span class="nn">glob</span>
 <span class="kn">import</span> <span class="nn">itertools</span>
-<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">TYPE_CHECKING</span>
-
-<span class="k">if</span> <span class="n">sys</span><span class="o">.</span><span class="n">version_info</span> <span class="o">&lt;</span> <span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">10</span><span class="p">):</span>
-    <span class="kn">from</span> <span class="nn">typing_extensions</span> <span class="kn">import</span> <span class="n">ParamSpec</span>
-<span class="k">else</span><span class="p">:</span>
-    <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">ParamSpec</span>
+<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">TYPE_CHECKING</span><span class="p">,</span> <span class="n">Any</span><span class="p">,</span> <span class="n">Callable</span><span class="p">,</span> <span class="n">Iterable</span><span class="p">,</span> <span class="n">Sequence</span>
+<span class="kn">from</span> <span class="nn">typing_extensions</span> <span class="kn">import</span> <span class="n">Literal</span>
+<span class="kn">import</span> <span class="nn">warnings</span>
+<span class="kn">from</span> <span class="nn">typing_extensions</span> <span class="kn">import</span> <span class="n">ParamSpec</span>
 <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
 <span class="kn">from</span> <span class="nn">functools</span> <span class="kn">import</span> <span class="n">wraps</span>
 
 <span class="kn">from</span> <span class="nn">impy</span> <span class="kn">import</span> <span class="n">io</span>
 <span class="kn">from</span> <span class="nn">impy.utils</span> <span class="kn">import</span> <span class="n">gauss</span>
-<span class="kn">from</span> <span class="nn">impy.utils.slicer</span> <span class="kn">import</span> <span class="o">*</span>
-<span class="kn">from</span> <span class="nn">impy._types</span> <span class="kn">import</span> <span class="o">*</span>
+<span class="kn">from</span> <span class="nn">impy.utils.slicer</span> <span class="kn">import</span> <span class="n">solve_slicer</span>
+<span class="kn">from</span> <span class="nn">impy._types</span> <span class="kn">import</span> <span class="n">AxesTargetedSlicer</span><span class="p">,</span> <span class="n">nDFloat</span>
 <span class="kn">from</span> <span class="nn">impy.axes</span> <span class="kn">import</span> <span class="n">ImageAxesError</span><span class="p">,</span> <span class="n">broadcast</span><span class="p">,</span> <span class="n">Axes</span><span class="p">,</span> <span class="n">AxesLike</span><span class="p">,</span> <span class="n">AxesTuple</span>
 <span class="kn">from</span> <span class="nn">impy.collections</span> <span class="kn">import</span> <span class="n">DataList</span>
 <span class="kn">from</span> <span class="nn">impy.arrays.bases</span> <span class="kn">import</span> <span class="n">MetaArray</span>
@@ -97,7 +98,7 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
 
 <span class="k">if</span> <span class="n">TYPE_CHECKING</span><span class="p">:</span>
     <span class="kn">from</span> <span class="nn">numpy.typing</span> <span class="kn">import</span> <span class="n">ArrayLike</span><span class="p">,</span> <span class="n">DTypeLike</span>
-    <span class="kn">from</span> <span class="nn">.roi</span> <span class="kn">import</span> <span class="n">RoiList</span>
+    <span class="kn">from</span> <span class="nn">impy.roi</span> <span class="kn">import</span> <span class="n">RoiList</span>
     <span class="c1"># NOTE: &quot;_ShapeLike&quot; is not a public type in numpy.typing.</span>
     <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">SupportsIndex</span><span class="p">,</span> <span class="n">Union</span>
     <span class="n">ShapeLike</span> <span class="o">=</span> <span class="n">Union</span><span class="p">[</span><span class="n">SupportsIndex</span><span class="p">,</span> <span class="n">Sequence</span><span class="p">[</span><span class="n">SupportsIndex</span><span class="p">]]</span>
@@ -131,7 +132,7 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
 
 
 <span class="n">shared_docs</span> <span class="o">=</span> \
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    dtype : data type, optional</span>
 <span class="sd">        Image data type.</span>
 <span class="sd">    name : str, optional</span>
@@ -141,7 +142,7 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
 <span class="sd">    &quot;&quot;&quot;</span>    
     
 <span class="k">def</span> <span class="nf">_write_docs</span><span class="p">(</span><span class="n">func</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;Add doc for numpy function.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Add doc for numpy function.&quot;&quot;&quot;</span>
     <span class="n">func</span><span class="o">.</span><span class="vm">__doc__</span> <span class="o">=</span> <span class="n">re</span><span class="o">.</span><span class="n">sub</span><span class="p">(</span><span class="sa">r</span><span class="s2">&quot;</span><span class="si">{}</span><span class="s2">&quot;</span><span class="p">,</span> <span class="n">shared_docs</span><span class="p">,</span> <span class="n">func</span><span class="o">.</span><span class="vm">__doc__</span><span class="p">)</span>
     <span class="k">return</span> <span class="n">func</span>
 
@@ -150,7 +151,7 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
     <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span><span class="p">,</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span><span class="p">]:</span>
-    <span class="sd">&quot;&quot;&quot;Normalize input parameters for MetaArray construction.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Normalize input parameters for MetaArray construction.&quot;&quot;&quot;</span>
     <span class="k">if</span> <span class="n">like</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">like</span><span class="p">,</span> <span class="p">(</span><span class="n">MetaArray</span><span class="p">,</span> <span class="n">LazyImgArray</span><span class="p">)):</span>
             <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span>
@@ -172,7 +173,7 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
     <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    make an ImgArray object, like ``np.array(x)``</span>
 <span class="sd">    </span>
 <span class="sd">    Parameters</span>
@@ -214,13 +215,13 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="asarray"><a class="viewcode-back" href="../../apidoc/impy.html#impy.core.asarray">[docs]</a><span class="nd">@_write_docs</span>
 <span class="k">def</span> <span class="nf">asarray</span><span class="p">(</span>
     <span class="n">arr</span><span class="p">:</span> <span class="n">ArrayLike</span><span class="p">,</span>
-    <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="o">*</span><span class="p">,</span> 
-    <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-    <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    make an ImgArray object, like ``np.asarray(x)``</span>
 <span class="sd">    </span>
 <span class="sd">    Parameters</span>
@@ -243,11 +244,11 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
     <span class="n">arr</span><span class="p">:</span> <span class="n">ArrayLike</span><span class="p">,</span>
     <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="o">*</span><span class="p">,</span> 
-    <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-    <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Make an Label object.</span>
 <span class="sd">    </span>
 <span class="sd">    This function helps to create a Label object from an array. Dtype check is performed</span>
@@ -293,73 +294,24 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
     <span class="bp">self</span> <span class="o">=</span> <span class="n">Label</span><span class="p">(</span><span class="n">_arr</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">)</span>
     <span class="k">return</span> <span class="bp">self</span></div>
 
-<div class="viewcode-block" id="aslazy"><a class="viewcode-back" href="../../apidoc/impy.html#impy.core.aslazy">[docs]</a><span class="nd">@_write_docs</span>
-<span class="k">def</span> <span class="nf">aslazy</span><span class="p">(</span>
-    <span class="n">arr</span><span class="p">:</span> <span class="n">ArrayLike</span><span class="p">,</span> 
-    <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-    <span class="o">*</span><span class="p">,</span> 
-    <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-    <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-    <span class="n">chunks</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span>
-    <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
-<span class="sd">    Make an LazyImgArray object from other types of array.</span>
-<span class="sd">    </span>
-<span class="sd">    Parameters</span>
-<span class="sd">    ----------</span>
-<span class="sd">    arr : array-like</span>
-<span class="sd">        Base array.</span>
-<span class="sd">    {}</span>
-<span class="sd">    chunks : int, tuple</span>
-<span class="sd">        How to chunk the array. For details see ``dask.array.from_array``.</span>
-<span class="sd">        </span>
-<span class="sd">    Returns</span>
-<span class="sd">    -------</span>
-<span class="sd">    LazyImgArray</span>
-<span class="sd">    </span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="kn">from</span> <span class="nn">dask</span> <span class="kn">import</span> <span class="n">array</span> <span class="k">as</span> <span class="n">da</span>
-    <span class="kn">from</span> <span class="nn">dask.array.core</span> <span class="kn">import</span> <span class="n">Array</span> <span class="k">as</span> <span class="n">DaskArray</span>
-
-    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">MetaArray</span><span class="p">):</span>
-        <span class="n">arr</span> <span class="o">=</span> <span class="n">da</span><span class="o">.</span><span class="n">from_array</span><span class="p">(</span><span class="n">arr</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">)</span>
-    <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">memmap</span><span class="p">)):</span>
-        <span class="n">arr</span> <span class="o">=</span> <span class="n">da</span><span class="o">.</span><span class="n">from_array</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">)</span>
-    <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">LazyImgArray</span><span class="p">):</span>
-        <span class="n">arr</span> <span class="o">=</span> <span class="n">arr</span><span class="o">.</span><span class="n">value</span>
-    <span class="k">elif</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">DaskArray</span><span class="p">):</span>
-        <span class="n">arr</span> <span class="o">=</span> <span class="n">da</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="p">)</span>
-    <span class="k">else</span><span class="p">:</span>
-        <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Unsupported array type </span><span class="si">{</span><span class="nb">type</span><span class="p">(</span><span class="n">arr</span><span class="p">)</span><span class="si">}</span><span class="s2">.&quot;</span><span class="p">)</span>
-        
-    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)</span> <span class="ow">and</span> <span class="n">dtype</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
-        <span class="k">if</span> <span class="n">arr</span><span class="o">.</span><span class="n">dtype</span> <span class="ow">in</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">uint16</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">):</span>
-            <span class="n">dtype</span> <span class="o">=</span> <span class="n">arr</span><span class="o">.</span><span class="n">dtype</span>
-        <span class="k">elif</span> <span class="n">arr</span><span class="o">.</span><span class="n">dtype</span><span class="o">.</span><span class="n">kind</span> <span class="o">==</span> <span class="s2">&quot;f&quot;</span><span class="p">:</span>
-            <span class="n">dtype</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">float32</span>
-        <span class="k">else</span><span class="p">:</span>
-            <span class="n">dtype</span> <span class="o">=</span> <span class="n">arr</span><span class="o">.</span><span class="n">dtype</span>
-        
-    <span class="n">axes</span><span class="p">,</span> <span class="n">name</span> <span class="o">=</span> <span class="n">_normalize_params</span><span class="p">(</span><span class="n">axes</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
-
-    <span class="c1"># Automatically determine axes</span>
-    <span class="k">if</span> <span class="n">axes</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
-        <span class="n">axes</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;x&quot;</span><span class="p">,</span> <span class="s2">&quot;yx&quot;</span><span class="p">,</span> <span class="s2">&quot;tyx&quot;</span><span class="p">,</span> <span class="s2">&quot;tzyx&quot;</span><span class="p">,</span> <span class="s2">&quot;tzcyx&quot;</span><span class="p">,</span> <span class="s2">&quot;ptzcyx&quot;</span><span class="p">][</span><span class="n">arr</span><span class="o">.</span><span class="n">ndim</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
-            
-    <span class="bp">self</span> <span class="o">=</span> <span class="n">LazyImgArray</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">)</span>
+<div class="viewcode-block" id="aslazy"><a class="viewcode-back" href="../../apidoc/impy.html#impy.core.aslazy">[docs]</a><span class="k">def</span> <span class="nf">aslazy</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+    <span class="kn">from</span> <span class="nn">impy.lazy</span> <span class="kn">import</span> <span class="n">asarray</span> <span class="k">as</span> <span class="n">lazy_asarray</span>
     
-    <span class="k">return</span> <span class="bp">self</span></div>
+    <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span>
+        <span class="s2">&quot;impy.aslazy is deprecated. Please use impy.lazy.asarray instead.&quot;</span><span class="p">,</span> 
+        <span class="ne">DeprecationWarning</span><span class="p">,</span>
+    <span class="p">)</span>
+    <span class="k">return</span> <span class="n">lazy_asarray</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div>
 
 <div class="viewcode-block" id="asbigarray"><a class="viewcode-back" href="../../apidoc/impy.html#impy.core.asbigarray">[docs]</a><span class="k">def</span> <span class="nf">asbigarray</span><span class="p">(</span>
     <span class="n">arr</span><span class="p">:</span> <span class="n">ArrayLike</span><span class="p">,</span> 
     <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="o">*</span><span class="p">,</span> 
-    <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-    <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">BigImgArray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Make an BigImgArray object from other types of array.</span>
 <span class="sd">    </span>
 <span class="sd">    Parameters</span>
@@ -425,8 +377,10 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
 <span class="s2">            Image axes. Must be same length as image dimension.</span>
 <span class="s2">        name: str, optional</span>
 <span class="s2">            Image name.</span>
-<span class="s2">        </span>
-<span class="s2">        </span><span class="si">{</span><span class="n">npfunc</span><span class="o">.</span><span class="vm">__doc__</span><span class="si">}</span><span class="s2"></span>
+<span class="s2">        like: MetaArray, optional</span>
+<span class="s2">            Reference array from which name and axes will be copied.</span>
+
+<span class="s2">        </span><span class="si">{</span><span class="n">npfunc</span><span class="o">.</span><span class="vm">__doc__</span><span class="si">}</span>
 <span class="s2">        &quot;&quot;&quot;</span>
         <span class="p">)</span>
     <span class="n">_func</span><span class="o">.</span><span class="vm">__annotations__</span><span class="o">.</span><span class="n">update</span><span class="p">({</span><span class="s2">&quot;return&quot;</span><span class="p">:</span> <span class="n">ImgArray</span><span class="p">})</span>
@@ -445,7 +399,11 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
 <span class="k">def</span> <span class="nf">full</span><span class="p">(</span><span class="n">shape</span><span class="p">:</span> <span class="n">ShapeLike</span><span class="p">,</span> <span class="n">fill_value</span><span class="p">:</span> <span class="n">Any</span><span class="p">,</span> <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">uint16</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span> <span class="o">...</span></div>
 
 <div class="viewcode-block" id="arange"><a class="viewcode-back" href="../../apidoc/impy.html#impy.core.arange">[docs]</a><span class="nd">@_inject_numpy_function</span>
-<span class="k">def</span> <span class="nf">arange</span><span class="p">(</span><span class="n">stop</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="o">...</span><span class="p">,</span> <span class="n">like</span><span class="p">:</span> <span class="n">Any</span> <span class="o">=</span> <span class="o">...</span><span class="p">):</span> <span class="o">...</span></div>
+<span class="k">def</span> <span class="nf">arange</span><span class="p">(</span><span class="n">stop</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span> <span class="o">...</span></div>
+
+<span class="nd">@_inject_numpy_function</span>
+<span class="k">def</span> <span class="nf">fromiter</span><span class="p">(</span><span class="n">iterable</span><span class="p">:</span> <span class="n">Iterable</span><span class="p">,</span> <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span><span class="p">,</span> <span class="n">count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="o">-</span><span class="mi">1</span><span class="p">):</span> <span class="o">...</span>
+
     
 <div class="viewcode-block" id="indices"><a class="viewcode-back" href="../../apidoc/impy.html#impy.core.indices">[docs]</a><span class="k">def</span> <span class="nf">indices</span><span class="p">(</span>
     <span class="n">dimensions</span><span class="p">:</span> <span class="n">ShapeLike</span><span class="p">,</span>
@@ -455,7 +413,7 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
     <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">AxesTuple</span><span class="p">[</span><span class="n">ImgArray</span><span class="p">]:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Copy of ``numpy.indices``.</span>
 <span class="sd">    </span>
 <span class="sd">    Parameters</span>
@@ -490,7 +448,7 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
     <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Make an Gaussian kernel or Gaussian image.</span>
 
 <span class="sd">    Parameters</span>
@@ -520,9 +478,11 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="circular_mask"><a class="viewcode-back" href="../../apidoc/impy.html#impy.core.circular_mask">[docs]</a><span class="k">def</span> <span class="nf">circular_mask</span><span class="p">(</span>
     <span class="n">radius</span><span class="p">:</span> <span class="n">nDFloat</span><span class="p">,</span> 
     <span class="n">shape</span><span class="p">:</span> <span class="n">ShapeLike</span><span class="p">,</span>
-    <span class="n">center</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">=</span> <span class="s2">&quot;center&quot;</span>
+    <span class="n">center</span><span class="p">:</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;center&quot;</span><span class="p">]</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">=</span> <span class="s2">&quot;center&quot;</span><span class="p">,</span>
+    <span class="n">soft</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
+    <span class="n">out_value</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Make a circular or ellipsoid shaped mask. Region close to center will be filled with ``False``. </span>
 
 <span class="sd">    Parameters</span>
@@ -545,19 +505,35 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
         <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;Length of `shape` and `center` must be same.&quot;</span><span class="p">)</span>
     
     <span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">isscalar</span><span class="p">(</span><span class="n">radius</span><span class="p">):</span>
-        <span class="n">radius</span> <span class="o">=</span> <span class="p">[</span><span class="n">radius</span><span class="p">]</span><span class="o">*</span><span class="nb">len</span><span class="p">(</span><span class="n">shape</span><span class="p">)</span>
-    <span class="k">elif</span> <span class="nb">len</span><span class="p">(</span><span class="n">radius</span><span class="p">)</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">shape</span><span class="p">):</span>
-        <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;Length of `shape` and `radius` must be same.&quot;</span><span class="p">)</span>
+        <span class="n">radius</span> <span class="o">=</span> <span class="p">[</span><span class="n">radius</span><span class="p">]</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">shape</span><span class="p">)</span>
+    <span class="k">else</span><span class="p">:</span>
+        <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">radius</span><span class="p">)</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">shape</span><span class="p">):</span>
+            <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;Length of `shape` and `radius` must be same.&quot;</span><span class="p">)</span>
+        <span class="k">if</span> <span class="n">soft</span><span class="p">:</span>
+            <span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s2">&quot;Soft mask is not implemented for ellipsoid mask.&quot;</span><span class="p">)</span>
 
     <span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">indices</span><span class="p">(</span><span class="n">shape</span><span class="p">)</span>
-    <span class="n">s</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(((</span><span class="n">x0</span> <span class="o">-</span> <span class="n">c0</span><span class="p">)</span><span class="o">/</span><span class="n">r0</span><span class="p">)</span><span class="o">**</span><span class="mi">2</span> <span class="k">for</span> <span class="n">x0</span><span class="p">,</span> <span class="n">c0</span><span class="p">,</span> <span class="n">r0</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">center</span><span class="p">,</span> <span class="n">radius</span><span class="p">))</span>
-    <span class="n">axes</span> <span class="o">=</span> <span class="s2">&quot;zyx&quot;</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">shape</span><span class="p">)</span> <span class="o">==</span> <span class="mi">3</span> <span class="k">else</span> <span class="kc">None</span> <span class="c1"># change the default axes in `array`</span>
-    
-    <span class="k">return</span> <span class="n">array</span><span class="p">(</span><span class="n">s</span> <span class="o">&gt;</span> <span class="mf">1.0</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">bool</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">)</span></div>
+    <span class="n">s</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(((</span><span class="n">x0</span> <span class="o">-</span> <span class="n">c0</span><span class="p">)</span> <span class="o">/</span> <span class="n">r0</span><span class="p">)</span> <span class="o">**</span> <span class="mi">2</span> <span class="k">for</span> <span class="n">x0</span><span class="p">,</span> <span class="n">c0</span><span class="p">,</span> <span class="n">r0</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">center</span><span class="p">,</span> <span class="n">radius</span><span class="p">))</span>
+    <span class="n">axes</span> <span class="o">=</span> <span class="s2">&quot;zyx&quot;</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">shape</span><span class="p">)</span> <span class="o">==</span> <span class="mi">3</span> <span class="k">else</span> <span class="kc">None</span>  <span class="c1"># change the default axes in `array`</span>
+    <span class="n">val</span> <span class="o">=</span> <span class="n">s</span> <span class="o">&gt;</span> <span class="mf">1.0</span>
+    <span class="k">if</span> <span class="n">soft</span><span class="p">:</span>
+        <span class="n">pix</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">/</span> <span class="n">radius</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
+        <span class="n">val</span> <span class="o">=</span> <span class="n">val</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span>
+        <span class="n">sl</span> <span class="o">=</span> <span class="p">(</span><span class="mf">1.0</span> <span class="o">&lt;</span> <span class="n">s</span><span class="p">)</span> <span class="o">&amp;</span> <span class="p">(</span><span class="n">s</span> <span class="o">&lt;=</span> <span class="mf">1.0</span> <span class="o">+</span> <span class="n">pix</span><span class="p">)</span>
+        <span class="n">val</span><span class="p">[</span><span class="n">sl</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">s</span><span class="p">[</span><span class="n">sl</span><span class="p">])</span> <span class="o">-</span> <span class="mf">1.0</span><span class="p">)</span> <span class="o">/</span> <span class="n">pix</span>
+        <span class="n">out</span> <span class="o">=</span> <span class="n">array</span><span class="p">(</span><span class="n">val</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">)</span>
+    <span class="k">else</span><span class="p">:</span>
+        <span class="n">out</span> <span class="o">=</span> <span class="n">array</span><span class="p">(</span><span class="n">val</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">bool</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">)</span>
+    <span class="k">if</span> <span class="ow">not</span> <span class="n">out_value</span><span class="p">:</span>
+        <span class="k">if</span> <span class="n">soft</span><span class="p">:</span>
+            <span class="n">out</span><span class="p">[:]</span> <span class="o">=</span> <span class="mf">1.0</span> <span class="o">-</span> <span class="n">out</span>
+        <span class="k">else</span><span class="p">:</span>
+            <span class="n">out</span><span class="p">[:]</span> <span class="o">=</span> <span class="o">~</span><span class="n">out</span>   
+    <span class="k">return</span> <span class="n">out</span></div>
 
 
 <div class="viewcode-block" id="sample_image"><a class="viewcode-back" href="../../apidoc/impy.html#impy.core.sample_image">[docs]</a><span class="k">def</span> <span class="nf">sample_image</span><span class="p">(</span><span class="n">name</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Get sample images from ``skimage`` and convert it into ImgArray.</span>
 
 <span class="sd">    Parameters</span>
@@ -579,7 +555,7 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="n">out</span></div>
 
 <div class="viewcode-block" id="broadcast_arrays"><a class="viewcode-back" href="../../apidoc/impy.html#impy.core.broadcast_arrays">[docs]</a><span class="k">def</span> <span class="nf">broadcast_arrays</span><span class="p">(</span><span class="o">*</span><span class="n">arrays</span><span class="p">:</span> <span class="n">MetaArray</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="n">MetaArray</span><span class="p">]:</span>
-    <span class="sd">&quot;&quot;&quot;Broadcast input arrays to the same shape and axes&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Broadcast input arrays to the same shape and axes&quot;&quot;&quot;</span>
     <span class="n">axes_list</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Axes</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
     <span class="n">shapes</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="p">{}</span>
     <span class="k">for</span> <span class="n">arr</span> <span class="ow">in</span> <span class="n">arrays</span><span class="p">:</span>
@@ -604,7 +580,7 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
     <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">squeeze</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Load image(s) from a path. You can read list of images from directories with </span>
 <span class="sd">    wildcards or ``&quot;$&quot;`` in ``path``.</span>
 
@@ -699,7 +675,7 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">sort_axes</span><span class="p">()</span><span class="o">.</span><span class="n">as_img_type</span><span class="p">(</span><span class="n">dtype</span><span class="p">)</span> <span class="c1"># arrange in tzcyx-order</span></div>
 
 <span class="k">def</span> <span class="nf">_imread_glob</span><span class="p">(</span><span class="n">path</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">squeeze</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Read images recursively from a directory, and stack them into one ImgArray.</span>
 
 <span class="sd">    Parameters</span>
@@ -738,7 +714,7 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
     <span class="n">key</span><span class="p">:</span> <span class="n">AxesTargetedSlicer</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">squeeze</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
 <span class="p">):</span>
-    <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Read separate image files using formated string. This function is useful when files/folders</span>
 <span class="sd">    are named in a certain rule, such as &quot;.../pos_0/img_0.tif&quot;, &quot;.../pos_0/img_1.tif&quot;.</span>
 
@@ -860,7 +836,7 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
     <span class="n">path</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">],</span> 
     <span class="n">filt</span><span class="p">:</span> <span class="n">Callable</span><span class="p">[[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">],</span> <span class="nb">bool</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">DataList</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Open images as ImgArray and store them in DataList.</span>
 
 <span class="sd">    Parameters</span>
@@ -896,108 +872,15 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="n">arrlist</span></div>
 
 
-<div class="viewcode-block" id="lazy_imread"><a class="viewcode-back" href="../../apidoc/impy.html#impy.core.lazy_imread">[docs]</a><span class="k">def</span> <span class="nf">lazy_imread</span><span class="p">(</span>
-    <span class="n">path</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> 
-    <span class="n">chunks</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span>
-    <span class="o">*</span><span class="p">,</span> 
-    <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-    <span class="n">squeeze</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
-<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
-<span class="sd">    Read an image lazily. Image file is first opened as an memory map, and subsequently converted</span>
-<span class="sd">    to `numpy.ndarray` or `cupy.ndarray` chunkwise by `dask.array.map_blocks`.</span>
+<div class="viewcode-block" id="lazy_imread"><a class="viewcode-back" href="../../apidoc/impy.html#impy.core.lazy_imread">[docs]</a><span class="k">def</span> <span class="nf">lazy_imread</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+    <span class="kn">from</span> <span class="nn">impy.lazy</span> <span class="kn">import</span> <span class="n">imread</span> <span class="k">as</span> <span class="n">lazy_imread_</span>
 
-<span class="sd">    Parameters</span>
-<span class="sd">    ----------</span>
-<span class="sd">    path : str</span>
-<span class="sd">        Path to the file.</span>
-<span class="sd">    chunks : optional</span>
-<span class="sd">        Specify chunk sizes. By default, yx-axes are assigned to the same chunk for every slice of</span>
-<span class="sd">        image, whild chunk sizes of the rest of axes are automatically set with &quot;auto&quot; option.</span>
-<span class="sd">    name : str, optional</span>
-<span class="sd">        Name of array.</span>
-<span class="sd">    squeeze : bool, default is False</span>
-<span class="sd">        If True and there is one-sized axis, then call `np.squeeze`.</span>
-<span class="sd">        </span>
-<span class="sd">    Returns</span>
-<span class="sd">    -------</span>
-<span class="sd">    LazyImgArray</span>
-<span class="sd">    &quot;&quot;&quot;</span>    
-    <span class="n">path</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">path</span><span class="p">)</span>
-    <span class="k">if</span> <span class="ow">not</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">exists</span><span class="p">(</span><span class="n">path</span><span class="p">):</span>
-        <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Path does not exist: </span><span class="si">{</span><span class="n">path</span><span class="si">}</span><span class="s2">.&quot;</span><span class="p">)</span>
-    
-    <span class="k">if</span> <span class="s2">&quot;*&quot;</span> <span class="ow">in</span> <span class="n">path</span><span class="p">:</span>
-        <span class="k">return</span> <span class="n">_lazy_imread_glob</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">,</span> <span class="n">squeeze</span><span class="o">=</span><span class="n">squeeze</span><span class="p">)</span>
-    
-    <span class="c1"># read as a dask array</span>
-    <span class="n">image_data</span> <span class="o">=</span> <span class="n">io</span><span class="o">.</span><span class="n">imread_dask</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">chunks</span><span class="p">)</span>
-    <span class="n">img</span> <span class="o">=</span> <span class="n">image_data</span><span class="o">.</span><span class="n">image</span>
-    <span class="n">axes</span> <span class="o">=</span> <span class="n">image_data</span><span class="o">.</span><span class="n">axes</span>
-    <span class="n">scale</span> <span class="o">=</span> <span class="n">image_data</span><span class="o">.</span><span class="n">scale</span>
-    <span class="n">spatial_scale_unit</span> <span class="o">=</span> <span class="n">image_data</span><span class="o">.</span><span class="n">unit</span>
-    <span class="n">metadata</span> <span class="o">=</span> <span class="n">image_data</span><span class="o">.</span><span class="n">metadata</span>
-    <span class="n">labels</span> <span class="o">=</span> <span class="n">image_data</span><span class="o">.</span><span class="n">labels</span>
-    
-    <span class="k">if</span> <span class="n">squeeze</span><span class="p">:</span>
-        <span class="n">axes</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">a</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">a</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">axes</span><span class="p">)</span> <span class="k">if</span> <span class="n">img</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">)</span>
-        <span class="n">img</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
-    
-    <span class="bp">self</span> <span class="o">=</span> <span class="n">LazyImgArray</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="n">path</span><span class="p">,</span> <span class="n">metadata</span><span class="o">=</span><span class="n">metadata</span><span class="p">)</span>
-
-    <span class="c1"># read scale if possible</span>
-    <span class="bp">self</span><span class="o">.</span><span class="n">set_scale</span><span class="p">(</span><span class="o">**</span><span class="n">scale</span><span class="p">)</span>
-    
-    
-    <span class="k">if</span> <span class="s2">&quot;c&quot;</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span> <span class="ow">and</span> <span class="n">labels</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">set_axis_label</span><span class="p">(</span><span class="n">c</span><span class="o">=</span><span class="n">labels</span><span class="p">)</span>
-    
-    <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">scale</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
-        <span class="k">if</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">:</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">set_scale</span><span class="p">({</span><span class="n">k</span><span class="p">:</span> <span class="n">v</span><span class="p">})</span>
-            <span class="k">if</span> <span class="n">k</span> <span class="ow">in</span> <span class="s2">&quot;zyx&quot;</span><span class="p">:</span>
-                <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">[</span><span class="n">k</span><span class="p">]</span><span class="o">.</span><span class="n">unit</span> <span class="o">=</span> <span class="n">spatial_scale_unit</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
-    
-    <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">sort_axes</span><span class="p">()</span></div>
-
-
-<span class="k">def</span> <span class="nf">_lazy_imread_glob</span><span class="p">(</span><span class="n">path</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">squeeze</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
-<span class="sd">    Read images recursively from a directory, and stack them into one LazyImgArray.</span>
+    <span class="n">warnings</span><span class="o">.</span><span class="n">warn</span><span class="p">(</span>
+        <span class="s2">&quot;impy.lazy_imread is deprecated. Please use `impy.lazy.imread`&quot;</span><span class="p">,</span> 
+        <span class="ne">DeprecationWarning</span>
+    <span class="p">)</span>
+    <span class="k">return</span> <span class="n">lazy_imread_</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div>
 
-<span class="sd">    Parameters</span>
-<span class="sd">    ----------</span>
-<span class="sd">    path : str</span>
-<span class="sd">        Path with wildcard.</span>
-<span class="sd">        </span>
-<span class="sd">    &quot;&quot;&quot;</span>    
-    <span class="n">path</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">path</span><span class="p">)</span>
-    <span class="n">paths</span> <span class="o">=</span> <span class="n">glob</span><span class="o">.</span><span class="n">glob</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">recursive</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-        
-    <span class="n">imgs</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">LazyImgArray</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
-    <span class="k">for</span> <span class="n">path</span> <span class="ow">in</span> <span class="n">paths</span><span class="p">:</span>
-        <span class="n">imgl</span> <span class="o">=</span> <span class="n">lazy_imread</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
-        <span class="n">imgs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">imgl</span><span class="p">)</span>
-    
-    <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">imgs</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
-        <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s2">&quot;Could not read any images.&quot;</span><span class="p">)</span>
-    
-    <span class="kn">from</span> <span class="nn">dask</span> <span class="kn">import</span> <span class="n">array</span> <span class="k">as</span> <span class="n">da</span>
-    <span class="n">out</span> <span class="o">=</span> <span class="n">da</span><span class="o">.</span><span class="n">stack</span><span class="p">([</span><span class="n">i</span><span class="o">.</span><span class="n">value</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">imgs</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
-    <span class="n">out</span> <span class="o">=</span> <span class="n">LazyImgArray</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>
-    <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="n">imgs</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">new_axes</span><span class="o">=</span><span class="s2">&quot;p&quot;</span><span class="o">+</span><span class="nb">str</span><span class="p">(</span><span class="n">imgs</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">axes</span><span class="p">))</span>
-    
-    <span class="k">if</span> <span class="n">squeeze</span><span class="p">:</span>
-        <span class="n">axes</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">a</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">a</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">out</span><span class="o">.</span><span class="n">axes</span><span class="p">)</span> <span class="k">if</span> <span class="n">out</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">)</span>
-        <span class="n">img</span> <span class="o">=</span> <span class="n">da</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="n">out</span><span class="o">.</span><span class="n">value</span><span class="p">)</span>
-        <span class="n">out</span> <span class="o">=</span> <span class="n">LazyImgArray</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
-        <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="n">imgs</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">new_axes</span><span class="o">=</span><span class="n">axes</span><span class="p">)</span>
-    <span class="k">try</span><span class="p">:</span>
-        <span class="n">out</span><span class="o">.</span><span class="n">source</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="n">path</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s2">&quot;*&quot;</span><span class="p">)[</span><span class="mi">0</span><span class="p">])[</span><span class="mi">0</span><span class="p">]</span>
-    <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span>
-        <span class="k">pass</span>
-    
-    <span class="k">return</span> <span class="n">out</span>
 
 <div class="viewcode-block" id="big_imread"><a class="viewcode-back" href="../../apidoc/impy.html#impy.core.big_imread">[docs]</a><span class="k">def</span> <span class="nf">big_imread</span><span class="p">(</span>
     <span class="n">path</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> 
@@ -1006,7 +889,7 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
     <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">squeeze</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">BigImgArray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Read an image lazily. Image file is first opened as an memory map, and subsequently converted</span>
 <span class="sd">    to `numpy.ndarray` or `cupy.ndarray` chunkwise by `dask.array.map_blocks`.</span>
 
@@ -1026,11 +909,13 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
 <span class="sd">    -------</span>
 <span class="sd">    BigImgArray</span>
 <span class="sd">    &quot;&quot;&quot;</span>
-    <span class="n">out</span> <span class="o">=</span> <span class="n">lazy_imread</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">squeeze</span><span class="o">=</span><span class="n">squeeze</span><span class="p">)</span>
+    <span class="kn">from</span> <span class="nn">impy.lazy</span> <span class="kn">import</span> <span class="n">imread</span> <span class="k">as</span> <span class="n">lazy_imread_</span>
+
+    <span class="n">out</span> <span class="o">=</span> <span class="n">lazy_imread_</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">squeeze</span><span class="o">=</span><span class="n">squeeze</span><span class="p">)</span>
     <span class="k">return</span> <span class="n">BigImgArray</span><span class="p">(</span><span class="n">out</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">out</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="n">out</span><span class="o">.</span><span class="n">axes</span><span class="p">,</span> <span class="n">out</span><span class="o">.</span><span class="n">source</span><span class="p">,</span> <span class="n">out</span><span class="o">.</span><span class="n">metadata</span><span class="p">)</span></div>
 
 <div class="viewcode-block" id="read_meta"><a class="viewcode-back" href="../../apidoc/impy.html#impy.core.read_meta">[docs]</a><span class="k">def</span> <span class="nf">read_meta</span><span class="p">(</span><span class="n">path</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Read the metadata of an image file. </span>
 
 <span class="sd">    Parameters</span>
@@ -1052,7 +937,7 @@ <h1>Source code for impy.core</h1><div class="highlight"><pre>
     <span class="p">}</span></div>
 
 <div class="viewcode-block" id="roiread"><a class="viewcode-back" href="../../apidoc/impy.html#impy.core.roiread">[docs]</a><span class="k">def</span> <span class="nf">roiread</span><span class="p">(</span><span class="n">path</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">RoiList</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;Read a Roi.zip file as a RoiList object.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Read a Roi.zip file as a RoiList object.&quot;&quot;&quot;</span>
     <span class="kn">from</span> <span class="nn">.roi</span> <span class="kn">import</span> <span class="n">RoiList</span>
     
     <span class="k">return</span> <span class="n">RoiList</span><span class="o">.</span><span class="n">fromfile</span><span class="p">(</span><span class="n">path</span><span class="p">)</span></div>
diff --git a/docs/_modules/impy/correlation.html b/docs/_modules/impy/correlation.html
index 32c009a8..26501788 100644
--- a/docs/_modules/impy/correlation.html
+++ b/docs/_modules/impy/correlation.html
@@ -3,7 +3,7 @@
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.correlation &mdash; impy 2.2.0 documentation</title>
+  <title>impy.correlation &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -11,9 +11,8 @@
   <![endif]-->
   
         <script data-url_root="../../" id="documentation_options" src="../../_static/documentation_options.js"></script>
-        <script src="../../_static/jquery.js"></script>
-        <script src="../../_static/underscore.js"></script>
         <script src="../../_static/doctools.js"></script>
+        <script src="../../_static/sphinx_highlight.js"></script>
     <script src="../../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../../genindex.html" />
     <link rel="search" title="Search" href="../../search.html" /> 
@@ -24,14 +23,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -58,9 +61,9 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../index.html">Module code</a> &raquo;</li>
-      <li>impy.correlation</li>
+      <li><a href="../../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../index.html">Module code</a></li>
+      <li class="breadcrumb-item active">impy.correlation</li>
       <li class="wy-breadcrumbs-aside">
       </li>
   </ul>
@@ -73,7 +76,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
 <span></span><span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="n">annotations</span>
 <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
 <span class="kn">from</span> <span class="nn">warnings</span> <span class="kn">import</span> <span class="n">warn</span>
-<span class="kn">from</span> <span class="nn">.core</span> <span class="kn">import</span> <span class="n">asarray</span> <span class="k">as</span> <span class="n">ip_asarray</span>
+<span class="kn">from</span> <span class="nn">.core</span> <span class="kn">import</span> <span class="n">asarray</span> <span class="k">as</span> <span class="n">ip_asarray</span><span class="p">,</span> <span class="n">circular_mask</span>
 <span class="kn">from</span> <span class="nn">.arrays</span> <span class="kn">import</span> <span class="n">ImgArray</span><span class="p">,</span> <span class="n">PropArray</span>
 <span class="kn">from</span> <span class="nn">.arrays._utils</span> <span class="kn">import</span> <span class="n">_docs</span>
 <span class="kn">from</span> <span class="nn">.arrays._utils._transform</span> <span class="kn">import</span> <span class="n">polar2d</span>
@@ -112,7 +115,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="n">img1</span><span class="p">:</span> <span class="n">ImgArray</span><span class="p">,</span> 
     <span class="n">dfreq</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.02</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">]:</span>
-    <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Calculate Fourier Shell Correlation (FSC; or Fourier Ring Correlation, FRC, for 2-D images) </span>
 <span class="sd">    between two images. FSC is defined as:</span>
 <span class="sd">    </span>
@@ -224,7 +227,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="o">*</span><span class="p">,</span> 
     <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PropArray</span> <span class="o">|</span> <span class="nb">float</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Normalized Cross Correlation.</span>
 <span class="sd">    </span>
 <span class="sd">    Parameters</span>
@@ -260,7 +263,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="o">*</span><span class="p">,</span>
     <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PropArray</span> <span class="o">|</span> <span class="nb">float</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Zero-mean Normalized Cross Correlation.</span>
 <span class="sd">    </span>
 <span class="sd">    Parameters</span>
@@ -305,7 +308,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="o">*</span><span class="p">,</span> 
     <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PropArray</span> <span class="o">|</span> <span class="nb">float</span><span class="p">:</span>
-    <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Normalized Mutual Information.</span>
 <span class="sd">    </span>
 <span class="sd">    :math:`Y(A, B) = \frac{H(A) + H(B)}{H(A, B)}`</span>
@@ -356,7 +359,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="o">*</span><span class="p">,</span> 
     <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PropArray</span> <span class="o">|</span> <span class="nb">float</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Normalized Cross Correlation in Fourier space.</span>
 <span class="sd">    </span>
 <span class="sd">    Parameters</span>
@@ -394,7 +397,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="o">*</span><span class="p">,</span> 
     <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PropArray</span> <span class="o">|</span> <span class="nb">float</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Zero-mean Normalized Cross Correlation in Fourier space.</span>
 <span class="sd">    </span>
 <span class="sd">    Parameters</span>
@@ -436,7 +439,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="n">upsample_factor</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span>
     <span class="n">max_shifts</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Calculate lateral shift between two images using phase cross correlation.</span>
 <span class="sd">    </span>
 <span class="sd">    Same as ``skimage.registration.phase_cross_correlation`` but some additional parameters </span>
@@ -466,7 +469,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="n">upsample_factor</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span>
     <span class="n">max_shifts</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Calculate lateral shift between two images using phase cross correlation.</span>
 <span class="sd">    </span>
 <span class="sd">    Same as ``skimage.registration.phase_cross_correlation`` but some additional parameters </span>
@@ -511,7 +514,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="n">upsample_factor</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span>
     <span class="n">max_shifts</span><span class="p">:</span> <span class="nb">float</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Calculate lateral shift between two images using phase cross correlation.</span>
 <span class="sd">    </span>
 <span class="sd">    This function takes Fourier transformed images as input. If you have to repetitively</span>
@@ -541,7 +544,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="n">upsample_factor</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span>
     <span class="n">max_shifts</span><span class="p">:</span> <span class="nb">float</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Calculate lateral shift between two images using phase cross correlation.</span>
 <span class="sd">    </span>
 <span class="sd">    This function takes Fourier transformed images as input. If you have to repetitively</span>
@@ -581,7 +584,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="n">img1</span><span class="p">:</span> <span class="n">ImgArray</span><span class="p">,</span>
     <span class="n">max_shifts</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Create landscape of phase cross correlation.</span>
 
 <span class="sd">    Parameters</span>
@@ -615,7 +618,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="n">img1</span><span class="p">:</span> <span class="n">ImgArray</span><span class="p">,</span>
     <span class="n">max_shifts</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Create landscape of phase cross correlation.</span>
 
 <span class="sd">    This function takes Fourier transformed images as input. If you have to repetitively</span>
@@ -651,7 +654,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="n">upsample_factor</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span>
     <span class="n">max_degree</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Calculate rotational shift between two images using polar Fourier transformation.</span>
 
 <span class="sd">    Parameters</span>
@@ -676,7 +679,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="n">upsample_factor</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span>
     <span class="n">max_degree</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Calculate rotational shift between two images using polar Fourier transformation.</span>
 
 <span class="sd">    Parameters</span>
@@ -692,20 +695,83 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
 <span class="sd">    float and float</span>
 <span class="sd">        Rotation in degree and phase cross correlation</span>
 <span class="sd">    &quot;&quot;&quot;</span>    
+    <span class="k">return</span> <span class="n">_polar_corr</span><span class="p">(</span><span class="n">pcc_maximum_with_corr</span><span class="p">,</span> <span class="n">img0</span><span class="p">,</span> <span class="n">img1</span><span class="p">,</span> <span class="n">upsample_factor</span><span class="p">,</span> <span class="n">max_degree</span><span class="p">)</span></div>
+
+
+<span class="nd">@_docs</span><span class="o">.</span><span class="n">write_docs</span>
+<span class="k">def</span> <span class="nf">polar_zncc_maximum</span><span class="p">(</span>
+    <span class="n">img0</span><span class="p">:</span> <span class="n">ImgArray</span><span class="p">,</span>
+    <span class="n">img1</span><span class="p">:</span> <span class="n">ImgArray</span><span class="p">,</span>
+    <span class="n">upsample_factor</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span>
+    <span class="n">max_degree</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+<span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Calculate rotational shift between two images using polar Fourier transformation.</span>
+
+<span class="sd">    Parameters</span>
+<span class="sd">    ----------</span>
+<span class="sd">    {inputs_of_correlation}</span>
+<span class="sd">    upsample_factor : int, default is 10</span>
+<span class="sd">        Up-sampling factor when calculating phase cross correlation.</span>
+<span class="sd">    max_degree : int, tuple of int, optional</span>
+<span class="sd">        Maximum rotation in degree.</span>
+
+<span class="sd">    Returns</span>
+<span class="sd">    -------</span>
+<span class="sd">    float</span>
+<span class="sd">        Rotation in degree</span>
+<span class="sd">    &quot;&quot;&quot;</span>    
+    <span class="k">return</span> <span class="n">polar_zncc_maximum_with_corr</span><span class="p">(</span><span class="n">img0</span><span class="p">,</span> <span class="n">img1</span><span class="p">,</span> <span class="n">upsample_factor</span><span class="p">,</span> <span class="n">max_degree</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
+
+<span class="nd">@_docs</span><span class="o">.</span><span class="n">write_docs</span>
+<span class="k">def</span> <span class="nf">polar_zncc_maximum_with_corr</span><span class="p">(</span>
+    <span class="n">img0</span><span class="p">:</span> <span class="n">ImgArray</span><span class="p">,</span>
+    <span class="n">img1</span><span class="p">:</span> <span class="n">ImgArray</span><span class="p">,</span>
+    <span class="n">upsample_factor</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span>
+    <span class="n">max_degree</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+<span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Calculate rotational shift between two images using polar Fourier transformation.</span>
+
+<span class="sd">    Parameters</span>
+<span class="sd">    ----------</span>
+<span class="sd">    {inputs_of_correlation}</span>
+<span class="sd">    upsample_factor : int, default is 10</span>
+<span class="sd">        Up-sampling factor when calculating phase cross correlation.</span>
+<span class="sd">    max_degree : int, tuple of int, optional</span>
+<span class="sd">        Maximum rotation in degree.</span>
+
+<span class="sd">    Returns</span>
+<span class="sd">    -------</span>
+<span class="sd">    float and float</span>
+<span class="sd">        Rotation in degree and phase cross correlation</span>
+<span class="sd">    &quot;&quot;&quot;</span>    
+    <span class="k">return</span> <span class="n">_polar_corr</span><span class="p">(</span><span class="n">zncc_maximum_with_corr</span><span class="p">,</span> <span class="n">img0</span><span class="p">,</span> <span class="n">img1</span><span class="p">,</span> <span class="n">upsample_factor</span><span class="p">,</span> <span class="n">max_degree</span><span class="p">)</span>
+
+
+<span class="k">def</span> <span class="nf">_polar_corr</span><span class="p">(</span>
+    <span class="n">corr_fn</span><span class="p">,</span>
+    <span class="n">img0</span><span class="p">:</span> <span class="n">ImgArray</span><span class="p">,</span>
+    <span class="n">img1</span><span class="p">:</span> <span class="n">ImgArray</span><span class="p">,</span>
+    <span class="n">upsample_factor</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span>
+    <span class="n">max_degree</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+<span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Calculate rotational shift between two images using polar Fourier transformation.&quot;&quot;&quot;</span>    
     <span class="n">img0</span><span class="p">,</span> <span class="n">img1</span> <span class="o">=</span> <span class="n">_check_inputs</span><span class="p">(</span><span class="n">img0</span><span class="p">,</span> <span class="n">img1</span><span class="p">)</span>
     <span class="k">if</span> <span class="n">img0</span><span class="o">.</span><span class="n">ndim</span> <span class="o">!=</span> <span class="mi">2</span><span class="p">:</span>
         <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s2">&quot;Currently only 2D image is supported.&quot;</span><span class="p">)</span>
     <span class="k">if</span> <span class="n">max_degree</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
         <span class="n">max_degree</span> <span class="o">=</span> <span class="mi">180</span>
-    <span class="n">rmax</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">img0</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
-    <span class="n">imgp</span> <span class="o">=</span> <span class="n">ip_asarray</span><span class="p">(</span><span class="n">xp</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">(</span><span class="n">polar2d</span><span class="p">(</span><span class="n">img0</span><span class="p">,</span> <span class="n">rmax</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="o">/</span><span class="mi">180</span><span class="p">)))</span>
-    <span class="n">imgrotp</span> <span class="o">=</span> <span class="n">ip_asarray</span><span class="p">(</span><span class="n">xp</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">(</span><span class="n">polar2d</span><span class="p">(</span><span class="n">img1</span><span class="p">,</span> <span class="n">rmax</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="o">/</span><span class="mi">180</span><span class="p">)))</span>
+    <span class="n">rmax</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">img0</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span> <span class="o">//</span> <span class="mi">2</span>
+    <span class="n">mask</span> <span class="o">=</span> <span class="n">circular_mask</span><span class="p">(</span><span class="n">rmax</span><span class="p">,</span> <span class="n">img0</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">soft</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">out_value</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
+    <span class="n">imgp</span> <span class="o">=</span> <span class="n">ip_asarray</span><span class="p">(</span><span class="n">xp</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">(</span><span class="n">polar2d</span><span class="p">(</span><span class="n">img0</span> <span class="o">*</span> <span class="n">mask</span><span class="p">,</span> <span class="n">rmax</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="o">/</span><span class="mi">180</span><span class="p">)))</span>
+    <span class="n">imgrotp</span> <span class="o">=</span> <span class="n">ip_asarray</span><span class="p">(</span><span class="n">xp</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">(</span><span class="n">polar2d</span><span class="p">(</span><span class="n">img1</span> <span class="o">*</span> <span class="n">mask</span><span class="p">,</span> <span class="n">rmax</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="o">/</span><span class="mi">180</span><span class="p">)))</span>
     <span class="n">max_shifts</span> <span class="o">=</span> <span class="p">(</span><span class="n">max_degree</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
-    <span class="n">shift</span><span class="p">,</span> <span class="n">pcc</span> <span class="o">=</span> <span class="n">pcc_maximum_with_corr</span><span class="p">(</span>
+    <span class="n">shift</span><span class="p">,</span> <span class="n">pcc</span> <span class="o">=</span> <span class="n">corr_fn</span><span class="p">(</span>
         <span class="n">imgp</span><span class="p">,</span> <span class="n">imgrotp</span><span class="p">,</span> <span class="n">upsample_factor</span><span class="o">=</span><span class="n">upsample_factor</span><span class="p">,</span> <span class="n">max_shifts</span><span class="o">=</span><span class="n">max_shifts</span>
     <span class="p">)</span>
     <span class="c1"># Here, `shift` satisfies `img0.rotate(-shift[0]) == img1`</span>
-    <span class="k">return</span> <span class="n">shift</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">pcc</span></div>
+    <span class="k">return</span> <span class="n">shift</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">pcc</span>
 
 <div class="viewcode-block" id="zncc_maximum"><a class="viewcode-back" href="../../apidoc/impy.html#impy.correlation.zncc_maximum">[docs]</a><span class="nd">@_docs</span><span class="o">.</span><span class="n">write_docs</span>
 <span class="k">def</span> <span class="nf">zncc_maximum</span><span class="p">(</span>
@@ -714,7 +780,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="n">upsample_factor</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span>
     <span class="n">max_shifts</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Calculate lateral shift between two images using zero-mean normalized cross correlation.</span>
 <span class="sd">    </span>
 <span class="sd">    Similar to :func:`pcc_maximum`, this function can determine shift at sub-pixel precision.</span>
@@ -744,7 +810,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="n">upsample_factor</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span>
     <span class="n">max_shifts</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="nb">float</span><span class="p">]:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Calculate lateral shift between two images using zero-mean normalized cross correlation.</span>
 <span class="sd">    </span>
 <span class="sd">    Similar to :func:`pcc_maximum`, this function can determine shift at sub-pixel precision.</span>
@@ -785,7 +851,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="n">img1</span><span class="p">:</span> <span class="n">ImgArray</span><span class="p">,</span>
     <span class="n">max_shifts</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Create landscape of zero-mean normalized cross correlation.</span>
 
 <span class="sd">    Parameters</span>
@@ -821,7 +887,7 @@ <h1>Source code for impy.correlation</h1><div class="highlight"><pre>
     <span class="n">squeeze</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
     <span class="n">dims</span><span class="p">:</span> <span class="n">Dims</span> <span class="o">=</span> <span class="kc">None</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">PropArray</span> <span class="o">|</span> <span class="nb">float</span><span class="p">:</span>
-    <span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sa">r</span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Manders&#39; correlation coefficient. This is defined as following:</span>
 <span class="sd">    </span>
 <span class="sd">    :math:`r = \frac{\sum_{i \in I_{ref}} I_i}{\sum_{i} I_i}`</span>
diff --git a/docs/_modules/impy/lazy/core.html b/docs/_modules/impy/lazy/core.html
new file mode 100644
index 00000000..2ab6272e
--- /dev/null
+++ b/docs/_modules/impy/lazy/core.html
@@ -0,0 +1,437 @@
+<!DOCTYPE html>
+<html class="writer-html5" lang="en" >
+<head>
+  <meta charset="utf-8" />
+  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+  <title>impy.lazy.core &mdash; impy 2.3.0 documentation</title>
+      <link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
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+          <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article">
+           <div itemprop="articleBody">
+             
+  <h1>Source code for impy.lazy.core</h1><div class="highlight"><pre>
+<span></span><span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="n">annotations</span>
+
+<span class="kn">import</span> <span class="nn">os</span>
+<span class="kn">import</span> <span class="nn">sys</span>
+<span class="kn">import</span> <span class="nn">re</span>
+<span class="kn">import</span> <span class="nn">glob</span>
+<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">TYPE_CHECKING</span><span class="p">,</span> <span class="n">Any</span><span class="p">,</span> <span class="n">Callable</span><span class="p">,</span> <span class="n">Sequence</span>
+<span class="kn">from</span> <span class="nn">typing_extensions</span> <span class="kn">import</span> <span class="n">ParamSpec</span>
+<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="kn">from</span> <span class="nn">functools</span> <span class="kn">import</span> <span class="n">wraps</span>
+
+<span class="kn">from</span> <span class="nn">impy</span> <span class="kn">import</span> <span class="n">io</span>
+<span class="kn">from</span> <span class="nn">impy.axes</span> <span class="kn">import</span> <span class="n">AxesLike</span><span class="p">,</span> <span class="n">AxesTuple</span>
+<span class="kn">from</span> <span class="nn">impy.arrays.bases</span> <span class="kn">import</span> <span class="n">MetaArray</span>
+<span class="kn">from</span> <span class="nn">impy.arrays</span> <span class="kn">import</span> <span class="n">LazyImgArray</span>
+
+<span class="k">if</span> <span class="n">TYPE_CHECKING</span><span class="p">:</span>
+    <span class="kn">from</span> <span class="nn">numpy.typing</span> <span class="kn">import</span> <span class="n">ArrayLike</span><span class="p">,</span> <span class="n">DTypeLike</span>
+    <span class="c1"># NOTE: &quot;_ShapeLike&quot; is not a public type in numpy.typing.</span>
+    <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">SupportsIndex</span><span class="p">,</span> <span class="n">Union</span>
+    <span class="n">ShapeLike</span> <span class="o">=</span> <span class="n">Union</span><span class="p">[</span><span class="n">SupportsIndex</span><span class="p">,</span> <span class="n">Sequence</span><span class="p">[</span><span class="n">SupportsIndex</span><span class="p">]]</span>
+
+<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span>
+    <span class="s2">&quot;array&quot;</span><span class="p">,</span>
+    <span class="s2">&quot;asarray&quot;</span><span class="p">,</span>
+    <span class="s2">&quot;zeros&quot;</span><span class="p">,</span>
+    <span class="s2">&quot;empty&quot;</span><span class="p">,</span>
+    <span class="s2">&quot;ones&quot;</span><span class="p">,</span>
+    <span class="s2">&quot;full&quot;</span><span class="p">,</span>
+    <span class="s2">&quot;arange&quot;</span><span class="p">,</span>
+    <span class="s2">&quot;indices&quot;</span><span class="p">,</span>
+    <span class="s2">&quot;imread&quot;</span><span class="p">,</span>
+<span class="p">]</span>
+
+<span class="n">_P</span> <span class="o">=</span> <span class="n">ParamSpec</span><span class="p">(</span><span class="s2">&quot;_P&quot;</span><span class="p">)</span>
+
+<span class="n">shared_docs</span> <span class="o">=</span> \
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    dtype : data type, optional</span>
+<span class="sd">        Image data type.</span>
+<span class="sd">    name : str, optional</span>
+<span class="sd">        Name of image.</span>
+<span class="sd">    axes : str, optional</span>
+<span class="sd">        Image axes.</span>
+<span class="sd">    &quot;&quot;&quot;</span>    
+    
+<span class="k">def</span> <span class="nf">_write_docs</span><span class="p">(</span><span class="n">func</span><span class="p">):</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Add doc for numpy function.&quot;&quot;&quot;</span>
+    <span class="n">func</span><span class="o">.</span><span class="vm">__doc__</span> <span class="o">=</span> <span class="n">re</span><span class="o">.</span><span class="n">sub</span><span class="p">(</span><span class="sa">r</span><span class="s2">&quot;</span><span class="si">{}</span><span class="s2">&quot;</span><span class="p">,</span> <span class="n">shared_docs</span><span class="p">,</span> <span class="n">func</span><span class="o">.</span><span class="vm">__doc__</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">func</span>
+
+<span class="k">def</span> <span class="nf">_inject_numpy_function</span><span class="p">(</span><span class="n">func</span><span class="p">:</span> <span class="n">Callable</span><span class="p">[</span><span class="n">_P</span><span class="p">,</span> <span class="n">Any</span> <span class="o">|</span> <span class="kc">None</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="n">Callable</span><span class="p">[</span><span class="n">_P</span><span class="p">,</span> <span class="n">LazyImgArray</span><span class="p">]:</span>
+    <span class="kn">from</span> <span class="nn">dask</span> <span class="kn">import</span> <span class="n">array</span> <span class="k">as</span> <span class="n">da</span>
+
+    <span class="n">dafunc</span><span class="p">:</span> <span class="n">Callable</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">da</span><span class="p">,</span> <span class="n">func</span><span class="o">.</span><span class="vm">__name__</span><span class="p">)</span>
+    <span class="nd">@wraps</span><span class="p">(</span><span class="n">func</span><span class="p">)</span>
+    <span class="k">def</span> <span class="nf">_func</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+        <span class="n">like</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s2">&quot;like&quot;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
+        <span class="n">axes</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s2">&quot;axes&quot;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
+        <span class="n">name</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s2">&quot;name&quot;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
+        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">dafunc</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">),</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="o">=</span><span class="n">like</span><span class="p">)</span>
+    
+    <span class="n">_func</span><span class="o">.</span><span class="vm">__doc__</span> <span class="o">=</span> <span class="p">(</span>
+        <span class="sa">f</span><span class="s2">&quot;&quot;&quot;</span>
+<span class="s2">        impy.lazy version of numpy.</span><span class="si">{</span><span class="n">func</span><span class="o">.</span><span class="vm">__name__</span><span class="si">}</span><span class="s2">. This function has additional parameters </span>
+<span class="s2">        ``axes`` and ``name``. Original docstring follows.</span>
+<span class="s2">        </span>
+<span class="s2">        Additional Parameters</span>
+<span class="s2">        ---------------------</span>
+<span class="s2">        axes : str, optional</span>
+<span class="s2">            Image axes. Must be same length as image dimension.</span>
+<span class="s2">        name: str, optional</span>
+<span class="s2">            Image name.</span>
+<span class="s2">        like: MetaArray, optional</span>
+<span class="s2">            Reference array from which name and axes will be copied.</span>
+
+<span class="s2">        </span><span class="si">{</span><span class="n">dafunc</span><span class="o">.</span><span class="vm">__doc__</span><span class="si">}</span>
+<span class="s2">        &quot;&quot;&quot;</span>
+        <span class="p">)</span>
+    <span class="n">_func</span><span class="o">.</span><span class="vm">__annotations__</span><span class="o">.</span><span class="n">update</span><span class="p">({</span><span class="s2">&quot;return&quot;</span><span class="p">:</span> <span class="n">LazyImgArray</span><span class="p">})</span>
+    <span class="k">return</span> <span class="n">_func</span>
+
+<div class="viewcode-block" id="zeros"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.core.zeros">[docs]</a><span class="nd">@_inject_numpy_function</span>
+<span class="k">def</span> <span class="nf">zeros</span><span class="p">(</span><span class="n">shape</span><span class="p">:</span> <span class="n">ShapeLike</span><span class="p">,</span> <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">uint16</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span> <span class="o">...</span></div>
+    
+<div class="viewcode-block" id="empty"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.core.empty">[docs]</a><span class="nd">@_inject_numpy_function</span>
+<span class="k">def</span> <span class="nf">empty</span><span class="p">(</span><span class="n">shape</span><span class="p">:</span> <span class="n">ShapeLike</span><span class="p">,</span> <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">uint16</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span> <span class="o">...</span></div>
+
+<div class="viewcode-block" id="ones"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.core.ones">[docs]</a><span class="nd">@_inject_numpy_function</span>
+<span class="k">def</span> <span class="nf">ones</span><span class="p">(</span><span class="n">shape</span><span class="p">:</span> <span class="n">ShapeLike</span><span class="p">,</span> <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">uint16</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span> <span class="o">...</span></div>
+
+<div class="viewcode-block" id="full"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.core.full">[docs]</a><span class="nd">@_inject_numpy_function</span>
+<span class="k">def</span> <span class="nf">full</span><span class="p">(</span><span class="n">shape</span><span class="p">:</span> <span class="n">ShapeLike</span><span class="p">,</span> <span class="n">fill_value</span><span class="p">:</span> <span class="n">Any</span><span class="p">,</span> <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">uint16</span><span class="p">,</span> <span class="o">*</span><span class="p">,</span> <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span> <span class="o">...</span></div>
+
+<div class="viewcode-block" id="arange"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.core.arange">[docs]</a><span class="nd">@_inject_numpy_function</span>
+<span class="k">def</span> <span class="nf">arange</span><span class="p">(</span><span class="n">stop</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span> <span class="o">...</span></div>
+
+<div class="viewcode-block" id="array"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.core.array">[docs]</a><span class="nd">@_write_docs</span>
+<span class="k">def</span> <span class="nf">array</span><span class="p">(</span>
+    <span class="n">arr</span><span class="p">:</span> <span class="n">ArrayLike</span><span class="p">,</span>
+    <span class="o">/</span><span class="p">,</span>
+    <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> 
+    <span class="o">*</span><span class="p">,</span>
+    <span class="n">copy</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
+    <span class="n">chunks</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span>
+    <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    make an LazyImgArray object, like ``np.array(x)``</span>
+<span class="sd">    </span>
+<span class="sd">    Parameters</span>
+<span class="sd">    ----------</span>
+<span class="sd">    arr : array-like</span>
+<span class="sd">        Base array.</span>
+<span class="sd">    copy : bool, default is True</span>
+<span class="sd">        If True, a copy of the original array is made.</span>
+<span class="sd">    {}</span>
+<span class="sd">        </span>
+<span class="sd">    Returns</span>
+<span class="sd">    -------</span>
+<span class="sd">    LazyImgArray</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="kn">from</span> <span class="nn">dask</span> <span class="kn">import</span> <span class="n">array</span> <span class="k">as</span> <span class="n">da</span>
+    <span class="kn">from</span> <span class="nn">dask.array.core</span> <span class="kn">import</span> <span class="n">Array</span> <span class="k">as</span> <span class="n">DaskArray</span>
+
+    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">MetaArray</span><span class="p">):</span>
+        <span class="n">arr</span> <span class="o">=</span> <span class="n">da</span><span class="o">.</span><span class="n">from_array</span><span class="p">(</span><span class="n">arr</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">)</span>
+    <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">memmap</span><span class="p">)):</span>
+        <span class="n">arr</span> <span class="o">=</span> <span class="n">da</span><span class="o">.</span><span class="n">from_array</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">)</span>
+    <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">LazyImgArray</span><span class="p">):</span>
+        <span class="n">arr</span> <span class="o">=</span> <span class="n">arr</span><span class="o">.</span><span class="n">value</span>
+    <span class="k">elif</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">DaskArray</span><span class="p">):</span>
+        <span class="n">arr</span> <span class="o">=</span> <span class="n">da</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="p">)</span>
+        
+    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)</span> <span class="ow">and</span> <span class="n">dtype</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+        <span class="k">if</span> <span class="n">arr</span><span class="o">.</span><span class="n">dtype</span> <span class="ow">in</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">uint16</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">):</span>
+            <span class="n">dtype</span> <span class="o">=</span> <span class="n">arr</span><span class="o">.</span><span class="n">dtype</span>
+        <span class="k">elif</span> <span class="n">arr</span><span class="o">.</span><span class="n">dtype</span><span class="o">.</span><span class="n">kind</span> <span class="o">==</span> <span class="s2">&quot;f&quot;</span><span class="p">:</span>
+            <span class="n">dtype</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">float32</span>
+        <span class="k">else</span><span class="p">:</span>
+            <span class="n">dtype</span> <span class="o">=</span> <span class="n">arr</span><span class="o">.</span><span class="n">dtype</span>
+        
+    <span class="n">axes</span><span class="p">,</span> <span class="n">name</span> <span class="o">=</span> <span class="n">_normalize_params</span><span class="p">(</span><span class="n">axes</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
+
+    <span class="c1"># Automatically determine axes</span>
+    <span class="k">if</span> <span class="n">axes</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+        <span class="n">axes</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;x&quot;</span><span class="p">,</span> <span class="s2">&quot;yx&quot;</span><span class="p">,</span> <span class="s2">&quot;tyx&quot;</span><span class="p">,</span> <span class="s2">&quot;tzyx&quot;</span><span class="p">,</span> <span class="s2">&quot;tzcyx&quot;</span><span class="p">,</span> <span class="s2">&quot;ptzcyx&quot;</span><span class="p">][</span><span class="n">arr</span><span class="o">.</span><span class="n">ndim</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
+    <span class="k">if</span> <span class="n">copy</span><span class="p">:</span>
+        <span class="n">arr</span> <span class="o">=</span> <span class="n">arr</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
+    <span class="bp">self</span> <span class="o">=</span> <span class="n">LazyImgArray</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">)</span>
+    
+    <span class="k">return</span> <span class="bp">self</span></div>
+
+<div class="viewcode-block" id="asarray"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.core.asarray">[docs]</a><span class="nd">@_write_docs</span>
+<span class="k">def</span> <span class="nf">asarray</span><span class="p">(</span>
+    <span class="n">arr</span><span class="p">:</span> <span class="n">ArrayLike</span><span class="p">,</span>
+    <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="o">*</span><span class="p">,</span> 
+    <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">chunks</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span>
+<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    make an LazyImgArray object, like ``np.asarray(x)``</span>
+<span class="sd">    </span>
+<span class="sd">    Parameters</span>
+<span class="sd">    ----------</span>
+<span class="sd">    arr : array-like</span>
+<span class="sd">        Base array.</span>
+<span class="sd">    {}</span>
+<span class="sd">    copy : bool, default is True</span>
+<span class="sd">        If True, a copy of the original array is made.</span>
+<span class="sd">        </span>
+<span class="sd">    Returns</span>
+<span class="sd">    -------</span>
+<span class="sd">    ImgArray</span>
+<span class="sd">    </span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="k">return</span> <span class="n">array</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">copy</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">,</span> <span class="n">like</span><span class="o">=</span><span class="n">like</span><span class="p">)</span></div>
+
+<div class="viewcode-block" id="indices"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.core.indices">[docs]</a><span class="k">def</span> <span class="nf">indices</span><span class="p">(</span>
+    <span class="n">dimensions</span><span class="p">:</span> <span class="n">ShapeLike</span><span class="p">,</span>
+    <span class="n">dtype</span><span class="p">:</span> <span class="n">DTypeLike</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">uint16</span><span class="p">,</span>
+    <span class="o">*</span><span class="p">,</span> 
+    <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">AxesTuple</span><span class="p">[</span><span class="n">LazyImgArray</span><span class="p">]:</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Copy of ``numpy.indices``.</span>
+<span class="sd">    </span>
+<span class="sd">    Parameters</span>
+<span class="sd">    ----------</span>
+<span class="sd">    dimensions : shape-like</span>
+<span class="sd">        The shape of the grid.</span>
+<span class="sd">    dtype : dtype, optional</span>
+<span class="sd">        Data type of the result.</span>
+<span class="sd">    name : str, optional</span>
+<span class="sd">        Name of the result arrays.</span>
+<span class="sd">    axes : AxesLike, optional</span>
+<span class="sd">        Axes of the result arrays.</span>
+<span class="sd">    like : MetaArray, optional</span>
+<span class="sd">        Reference array from which name and axes will be copied.</span>
+
+<span class="sd">    Returns</span>
+<span class="sd">    -------</span>
+<span class="sd">    tuple of LazyImgArray</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="kn">from</span> <span class="nn">dask</span> <span class="kn">import</span> <span class="n">array</span> <span class="k">as</span> <span class="n">da</span>
+    <span class="n">out</span> <span class="o">=</span> <span class="nb">tuple</span><span class="p">(</span>
+        <span class="n">asarray</span><span class="p">(</span><span class="n">ind</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="o">=</span><span class="n">like</span><span class="p">)</span> <span class="k">for</span> <span class="n">ind</span> <span class="ow">in</span> <span class="n">da</span><span class="o">.</span><span class="n">indices</span><span class="p">(</span><span class="n">dimensions</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">)</span>
+    <span class="p">)</span>
+    <span class="k">return</span> <span class="n">out</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">tuple</span><span class="p">(</span><span class="n">out</span><span class="p">)</span></div>
+
+<div class="viewcode-block" id="imread"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.core.imread">[docs]</a><span class="k">def</span> <span class="nf">imread</span><span class="p">(</span>
+    <span class="n">path</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> 
+    <span class="n">chunks</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span>
+    <span class="o">*</span><span class="p">,</span> 
+    <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">squeeze</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
+<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Read an image lazily. Image file is first opened as an memory map, and subsequently converted</span>
+<span class="sd">    to `numpy.ndarray` or `cupy.ndarray` chunkwise by `dask.array.map_blocks`.</span>
+
+<span class="sd">    Parameters</span>
+<span class="sd">    ----------</span>
+<span class="sd">    path : str</span>
+<span class="sd">        Path to the file.</span>
+<span class="sd">    chunks : optional</span>
+<span class="sd">        Specify chunk sizes. By default, yx-axes are assigned to the same chunk for every slice of</span>
+<span class="sd">        image, whild chunk sizes of the rest of axes are automatically set with &quot;auto&quot; option.</span>
+<span class="sd">    name : str, optional</span>
+<span class="sd">        Name of array.</span>
+<span class="sd">    squeeze : bool, default is False</span>
+<span class="sd">        If True and there is one-sized axis, then call `np.squeeze`.</span>
+<span class="sd">        </span>
+<span class="sd">    Returns</span>
+<span class="sd">    -------</span>
+<span class="sd">    LazyImgArray</span>
+<span class="sd">    &quot;&quot;&quot;</span>    
+    <span class="n">path</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">path</span><span class="p">)</span>
+    <span class="k">if</span> <span class="s2">&quot;*&quot;</span> <span class="ow">in</span> <span class="n">path</span><span class="p">:</span>
+        <span class="k">return</span> <span class="n">_imread_glob</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">,</span> <span class="n">squeeze</span><span class="o">=</span><span class="n">squeeze</span><span class="p">)</span>
+    <span class="k">if</span> <span class="ow">not</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">exists</span><span class="p">(</span><span class="n">path</span><span class="p">):</span>
+        <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Path does not exist: </span><span class="si">{</span><span class="n">path</span><span class="si">}</span><span class="s2">.&quot;</span><span class="p">)</span>
+    
+    <span class="c1"># read as a dask array</span>
+    <span class="n">image_data</span> <span class="o">=</span> <span class="n">io</span><span class="o">.</span><span class="n">imread_dask</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">chunks</span><span class="p">)</span>
+    <span class="n">img</span> <span class="o">=</span> <span class="n">image_data</span><span class="o">.</span><span class="n">image</span>
+    <span class="n">axes</span> <span class="o">=</span> <span class="n">image_data</span><span class="o">.</span><span class="n">axes</span>
+    <span class="n">scale</span> <span class="o">=</span> <span class="n">image_data</span><span class="o">.</span><span class="n">scale</span>
+    <span class="n">spatial_scale_unit</span> <span class="o">=</span> <span class="n">image_data</span><span class="o">.</span><span class="n">unit</span>
+    <span class="n">metadata</span> <span class="o">=</span> <span class="n">image_data</span><span class="o">.</span><span class="n">metadata</span>
+    <span class="n">labels</span> <span class="o">=</span> <span class="n">image_data</span><span class="o">.</span><span class="n">labels</span>
+    
+    <span class="k">if</span> <span class="n">squeeze</span><span class="p">:</span>
+        <span class="n">axes</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">a</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">a</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">axes</span><span class="p">)</span> <span class="k">if</span> <span class="n">img</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">)</span>
+        <span class="n">img</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
+    
+    <span class="bp">self</span> <span class="o">=</span> <span class="n">LazyImgArray</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="n">path</span><span class="p">,</span> <span class="n">metadata</span><span class="o">=</span><span class="n">metadata</span><span class="p">)</span>
+
+    <span class="c1"># read scale if possible</span>
+    <span class="bp">self</span><span class="o">.</span><span class="n">set_scale</span><span class="p">(</span><span class="o">**</span><span class="n">scale</span><span class="p">)</span>
+
+    <span class="k">if</span> <span class="s2">&quot;c&quot;</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span> <span class="ow">and</span> <span class="n">labels</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">set_axis_label</span><span class="p">(</span><span class="n">c</span><span class="o">=</span><span class="n">labels</span><span class="p">)</span>
+    
+    <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">scale</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
+        <span class="k">if</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">:</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">set_scale</span><span class="p">({</span><span class="n">k</span><span class="p">:</span> <span class="n">v</span><span class="p">})</span>
+            <span class="k">if</span> <span class="n">k</span> <span class="ow">in</span> <span class="s2">&quot;zyx&quot;</span><span class="p">:</span>
+                <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="p">[</span><span class="n">k</span><span class="p">]</span><span class="o">.</span><span class="n">unit</span> <span class="o">=</span> <span class="n">spatial_scale_unit</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
+    
+    <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">sort_axes</span><span class="p">()</span></div>
+
+
+<span class="k">def</span> <span class="nf">_imread_glob</span><span class="p">(</span><span class="n">path</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">squeeze</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Read images recursively from a directory, and stack them into one LazyImgArray.</span>
+
+<span class="sd">    Parameters</span>
+<span class="sd">    ----------</span>
+<span class="sd">    path : str</span>
+<span class="sd">        Path with wildcard.</span>
+<span class="sd">        </span>
+<span class="sd">    &quot;&quot;&quot;</span>    
+    <span class="n">path</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">path</span><span class="p">)</span>
+    <span class="n">paths</span> <span class="o">=</span> <span class="n">glob</span><span class="o">.</span><span class="n">glob</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">recursive</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+        
+    <span class="n">imgs</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">LazyImgArray</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
+    <span class="k">for</span> <span class="n">path</span> <span class="ow">in</span> <span class="n">paths</span><span class="p">:</span>
+        <span class="n">imgl</span> <span class="o">=</span> <span class="n">imread</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
+        <span class="n">imgs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">imgl</span><span class="p">)</span>
+    
+    <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">imgs</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
+        <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s2">&quot;Could not read any images.&quot;</span><span class="p">)</span>
+    
+    <span class="kn">from</span> <span class="nn">dask</span> <span class="kn">import</span> <span class="n">array</span> <span class="k">as</span> <span class="n">da</span>
+    <span class="n">out</span> <span class="o">=</span> <span class="n">da</span><span class="o">.</span><span class="n">stack</span><span class="p">([</span><span class="n">i</span><span class="o">.</span><span class="n">value</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">imgs</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
+    <span class="n">out</span> <span class="o">=</span> <span class="n">LazyImgArray</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>
+    <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="n">imgs</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">new_axes</span><span class="o">=</span><span class="s2">&quot;p&quot;</span><span class="o">+</span><span class="nb">str</span><span class="p">(</span><span class="n">imgs</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">axes</span><span class="p">))</span>
+    
+    <span class="k">if</span> <span class="n">squeeze</span><span class="p">:</span>
+        <span class="n">axes</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">a</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">a</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">out</span><span class="o">.</span><span class="n">axes</span><span class="p">)</span> <span class="k">if</span> <span class="n">out</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">)</span>
+        <span class="n">img</span> <span class="o">=</span> <span class="n">da</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="n">out</span><span class="o">.</span><span class="n">value</span><span class="p">)</span>
+        <span class="n">out</span> <span class="o">=</span> <span class="n">LazyImgArray</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
+        <span class="n">out</span><span class="o">.</span><span class="n">_set_info</span><span class="p">(</span><span class="n">imgs</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">new_axes</span><span class="o">=</span><span class="n">axes</span><span class="p">)</span>
+    <span class="k">try</span><span class="p">:</span>
+        <span class="n">out</span><span class="o">.</span><span class="n">source</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="n">path</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s2">&quot;*&quot;</span><span class="p">)[</span><span class="mi">0</span><span class="p">])[</span><span class="mi">0</span><span class="p">]</span>
+    <span class="k">except</span> <span class="ne">Exception</span><span class="p">:</span>
+        <span class="k">pass</span>
+    
+    <span class="k">return</span> <span class="n">out</span>
+
+<span class="k">def</span> <span class="nf">_normalize_params</span><span class="p">(</span>
+    <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span>
+<span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span><span class="p">,</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span><span class="p">]:</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Normalize input parameters for MetaArray construction.&quot;&quot;&quot;</span>
+    <span class="k">if</span> <span class="n">like</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
+        <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">like</span><span class="p">,</span> <span class="p">(</span><span class="n">MetaArray</span><span class="p">,</span> <span class="n">LazyImgArray</span><span class="p">)):</span>
+            <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span>
+                <span class="sa">f</span><span class="s2">&quot;&#39;like&#39; must be a MetaArray or a LazyImgArray, not </span><span class="si">{</span><span class="nb">type</span><span class="p">(</span><span class="n">like</span><span class="p">)</span><span class="si">}</span><span class="s2">&quot;</span>
+            <span class="p">)</span>
+        <span class="n">name</span> <span class="o">=</span> <span class="n">name</span> <span class="ow">or</span> <span class="n">like</span><span class="o">.</span><span class="n">name</span>
+        <span class="n">axes</span> <span class="o">=</span> <span class="n">axes</span> <span class="ow">or</span> <span class="n">like</span><span class="o">.</span><span class="n">axes</span>
+    <span class="k">return</span> <span class="n">axes</span><span class="p">,</span> <span class="n">name</span>
+</pre></div>
+
+           </div>
+          </div>
+          <footer>
+
+  <hr/>
+
+  <div role="contentinfo">
+    <p>&#169; Copyright 2021, Hanjin Liu.</p>
+  </div>
+
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+    provided by <a href="https://readthedocs.org">Read the Docs</a>.
+   
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diff --git a/docs/_modules/impy/lazy/random.html b/docs/_modules/impy/lazy/random.html
new file mode 100644
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--- /dev/null
+++ b/docs/_modules/impy/lazy/random.html
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+<!DOCTYPE html>
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+  <h1>Source code for impy.lazy.random</h1><div class="highlight"><pre>
+<span></span><span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="n">annotations</span>
+<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Literal</span>
+<span class="kn">from</span> <span class="nn">dask</span> <span class="kn">import</span> <span class="n">array</span> <span class="k">as</span> <span class="n">da</span>
+<span class="kn">from</span> <span class="nn">impy.arrays</span> <span class="kn">import</span> <span class="n">LazyImgArray</span>
+<span class="kn">from</span> <span class="nn">impy.arrays.bases</span> <span class="kn">import</span> <span class="n">MetaArray</span>
+<span class="kn">from</span> <span class="nn">impy.lazy.core</span> <span class="kn">import</span> <span class="n">asarray</span>
+<span class="kn">from</span> <span class="nn">impy.axes</span> <span class="kn">import</span> <span class="n">AxesLike</span>
+
+<span class="k">def</span> <span class="nf">wraps</span><span class="p">(</span><span class="n">npfunc</span><span class="p">):</span>
+    <span class="k">def</span> <span class="nf">_wraps</span><span class="p">(</span><span class="n">ipfunc</span><span class="p">):</span>
+        <span class="n">ipfunc</span><span class="o">.</span><span class="vm">__doc__</span> <span class="o">=</span> <span class="n">npfunc</span><span class="o">.</span><span class="vm">__doc__</span>
+        <span class="k">return</span> <span class="n">ipfunc</span>
+    <span class="k">return</span> <span class="n">_wraps</span>
+
+<span class="k">def</span> <span class="fm">__getattr__</span><span class="p">(</span><span class="n">name</span><span class="p">:</span> <span class="nb">str</span><span class="p">):</span>
+    <span class="n">rndfunc</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">da</span><span class="o">.</span><span class="n">random</span><span class="p">,</span> <span class="n">name</span><span class="p">)</span>
+    <span class="nd">@wraps</span><span class="p">(</span><span class="n">rndfunc</span><span class="p">)</span>
+    <span class="k">def</span> <span class="nf">_func</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+        <span class="n">name</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s2">&quot;name&quot;</span><span class="p">,</span> <span class="n">rndfunc</span><span class="o">.</span><span class="vm">__name__</span><span class="p">)</span>
+        <span class="n">axes</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s2">&quot;axes&quot;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
+        <span class="n">out</span> <span class="o">=</span> <span class="n">rndfunc</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
+        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">_func</span>
+
+
+<span class="k">def</span> <span class="nf">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">|</span> <span class="kc">None</span><span class="p">):</span>
+    <span class="k">if</span> <span class="n">like</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
+        <span class="n">name</span> <span class="o">=</span> <span class="n">name</span> <span class="ow">or</span> <span class="n">like</span><span class="o">.</span><span class="n">name</span>
+        <span class="n">axes</span> <span class="o">=</span> <span class="n">axes</span> <span class="ow">or</span> <span class="n">like</span><span class="o">.</span><span class="n">axes</span>
+        <span class="n">size</span> <span class="o">=</span> <span class="n">size</span> <span class="ow">or</span> <span class="n">like</span><span class="o">.</span><span class="n">shape</span>
+    <span class="k">return</span> <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span>
+    
+
+<div class="viewcode-block" id="random"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.random.random">[docs]</a><span class="nd">@wraps</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">random</span><span class="p">)</span>
+<span class="k">def</span> <span class="nf">random</span><span class="p">(</span>
+    <span class="n">size</span><span class="p">,</span> 
+    <span class="o">*</span><span class="p">,</span>
+    <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">chunks</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span>
+<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+    <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
+    <span class="n">name</span> <span class="o">=</span> <span class="n">name</span> <span class="ow">or</span> <span class="s2">&quot;random&quot;</span>
+    <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">da</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">random</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">),</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">)</span></div>
+
+<div class="viewcode-block" id="normal"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.random.normal">[docs]</a><span class="nd">@wraps</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">normal</span><span class="p">)</span>
+<span class="k">def</span> <span class="nf">normal</span><span class="p">(</span>
+    <span class="n">loc</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">,</span> 
+    <span class="n">scale</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">1.0</span><span class="p">,</span>
+    <span class="n">size</span><span class="o">=</span> <span class="kc">None</span><span class="p">,</span> 
+    <span class="o">*</span><span class="p">,</span>
+    <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> 
+    <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">chunks</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span>
+<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+    <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">like</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
+    <span class="n">name</span> <span class="o">=</span> <span class="n">name</span> <span class="ow">or</span> <span class="sa">f</span><span class="s2">&quot;normal(</span><span class="si">{</span><span class="n">loc</span><span class="si">}</span><span class="s2">, </span><span class="si">{</span><span class="n">scale</span><span class="si">}</span><span class="s2">)&quot;</span>
+    <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">da</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">normal</span><span class="p">(</span><span class="n">loc</span><span class="p">,</span> <span class="n">scale</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">),</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">)</span></div>
+
+<div class="viewcode-block" id="random_uint8"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.random.random_uint8">[docs]</a><span class="k">def</span> <span class="nf">random_uint8</span><span class="p">(</span>
+    <span class="n">size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">],</span> 
+    <span class="o">*</span><span class="p">,</span> 
+    <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">chunks</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span>
+<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Return a random uint8 image, ranging 0-255.</span>
+
+<span class="sd">    Parameters</span>
+<span class="sd">    ----------</span>
+<span class="sd">    size : int or tuple of int</span>
+<span class="sd">        Image shape.</span>
+<span class="sd">    name : str, optional</span>
+<span class="sd">        Image name.</span>
+<span class="sd">    axes : str, optional</span>
+<span class="sd">        Image axes.</span>
+<span class="sd">        </span>
+<span class="sd">    Returns</span>
+<span class="sd">    -------</span>
+<span class="sd">    ImgArray</span>
+<span class="sd">        Random Image in dtype ``np.uint8``.</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">like</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
+    <span class="n">arr</span> <span class="o">=</span> <span class="n">da</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randint</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">255</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">)</span>
+    <span class="n">name</span> <span class="o">=</span> <span class="n">name</span> <span class="ow">or</span> <span class="s2">&quot;random_uint8&quot;</span>
+    <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">)</span></div>
+
+<div class="viewcode-block" id="random_uint16"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.random.random_uint16">[docs]</a><span class="k">def</span> <span class="nf">random_uint16</span><span class="p">(</span>
+    <span class="n">size</span><span class="p">,</span>
+    <span class="o">*</span><span class="p">,</span> 
+    <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="n">chunks</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span>
+<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Return a random uint16 image, ranging 0-65535.</span>
+
+<span class="sd">    Parameters</span>
+<span class="sd">    ----------</span>
+<span class="sd">    size : int or tuple of int</span>
+<span class="sd">        Image shape.</span>
+<span class="sd">    name : str, optional</span>
+<span class="sd">        Image name.</span>
+<span class="sd">    axes : str, optional</span>
+<span class="sd">        Image axes.</span>
+<span class="sd">        </span>
+<span class="sd">    Returns</span>
+<span class="sd">    -------</span>
+<span class="sd">    ImgArray</span>
+<span class="sd">        Random Image in dtype ``np.uint16``.</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">like</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
+    <span class="n">arr</span> <span class="o">=</span> <span class="n">da</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randint</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">65535</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint16</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">)</span>
+    <span class="n">name</span> <span class="o">=</span> <span class="n">name</span> <span class="ow">or</span> <span class="s2">&quot;random_uint16&quot;</span>
+    <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">)</span></div>
+
+
+<div class="viewcode-block" id="default_rng"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.random.default_rng">[docs]</a><span class="k">def</span> <span class="nf">default_rng</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImageGenerator</span><span class="p">:</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Get the default random number generator.&quot;&quot;&quot;</span>
+    <span class="k">return</span> <span class="n">ImageGenerator</span><span class="p">(</span><span class="n">da</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">default_rng</span><span class="p">(</span><span class="n">seed</span><span class="p">))</span></div>
+
+<div class="viewcode-block" id="ImageGenerator"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.random.ImageGenerator">[docs]</a><span class="k">class</span> <span class="nc">ImageGenerator</span><span class="p">:</span>
+    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">rng</span><span class="p">:</span> <span class="n">da</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">Generator</span><span class="p">):</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">_rng</span> <span class="o">=</span> <span class="n">rng</span>
+    
+<div class="viewcode-block" id="ImageGenerator.standard_normal"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.random.ImageGenerator.standard_normal">[docs]</a>    <span class="k">def</span> <span class="nf">standard_normal</span><span class="p">(</span>
+        <span class="bp">self</span><span class="p">,</span>
+        <span class="n">size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">dtype</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="o">*</span><span class="p">,</span>
+        <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">chunks</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span>
+    <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+        <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
+        <span class="n">arr</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_rng</span><span class="o">.</span><span class="n">standard_normal</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="n">size</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">)</span>
+        <span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">isscalar</span><span class="p">(</span><span class="n">arr</span><span class="p">):</span>
+            <span class="k">return</span> <span class="n">arr</span>
+        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">)</span></div>
+    
+<div class="viewcode-block" id="ImageGenerator.standard_exponential"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.random.ImageGenerator.standard_exponential">[docs]</a>    <span class="k">def</span> <span class="nf">standard_exponential</span><span class="p">(</span>
+        <span class="bp">self</span><span class="p">,</span>
+        <span class="n">size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> 
+        <span class="n">dtype</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">method</span><span class="p">:</span> <span class="n">Literal</span><span class="p">[</span><span class="s2">&quot;zig&quot;</span><span class="p">,</span> <span class="s2">&quot;inv&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="o">*</span><span class="p">,</span>
+        <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">chunks</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span>
+    <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+        <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
+    
+        <span class="n">arr</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_rng</span><span class="o">.</span><span class="n">standard_exponential</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="n">size</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="n">method</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">)</span>
+        <span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">isscalar</span><span class="p">(</span><span class="n">arr</span><span class="p">):</span>
+            <span class="k">return</span> <span class="n">arr</span>
+        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">)</span></div>
+    
+<div class="viewcode-block" id="ImageGenerator.random"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.random.ImageGenerator.random">[docs]</a>    <span class="k">def</span> <span class="nf">random</span><span class="p">(</span>
+        <span class="bp">self</span><span class="p">,</span>
+        <span class="n">size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> 
+        <span class="n">dtype</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">,</span>
+        <span class="o">*</span><span class="p">,</span>
+        <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">chunks</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span>
+    <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+        <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
+    
+        <span class="n">arr</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_rng</span><span class="o">.</span><span class="n">random</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="n">size</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">float64</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">)</span>
+        <span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">isscalar</span><span class="p">(</span><span class="n">arr</span><span class="p">):</span>
+            <span class="k">return</span> <span class="n">arr</span>
+        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">dtype</span><span class="p">,</span> <span class="n">copy</span><span class="o">=</span><span class="kc">False</span><span class="p">),</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">)</span></div>
+    
+<div class="viewcode-block" id="ImageGenerator.normal"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.random.ImageGenerator.normal">[docs]</a>    <span class="k">def</span> <span class="nf">normal</span><span class="p">(</span>
+        <span class="bp">self</span><span class="p">,</span>
+        <span class="n">loc</span><span class="p">:</span> <span class="nb">float</span> <span class="o">|</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">=</span> <span class="mf">0.</span><span class="p">,</span>
+        <span class="n">scale</span><span class="p">:</span> <span class="nb">float</span> <span class="o">|</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">=</span> <span class="mf">1.</span><span class="p">,</span>
+        <span class="n">size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="o">*</span><span class="p">,</span>
+        <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">chunks</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span>
+    <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+        <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
+    
+        <span class="n">arr</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_rng</span><span class="o">.</span><span class="n">normal</span><span class="p">(</span><span class="n">loc</span><span class="o">=</span><span class="n">loc</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="n">scale</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="n">size</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">)</span>
+        <span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">isscalar</span><span class="p">(</span><span class="n">arr</span><span class="p">):</span>
+            <span class="k">return</span> <span class="n">arr</span>
+        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">),</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">)</span></div>
+
+<div class="viewcode-block" id="ImageGenerator.poisson"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.random.ImageGenerator.poisson">[docs]</a>    <span class="k">def</span> <span class="nf">poisson</span><span class="p">(</span>
+        <span class="bp">self</span><span class="p">,</span>
+        <span class="n">lam</span><span class="p">:</span> <span class="nb">float</span><span class="p">,</span>
+        <span class="n">size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="o">*</span><span class="p">,</span>
+        <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">chunks</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span>
+    <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+        <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
+    
+        <span class="n">arr</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_rng</span><span class="o">.</span><span class="n">poisson</span><span class="p">(</span><span class="n">lam</span><span class="o">=</span><span class="n">lam</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="n">size</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">)</span>
+        <span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">isscalar</span><span class="p">(</span><span class="n">arr</span><span class="p">):</span>
+            <span class="k">return</span> <span class="n">arr</span>
+        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">)</span></div>
+    
+<div class="viewcode-block" id="ImageGenerator.random_uint8"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.random.ImageGenerator.random_uint8">[docs]</a>    <span class="k">def</span> <span class="nf">random_uint8</span><span class="p">(</span>
+        <span class="bp">self</span><span class="p">,</span>
+        <span class="n">size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">],</span> 
+        <span class="o">*</span><span class="p">,</span> 
+        <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">chunks</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span>
+    <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+        <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
+    
+        <span class="n">arr</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_rng</span><span class="o">.</span><span class="n">integers</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">255</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">)</span>
+        <span class="n">name</span> <span class="o">=</span> <span class="n">name</span> <span class="ow">or</span> <span class="s2">&quot;random_uint8&quot;</span>
+        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">)</span></div>
+
+<div class="viewcode-block" id="ImageGenerator.random_uint16"><a class="viewcode-back" href="../../../apidoc/impy.lazy.html#impy.lazy.random.ImageGenerator.random_uint16">[docs]</a>    <span class="k">def</span> <span class="nf">random_uint16</span><span class="p">(</span>
+        <span class="bp">self</span><span class="p">,</span>
+        <span class="n">size</span><span class="p">,</span>
+        <span class="o">*</span><span class="p">,</span> 
+        <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">chunks</span><span class="o">=</span><span class="s2">&quot;auto&quot;</span><span class="p">,</span>
+    <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">LazyImgArray</span><span class="p">:</span>
+        <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
+    
+        <span class="n">arr</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_rng</span><span class="o">.</span><span class="n">integers</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">65535</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">uint16</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="n">chunks</span><span class="p">)</span>
+        <span class="n">name</span> <span class="o">=</span> <span class="n">name</span> <span class="ow">or</span> <span class="s2">&quot;random_uint16&quot;</span>
+        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">)</span></div></div>
+
+
+<span class="k">del</span> <span class="n">wraps</span>
+</pre></div>
+
+           </div>
+          </div>
+          <footer>
+
+  <hr/>
+
+  <div role="contentinfo">
+    <p>&#169; Copyright 2021, Hanjin Liu.</p>
+  </div>
+
+  Built with <a href="https://www.sphinx-doc.org/">Sphinx</a> using a
+    <a href="https://github.com/readthedocs/sphinx_rtd_theme">theme</a>
+    provided by <a href="https://readthedocs.org">Read the Docs</a>.
+   
+
+</footer>
+        </div>
+      </div>
+    </section>
+  </div>
+  <script>
+      jQuery(function () {
+          SphinxRtdTheme.Navigation.enable(true);
+      });
+  </script> 
+
+</body>
+</html>
\ No newline at end of file
diff --git a/docs/_modules/impy/random.html b/docs/_modules/impy/random.html
index 9fd6d9d3..31567bc4 100644
--- a/docs/_modules/impy/random.html
+++ b/docs/_modules/impy/random.html
@@ -3,7 +3,7 @@
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.random &mdash; impy 2.2.0 documentation</title>
+  <title>impy.random &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -11,9 +11,8 @@
   <![endif]-->
   
         <script data-url_root="../../" id="documentation_options" src="../../_static/documentation_options.js"></script>
-        <script src="../../_static/jquery.js"></script>
-        <script src="../../_static/underscore.js"></script>
         <script src="../../_static/doctools.js"></script>
+        <script src="../../_static/sphinx_highlight.js"></script>
     <script src="../../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../../genindex.html" />
     <link rel="search" title="Search" href="../../search.html" /> 
@@ -24,14 +23,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -58,9 +61,9 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../index.html">Module code</a> &raquo;</li>
-      <li>impy.random</li>
+      <li><a href="../../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../index.html">Module code</a></li>
+      <li class="breadcrumb-item active">impy.random</li>
       <li class="wy-breadcrumbs-aside">
       </li>
   </ul>
@@ -72,8 +75,7 @@
   <h1>Source code for impy.random</h1><div class="highlight"><pre>
 <span></span><span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="n">annotations</span>
 <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
-<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Callable</span><span class="p">,</span> <span class="n">Literal</span><span class="p">,</span> <span class="n">TypeVar</span>
-<span class="kn">import</span> <span class="nn">functools</span>
+<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Literal</span>
 <span class="kn">from</span> <span class="nn">.arrays</span> <span class="kn">import</span> <span class="n">ImgArray</span><span class="p">,</span> <span class="n">LazyImgArray</span>
 <span class="kn">from</span> <span class="nn">.arrays.bases</span> <span class="kn">import</span> <span class="n">MetaArray</span>
 <span class="kn">from</span> <span class="nn">.array_api</span> <span class="kn">import</span> <span class="n">xp</span>
@@ -111,7 +113,7 @@ <h1>Source code for impy.random</h1><div class="highlight"><pre>
     <span class="o">*</span><span class="p">,</span>
     <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-    <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span><span class="kc">None</span><span class="p">,</span>
+    <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
     <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
     <span class="n">name</span> <span class="o">=</span> <span class="n">name</span> <span class="ow">or</span> <span class="s2">&quot;random&quot;</span>
@@ -121,7 +123,7 @@ <h1>Source code for impy.random</h1><div class="highlight"><pre>
 <span class="k">def</span> <span class="nf">normal</span><span class="p">(</span>
     <span class="n">loc</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">,</span> 
     <span class="n">scale</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">1.0</span><span class="p">,</span>
-    <span class="n">size</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> 
+    <span class="n">size</span><span class="o">=</span> <span class="kc">None</span><span class="p">,</span> 
     <span class="o">*</span><span class="p">,</span>
     <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> 
     <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
@@ -136,9 +138,9 @@ <h1>Source code for impy.random</h1><div class="highlight"><pre>
     <span class="o">*</span><span class="p">,</span> 
     <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-    <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span><span class="kc">None</span><span class="p">,</span>
+    <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Return a random uint8 image, ranging 0-255.</span>
 
 <span class="sd">    Parameters</span>
@@ -165,9 +167,9 @@ <h1>Source code for impy.random</h1><div class="highlight"><pre>
     <span class="o">*</span><span class="p">,</span> 
     <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-    <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span><span class="kc">None</span><span class="p">,</span>
+    <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
 <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Return a random uint16 image, ranging 0-65535.</span>
 
 <span class="sd">    Parameters</span>
@@ -191,7 +193,7 @@ <h1>Source code for impy.random</h1><div class="highlight"><pre>
 
 
 <div class="viewcode-block" id="default_rng"><a class="viewcode-back" href="../../apidoc/impy.html#impy.random.default_rng">[docs]</a><span class="k">def</span> <span class="nf">default_rng</span><span class="p">(</span><span class="n">seed</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImageGenerator</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;Get the default random number generator.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Get the default random number generator.&quot;&quot;&quot;</span>
     <span class="k">return</span> <span class="n">ImageGenerator</span><span class="p">(</span><span class="n">xp</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">default_rng</span><span class="p">(</span><span class="n">seed</span><span class="p">))</span></div>
 
 <div class="viewcode-block" id="ImageGenerator"><a class="viewcode-back" href="../../apidoc/impy.html#impy.random.ImageGenerator">[docs]</a><span class="k">class</span> <span class="nc">ImageGenerator</span><span class="p">:</span>
@@ -205,13 +207,13 @@ <h1>Source code for impy.random</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span><span class="kc">None</span><span class="p">,</span>
+        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
         <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
         <span class="n">arr</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_rng</span><span class="o">.</span><span class="n">standard_normal</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="n">size</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">)</span>
         <span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">isscalar</span><span class="p">(</span><span class="n">arr</span><span class="p">):</span>
             <span class="k">return</span> <span class="n">arr</span>
-        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">)</span></div>
+        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">xp</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">(</span><span class="n">arr</span><span class="p">),</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">)</span></div>
     
 <div class="viewcode-block" id="ImageGenerator.standard_exponential"><a class="viewcode-back" href="../../apidoc/impy.html#impy.random.ImageGenerator.standard_exponential">[docs]</a>    <span class="k">def</span> <span class="nf">standard_exponential</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">,</span>
@@ -221,14 +223,14 @@ <h1>Source code for impy.random</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span><span class="kc">None</span><span class="p">,</span>
+        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
         <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
     
         <span class="n">arr</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_rng</span><span class="o">.</span><span class="n">standard_exponential</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="n">size</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="n">method</span><span class="p">)</span>
         <span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">isscalar</span><span class="p">(</span><span class="n">arr</span><span class="p">):</span>
             <span class="k">return</span> <span class="n">arr</span>
-        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">)</span></div>
+        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">xp</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">(</span><span class="n">arr</span><span class="p">),</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">)</span></div>
     
 <div class="viewcode-block" id="ImageGenerator.random"><a class="viewcode-back" href="../../apidoc/impy.html#impy.random.ImageGenerator.random">[docs]</a>    <span class="k">def</span> <span class="nf">random</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">,</span>
@@ -237,14 +239,14 @@ <h1>Source code for impy.random</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span><span class="kc">None</span><span class="p">,</span>
+        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
         <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
     
         <span class="n">arr</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_rng</span><span class="o">.</span><span class="n">random</span><span class="p">(</span><span class="n">size</span><span class="o">=</span><span class="n">size</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">)</span>
         <span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">isscalar</span><span class="p">(</span><span class="n">arr</span><span class="p">):</span>
             <span class="k">return</span> <span class="n">arr</span>
-        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">)</span></div>
+        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">xp</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">(</span><span class="n">arr</span><span class="p">),</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">)</span></div>
     
 <div class="viewcode-block" id="ImageGenerator.normal"><a class="viewcode-back" href="../../apidoc/impy.html#impy.random.ImageGenerator.normal">[docs]</a>    <span class="k">def</span> <span class="nf">normal</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">,</span>
@@ -254,14 +256,14 @@ <h1>Source code for impy.random</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span><span class="kc">None</span><span class="p">,</span>
+        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
         <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
     
         <span class="n">arr</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_rng</span><span class="o">.</span><span class="n">normal</span><span class="p">(</span><span class="n">loc</span><span class="o">=</span><span class="n">loc</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="n">scale</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="n">size</span><span class="p">)</span>
         <span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">isscalar</span><span class="p">(</span><span class="n">arr</span><span class="p">):</span>
             <span class="k">return</span> <span class="n">arr</span>
-        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">)</span></div>
+        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">xp</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">(</span><span class="n">arr</span><span class="p">),</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">)</span></div>
 
 <div class="viewcode-block" id="ImageGenerator.poisson"><a class="viewcode-back" href="../../apidoc/impy.html#impy.random.ImageGenerator.poisson">[docs]</a>    <span class="k">def</span> <span class="nf">poisson</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">,</span>
@@ -270,14 +272,14 @@ <h1>Source code for impy.random</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span>
         <span class="n">axes</span><span class="p">:</span> <span class="n">AxesLike</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="kc">None</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span><span class="kc">None</span><span class="p">,</span>
+        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
         <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
     
         <span class="n">arr</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_rng</span><span class="o">.</span><span class="n">poisson</span><span class="p">(</span><span class="n">lam</span><span class="o">=</span><span class="n">lam</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="n">size</span><span class="p">)</span>
         <span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">isscalar</span><span class="p">(</span><span class="n">arr</span><span class="p">):</span>
             <span class="k">return</span> <span class="n">arr</span>
-        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">arr</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">)</span></div>
+        <span class="k">return</span> <span class="n">asarray</span><span class="p">(</span><span class="n">xp</span><span class="o">.</span><span class="n">asnumpy</span><span class="p">(</span><span class="n">arr</span><span class="p">),</span> <span class="n">axes</span><span class="o">=</span><span class="n">axes</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">)</span></div>
     
 <div class="viewcode-block" id="ImageGenerator.random_uint8"><a class="viewcode-back" href="../../apidoc/impy.html#impy.random.ImageGenerator.random_uint8">[docs]</a>    <span class="k">def</span> <span class="nf">random_uint8</span><span class="p">(</span>
         <span class="bp">self</span><span class="p">,</span>
@@ -285,7 +287,7 @@ <h1>Source code for impy.random</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span> 
         <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span><span class="kc">None</span><span class="p">,</span>
+        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
         <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
     
@@ -299,7 +301,7 @@ <h1>Source code for impy.random</h1><div class="highlight"><pre>
         <span class="o">*</span><span class="p">,</span> 
         <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
         <span class="n">axes</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
-        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span><span class="kc">None</span><span class="p">,</span>
+        <span class="n">like</span><span class="p">:</span> <span class="n">MetaArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImgArray</span><span class="p">:</span>
         <span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">_normalize_like</span><span class="p">(</span><span class="n">size</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">axes</span><span class="p">,</span> <span class="n">like</span><span class="p">)</span>
     
diff --git a/docs/_modules/impy/viewer/utils.html b/docs/_modules/impy/viewer/utils.html
index 66a44152..e717af1b 100644
--- a/docs/_modules/impy/viewer/utils.html
+++ b/docs/_modules/impy/viewer/utils.html
@@ -3,7 +3,7 @@
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.viewer.utils &mdash; impy 2.1.2.dev0 documentation</title>
+  <title>impy.viewer.utils &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../../../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -11,9 +11,8 @@
   <![endif]-->
   
         <script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
-        <script src="../../../_static/jquery.js"></script>
-        <script src="../../../_static/underscore.js"></script>
         <script src="../../../_static/doctools.js"></script>
+        <script src="../../../_static/sphinx_highlight.js"></script>
     <script src="../../../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../../../genindex.html" />
     <link rel="search" title="Search" href="../../../search.html" /> 
@@ -24,14 +23,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../../../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../../../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.1.2.dev0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../../../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -58,9 +61,9 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../../../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../../index.html">Module code</a> &raquo;</li>
-      <li>impy.viewer.utils</li>
+      <li><a href="../../../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../../index.html">Module code</a></li>
+      <li class="breadcrumb-item active">impy.viewer.utils</li>
       <li class="wy-breadcrumbs-aside">
       </li>
   </ul>
@@ -77,18 +80,19 @@ <h1>Source code for impy.viewer.utils</h1><div class="highlight"><pre>
 <span class="kn">import</span> <span class="nn">napari</span>
 <span class="kn">import</span> <span class="nn">os</span>
 
-<span class="kn">from</span> <span class="nn">..arrays</span> <span class="kn">import</span> <span class="o">*</span>
-<span class="kn">from</span> <span class="nn">.._const</span> <span class="kn">import</span> <span class="n">Const</span>
-<span class="kn">from</span> <span class="nn">..core</span> <span class="kn">import</span> <span class="n">imread</span><span class="p">,</span> <span class="n">lazy_imread</span>
+<span class="kn">from</span> <span class="nn">impy.arrays</span> <span class="kn">import</span> <span class="o">*</span>
+<span class="kn">from</span> <span class="nn">impy._const</span> <span class="kn">import</span> <span class="n">Const</span>
+<span class="kn">from</span> <span class="nn">impy.core</span> <span class="kn">import</span> <span class="n">imread</span>
+<span class="kn">from</span> <span class="nn">impy.lazy</span> <span class="kn">import</span> <span class="n">imread</span> <span class="k">as</span> <span class="n">lazy_imread</span>
 
 <span class="k">if</span> <span class="n">TYPE_CHECKING</span><span class="p">:</span>
-    <span class="kn">from</span> <span class="nn">..frame</span> <span class="kn">import</span> <span class="n">TrackFrame</span><span class="p">,</span> <span class="n">PathFrame</span><span class="p">,</span> <span class="n">AxesFrame</span>
-    <span class="kn">from</span> <span class="nn">..roi</span> <span class="kn">import</span> <span class="n">Roi</span>
+    <span class="kn">from</span> <span class="nn">impy.frame</span> <span class="kn">import</span> <span class="n">TrackFrame</span><span class="p">,</span> <span class="n">PathFrame</span><span class="p">,</span> <span class="n">AxesFrame</span>
+    <span class="kn">from</span> <span class="nn">impy.roi</span> <span class="kn">import</span> <span class="n">Roi</span>
     <span class="kn">from</span> <span class="nn">napari.layers</span> <span class="kn">import</span> <span class="n">Shapes</span>
 
 
 <div class="viewcode-block" id="iter_layer"><a class="viewcode-back" href="../../../apidoc/impy.viewer.html#impy.viewer.utils.iter_layer">[docs]</a><span class="k">def</span> <span class="nf">iter_layer</span><span class="p">(</span><span class="n">viewer</span><span class="p">:</span><span class="s2">&quot;napari.Viewer&quot;</span><span class="p">,</span> <span class="n">layer_type</span><span class="p">:</span> <span class="nb">str</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Iterate over layers and yield only certain type of layers.</span>
 
 <span class="sd">    Parameters</span>
@@ -111,7 +115,7 @@ <h1>Source code for impy.viewer.utils</h1><div class="highlight"><pre>
             <span class="k">yield</span> <span class="n">layer</span></div>
 
 <div class="viewcode-block" id="iter_selected_layer"><a class="viewcode-back" href="../../../apidoc/impy.viewer.html#impy.viewer.utils.iter_selected_layer">[docs]</a><span class="k">def</span> <span class="nf">iter_selected_layer</span><span class="p">(</span><span class="n">viewer</span><span class="p">:</span> <span class="s2">&quot;napari.Viewer&quot;</span><span class="p">,</span> <span class="n">layer_type</span><span class="p">:</span> <span class="nb">str</span> <span class="o">|</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]):</span>
-    <span class="sd">&quot;&quot;&quot;Iterate over selected layers and yield only certain type of layers.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Iterate over selected layers and yield only certain type of layers.&quot;&quot;&quot;</span>
     
     <span class="kn">from</span> <span class="nn">napari</span> <span class="kn">import</span> <span class="n">layers</span>
     <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">layer_type</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span>
@@ -123,7 +127,7 @@ <h1>Source code for impy.viewer.utils</h1><div class="highlight"><pre>
             <span class="k">yield</span> <span class="n">layer</span></div>
 
 <div class="viewcode-block" id="front_image"><a class="viewcode-back" href="../../../apidoc/impy.viewer.html#impy.viewer.utils.front_image">[docs]</a><span class="k">def</span> <span class="nf">front_image</span><span class="p">(</span><span class="n">viewer</span><span class="p">:</span><span class="s2">&quot;napari.Viewer&quot;</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;From list of image layers return the most front visible image.&quot;&quot;&quot;</span>        
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;From list of image layers return the most front visible image.&quot;&quot;&quot;</span>        
     
     <span class="n">front</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="k">for</span> <span class="n">img</span> <span class="ow">in</span> <span class="n">iter_layer</span><span class="p">(</span><span class="n">viewer</span><span class="p">,</span> <span class="s2">&quot;Image&quot;</span><span class="p">):</span>
@@ -134,7 +138,7 @@ <h1>Source code for impy.viewer.utils</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="n">front</span></div>
 
 <div class="viewcode-block" id="to_labels"><a class="viewcode-back" href="../../../apidoc/impy.viewer.html#impy.viewer.utils.to_labels">[docs]</a><span class="k">def</span> <span class="nf">to_labels</span><span class="p">(</span><span class="n">layer</span><span class="p">:</span> <span class="s2">&quot;Shapes&quot;</span><span class="p">,</span> <span class="n">labels_shape</span><span class="p">:</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">],</span> <span class="n">zoom_factor</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">1.</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;Convert a Shapes layer to labels, with given zoom factor.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Convert a Shapes layer to labels, with given zoom factor.&quot;&quot;&quot;</span>
     <span class="k">return</span> <span class="n">layer</span><span class="o">.</span><span class="n">_data_view</span><span class="o">.</span><span class="n">to_labels</span><span class="p">(</span>
         <span class="n">labels_shape</span><span class="o">=</span><span class="n">labels_shape</span><span class="p">,</span> <span class="n">zoom_factor</span><span class="o">=</span><span class="n">zoom_factor</span>
     <span class="p">)</span></div>
@@ -151,7 +155,7 @@ <h1>Source code for impy.viewer.utils</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="n">scale</span></div>
 
 <div class="viewcode-block" id="viewer_imread"><a class="viewcode-back" href="../../../apidoc/impy.viewer.html#impy.viewer.utils.viewer_imread">[docs]</a><span class="k">def</span> <span class="nf">viewer_imread</span><span class="p">(</span><span class="n">viewer</span><span class="p">:</span> <span class="s2">&quot;napari.Viewer&quot;</span><span class="p">,</span> <span class="n">path</span><span class="p">:</span> <span class="nb">str</span><span class="p">):</span>    
-    <span class="sd">&quot;&quot;&quot;Read an image into the viewer.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Read an image into the viewer.&quot;&quot;&quot;</span>
     
     <span class="k">if</span> <span class="s2">&quot;*&quot;</span> <span class="ow">in</span> <span class="n">path</span> <span class="ow">or</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">getsize</span><span class="p">(</span><span class="n">path</span><span class="p">)</span><span class="o">/</span><span class="mf">1e9</span> <span class="o">&lt;</span> <span class="n">Const</span><span class="p">[</span><span class="s2">&quot;MAX_GB&quot;</span><span class="p">]:</span>
         <span class="n">img</span> <span class="o">=</span> <span class="n">imread</span><span class="p">(</span><span class="n">path</span><span class="p">)</span>
@@ -161,7 +165,7 @@ <h1>Source code for impy.viewer.utils</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="n">layer</span></div>
 
 <div class="viewcode-block" id="add_labeledarray"><a class="viewcode-back" href="../../../apidoc/impy.viewer.html#impy.viewer.utils.add_labeledarray">[docs]</a><span class="k">def</span> <span class="nf">add_labeledarray</span><span class="p">(</span><span class="n">viewer</span><span class="p">:</span> <span class="s2">&quot;napari.Viewer&quot;</span><span class="p">,</span> <span class="n">img</span><span class="p">:</span> <span class="n">LabeledArray</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;Add a LabeledArray to the viewer.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Add a LabeledArray to the viewer.&quot;&quot;&quot;</span>
     
     <span class="k">if</span> <span class="ow">not</span> <span class="n">img</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">is_sorted</span><span class="p">()</span> <span class="ow">and</span> <span class="n">img</span><span class="o">.</span><span class="n">ndim</span> <span class="o">&gt;</span> <span class="mi">2</span><span class="p">:</span>
         <span class="n">msg</span> <span class="o">=</span> <span class="p">(</span>
@@ -351,11 +355,11 @@ <h1>Source code for impy.viewer.utils</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="kc">None</span></div>
 
 <div class="viewcode-block" id="get_viewer_scale"><a class="viewcode-back" href="../../../apidoc/impy.viewer.html#impy.viewer.utils.get_viewer_scale">[docs]</a><span class="k">def</span> <span class="nf">get_viewer_scale</span><span class="p">(</span><span class="n">viewer</span><span class="p">:</span> <span class="s2">&quot;napari.Viewer&quot;</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;Get the scale of the viewer.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Get the scale of the viewer.&quot;&quot;&quot;</span>
     <span class="k">return</span> <span class="p">{</span><span class="n">a</span><span class="p">:</span> <span class="n">r</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="k">for</span> <span class="n">a</span><span class="p">,</span> <span class="n">r</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">viewer</span><span class="o">.</span><span class="n">dims</span><span class="o">.</span><span class="n">axis_labels</span><span class="p">,</span> <span class="n">viewer</span><span class="o">.</span><span class="n">dims</span><span class="o">.</span><span class="n">range</span><span class="p">)}</span></div>
 
 <div class="viewcode-block" id="layer_to_impy_object"><a class="viewcode-back" href="../../../apidoc/impy.viewer.html#impy.viewer.utils.layer_to_impy_object">[docs]</a><span class="k">def</span> <span class="nf">layer_to_impy_object</span><span class="p">(</span><span class="n">viewer</span><span class="p">:</span> <span class="s2">&quot;napari.Viewer&quot;</span><span class="p">,</span> <span class="n">layer</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Convert layer to real data.</span>
 
 <span class="sd">    Parameters</span>
@@ -418,7 +422,7 @@ <h1>Source code for impy.viewer.utils</h1><div class="highlight"><pre>
 <span class="n">_A</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s2">&quot;_A&quot;</span><span class="p">,</span> <span class="n">bound</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)</span>
 
 <div class="viewcode-block" id="ComplexArrayView"><a class="viewcode-back" href="../../../apidoc/impy.viewer.html#impy.viewer.utils.ComplexArrayView">[docs]</a><span class="k">class</span> <span class="nc">ComplexArrayView</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;View a complex array in napari.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;View a complex array in napari.&quot;&quot;&quot;</span>
     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">:</span> <span class="n">_A</span><span class="p">):</span>
         <span class="k">if</span> <span class="n">data</span><span class="o">.</span><span class="n">dtype</span><span class="o">.</span><span class="n">kind</span> <span class="o">!=</span> <span class="s2">&quot;c&quot;</span><span class="p">:</span>
             <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s2">&quot;Input was not a complex array.&quot;</span><span class="p">)</span>
@@ -429,27 +433,27 @@ <h1>Source code for impy.viewer.utils</h1><div class="highlight"><pre>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">data_raw</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">_A</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Return the raw data.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Return the raw data.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_data</span>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">shape</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Shape of array.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Shape of array.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_data</span><span class="o">.</span><span class="n">shape</span>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">ndim</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">int</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Number of dimensions of array.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Number of dimensions of array.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_data</span><span class="o">.</span><span class="n">ndim</span>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">dtype</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">dtype</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Data type of array.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Data type of array.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_data</span><span class="o">.</span><span class="n">dtype</span>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">nbytes</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">int</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Bytes of array.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Bytes of array.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_data</span><span class="o">.</span><span class="n">nbytes</span>
     
     <span class="k">def</span> <span class="fm">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">key</span><span class="p">):</span>
diff --git a/docs/_modules/impy/viewer/viewer.html b/docs/_modules/impy/viewer/viewer.html
index 9580cd79..d6cc04c6 100644
--- a/docs/_modules/impy/viewer/viewer.html
+++ b/docs/_modules/impy/viewer/viewer.html
@@ -3,7 +3,7 @@
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.viewer.viewer &mdash; impy 2.2.0 documentation</title>
+  <title>impy.viewer.viewer &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../../../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -11,9 +11,8 @@
   <![endif]-->
   
         <script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
-        <script src="../../../_static/jquery.js"></script>
-        <script src="../../../_static/underscore.js"></script>
         <script src="../../../_static/doctools.js"></script>
+        <script src="../../../_static/sphinx_highlight.js"></script>
     <script src="../../../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../../../genindex.html" />
     <link rel="search" title="Search" href="../../../search.html" /> 
@@ -24,14 +23,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../../../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../../../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../../../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -58,9 +61,9 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../../../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../../index.html">Module code</a> &raquo;</li>
-      <li>impy.viewer.viewer</li>
+      <li><a href="../../../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../../index.html">Module code</a></li>
+      <li class="breadcrumb-item active">impy.viewer.viewer</li>
       <li class="wy-breadcrumbs-aside">
       </li>
   </ul>
@@ -91,11 +94,12 @@ <h1>Source code for impy.viewer.viewer</h1><div class="highlight"><pre>
     <span class="n">make_world_scale</span><span class="p">,</span>
 <span class="p">)</span>
 
-<span class="kn">from</span> <span class="nn">..collections</span> <span class="kn">import</span> <span class="o">*</span>
-<span class="kn">from</span> <span class="nn">..arrays</span> <span class="kn">import</span> <span class="o">*</span>
-<span class="kn">from</span> <span class="nn">..core</span> <span class="kn">import</span> <span class="n">array</span> <span class="k">as</span> <span class="n">ip_array</span><span class="p">,</span> <span class="n">aslazy</span> <span class="k">as</span> <span class="n">ip_aslazy</span>
-<span class="kn">from</span> <span class="nn">..axes</span> <span class="kn">import</span> <span class="n">ScaleView</span><span class="p">,</span> <span class="n">AxisLike</span><span class="p">,</span> <span class="n">Axes</span><span class="p">,</span> <span class="n">Axis</span>
-<span class="kn">from</span> <span class="nn">.._const</span> <span class="kn">import</span> <span class="n">Const</span>
+<span class="kn">from</span> <span class="nn">impy.collections</span> <span class="kn">import</span> <span class="o">*</span>
+<span class="kn">from</span> <span class="nn">impy.arrays</span> <span class="kn">import</span> <span class="o">*</span>
+<span class="kn">from</span> <span class="nn">impy.core</span> <span class="kn">import</span> <span class="n">array</span> <span class="k">as</span> <span class="n">ip_array</span>
+<span class="kn">from</span> <span class="nn">impy.lazy</span> <span class="kn">import</span> <span class="n">asarray</span> <span class="k">as</span> <span class="n">ip_aslazy</span>
+<span class="kn">from</span> <span class="nn">impy.axes</span> <span class="kn">import</span> <span class="n">ScaleView</span><span class="p">,</span> <span class="n">AxisLike</span><span class="p">,</span> <span class="n">Axes</span><span class="p">,</span> <span class="n">Axis</span>
+<span class="kn">from</span> <span class="nn">impy._const</span> <span class="kn">import</span> <span class="n">Const</span>
 
 <span class="k">if</span> <span class="n">TYPE_CHECKING</span><span class="p">:</span>
     <span class="kn">from</span> <span class="nn">napari.components</span> <span class="kn">import</span> <span class="n">LayerList</span>
@@ -110,19 +114,20 @@ <h1>Source code for impy.viewer.viewer</h1><div class="highlight"><pre>
 <span class="n">ImpyObject</span> <span class="o">=</span> <span class="n">NewType</span><span class="p">(</span><span class="s2">&quot;ImpyObject&quot;</span><span class="p">,</span> <span class="n">Any</span><span class="p">)</span>
 
 <div class="viewcode-block" id="napariViewers"><a class="viewcode-back" href="../../../apidoc/impy.viewer.html#impy.viewer.viewer.napariViewers">[docs]</a><span class="k">class</span> <span class="nc">napariViewers</span><span class="p">:</span>
-    <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    The controller of ``napari.Viewer``s from ``impy``. Always access by ``ip.gui``.</span>
 <span class="sd">    &quot;&quot;&quot;</span>    
     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">_viewers</span><span class="p">:</span> <span class="n">WeakValueDictionary</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="s2">&quot;napari.Viewer&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">WeakValueDictionary</span><span class="p">()</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">_front_viewer</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">_axes</span><span class="p">:</span> <span class="n">Axes</span> <span class="o">=</span> <span class="kc">None</span>
     
     <span class="k">def</span> <span class="fm">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
         <span class="n">w</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="sa">f</span><span class="s2">&quot;&lt;</span><span class="si">{</span><span class="n">k</span><span class="si">}</span><span class="s2">&gt;&quot;</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_viewers</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span>
         <span class="k">return</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="si">}{</span><span class="n">w</span><span class="si">}</span><span class="s2">&quot;</span>
     
     <span class="k">def</span> <span class="fm">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">key</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">napariViewers</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        This method looks strange but intuitive because you can access the last viewer by</span>
 <span class="sd">        &gt;&gt;&gt; ip.gui.add(...)</span>
 <span class="sd">        while turn to another by</span>
@@ -141,19 +146,19 @@ <h1>Source code for impy.viewer.viewer</h1><div class="highlight"><pre>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">viewer</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="s2">&quot;napari.Viewer&quot;</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;The most front viewer you&#39;re using&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;The most front viewer you&#39;re using&quot;&quot;&quot;</span>
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_front_viewer</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_viewers</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">start</span><span class="p">()</span>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_viewers</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">_front_viewer</span><span class="p">]</span>
         
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">layers</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="s2">&quot;LayerList&quot;</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Napari layer list. Identical to ``ip.gui.viewer.layers``.&quot;&quot;&quot;</span>        
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Napari layer list. Identical to ``ip.gui.viewer.layers``.&quot;&quot;&quot;</span>        
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">viewer</span><span class="o">.</span><span class="n">layers</span>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">current_slice</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">slice</span> <span class="o">|</span> <span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Return a tuple of slicer that corresponds to current field of view. </span>
 <span class="sd">        </span>
 <span class="sd">        For instance, when the viewer is displaying yx-plane at t=1, then this property </span>
@@ -169,18 +174,18 @@ <h1>Source code for impy.viewer.viewer</h1><div class="highlight"><pre>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">selection</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="n">ImpyObject</span><span class="p">]:</span>
-        <span class="sd">&quot;&quot;&quot;Return selected layers&#39; data as a list of impy objects.&quot;&quot;&quot;</span>        
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Return selected layers&#39; data as a list of impy objects.&quot;&quot;&quot;</span>        
         <span class="k">return</span> <span class="p">[</span><span class="n">layer_to_impy_object</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">viewer</span><span class="p">,</span> <span class="n">layer</span><span class="p">)</span> 
                 <span class="k">for</span> <span class="n">layer</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">viewer</span><span class="o">.</span><span class="n">layers</span><span class="o">.</span><span class="n">selection</span><span class="p">]</span>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">cursor_pos</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;Return cursor position. Scale is considered.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Return cursor position. Scale is considered.&quot;&quot;&quot;</span>
         <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">viewer</span><span class="o">.</span><span class="n">cursor</span><span class="o">.</span><span class="n">position</span><span class="p">)</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">scale</span>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">axes</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Axes</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Axes information of current viewer. </span>
 <span class="sd">        </span>
 <span class="sd">        Defined to make compatible with ``ImgArray``.</span>
@@ -199,7 +204,7 @@ <h1>Source code for impy.viewer.viewer</h1><div class="highlight"><pre>
     
     <span class="nd">@property</span>
     <span class="k">def</span> <span class="nf">scale</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ScaleView</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Scale information of current viewer.</span>
 <span class="sd">        </span>
 <span class="sd">        Defined to make compatible with ``ImgArray``.</span>
@@ -207,7 +212,7 @@ <h1>Source code for impy.viewer.viewer</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">axes</span><span class="o">.</span><span class="n">scale</span>
     
 <div class="viewcode-block" id="napariViewers.start"><a class="viewcode-back" href="../../../apidoc/impy.viewer.html#impy.viewer.viewer.napariViewers.start">[docs]</a>    <span class="k">def</span> <span class="nf">start</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">key</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;impy&quot;</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;Create a napari window with name ``key``.&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Create a napari window with name ``key``.&quot;&quot;&quot;</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">key</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span>
             <span class="k">raise</span> <span class="ne">TypeError</span><span class="p">(</span><span class="s2">&quot;`key` must be str.&quot;</span><span class="p">)</span>
         <span class="k">if</span> <span class="n">key</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_viewers</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
@@ -224,7 +229,7 @@ <h1>Source code for impy.viewer.viewer</h1><div class="highlight"><pre>
         <span class="n">layer_state</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;visible&quot;</span><span class="p">,</span>
         <span class="n">returns</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;last&quot;</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ImpyObject</span> <span class="o">|</span> <span class="nb">list</span><span class="p">[</span><span class="n">ImpyObject</span><span class="p">]:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Simple way to get impy object from viewer.</span>
 
 <span class="sd">        Parameters</span>
@@ -332,7 +337,7 @@ <h1>Source code for impy.viewer.viewer</h1><div class="highlight"><pre>
         <span class="n">ref</span><span class="p">:</span> <span class="s2">&quot;napari.layers.Image&quot;</span> <span class="o">|</span> <span class="nb">int</span> <span class="o">|</span> <span class="nb">str</span> <span class="o">|</span> <span class="n">LabeledArray</span> <span class="o">|</span> <span class="n">LazyImgArray</span><span class="p">,</span> 
         <span class="n">ndim</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="kc">None</span>
     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        With cursor position and a layer as inputs, this function returns the cursor &quot;pixel&quot; coordinates on the given</span>
 <span class="sd">        layer. This function is useful when you want to get such as pixel value at the cursor position.</span>
 
@@ -381,7 +386,7 @@ <h1>Source code for impy.viewer.viewer</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="p">(</span><span class="n">pos</span> <span class="o">+</span> <span class="mf">0.5</span><span class="p">)</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">int64</span><span class="p">)</span></div>
         
 <div class="viewcode-block" id="napariViewers.add"><a class="viewcode-back" href="../../../apidoc/impy.viewer.html#impy.viewer.viewer.napariViewers.add">[docs]</a>    <span class="k">def</span> <span class="nf">add</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">obj</span><span class="p">:</span> <span class="n">ImpyObject</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Add images, points, labels, tracks etc to viewer.</span>
 
 <span class="sd">        Parameters</span>
@@ -466,7 +471,7 @@ <h1>Source code for impy.viewer.viewer</h1><div class="highlight"><pre>
         <span class="n">mask</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
         <span class="o">**</span><span class="n">kwargs</span>
     <span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Add a surface layer from a 3D image.</span>
 
 <span class="sd">        Parameters</span>
@@ -490,7 +495,7 @@ <h1>Source code for impy.viewer.viewer</h1><div class="highlight"><pre>
     
     
 <div class="viewcode-block" id="napariViewers.goto"><a class="viewcode-back" href="../../../apidoc/impy.viewer.html#impy.viewer.viewer.napariViewers.goto">[docs]</a>    <span class="k">def</span> <span class="nf">goto</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="o">...</span><span class="p">]:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Change the current step of the viewer.</span>
 
 <span class="sd">        Examples</span>
@@ -515,7 +520,7 @@ <h1>Source code for impy.viewer.viewer</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">step</span></div>
     
 <div class="viewcode-block" id="napariViewers.stepof"><a class="viewcode-back" href="../../../apidoc/impy.viewer.html#impy.viewer.viewer.napariViewers.stepof">[docs]</a>    <span class="k">def</span> <span class="nf">stepof</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">symbol</span><span class="p">:</span> <span class="n">AxisLike</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">int</span><span class="p">:</span>
-        <span class="sd">&quot;&quot;&quot;</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Get the current step of certain axis.</span>
 
 <span class="sd">        Parameters</span>
diff --git a/docs/_modules/index.html b/docs/_modules/index.html
index f5fc916b..387de022 100644
--- a/docs/_modules/index.html
+++ b/docs/_modules/index.html
@@ -3,7 +3,7 @@
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>Overview: module code &mdash; impy 2.2.0 documentation</title>
+  <title>Overview: module code &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -11,9 +11,8 @@
   <![endif]-->
   
         <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-        <script src="../_static/jquery.js"></script>
-        <script src="../_static/underscore.js"></script>
         <script src="../_static/doctools.js"></script>
+        <script src="../_static/sphinx_highlight.js"></script>
     <script src="../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" /> 
@@ -24,14 +23,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -58,8 +61,8 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../index.html" class="icon icon-home"></a> &raquo;</li>
-      <li>Overview: module code</li>
+      <li><a href="../index.html" class="icon icon-home" aria-label="Home"></a></li>
+      <li class="breadcrumb-item active">Overview: module code</li>
       <li class="wy-breadcrumbs-aside">
       </li>
   </ul>
@@ -80,11 +83,14 @@ <h1>All modules for which code is available</h1>
 <li><a href="impy/arrays/lazy.html">impy.arrays.lazy</a></li>
 <li><a href="impy/arrays/phasearray.html">impy.arrays.phasearray</a></li>
 <li><a href="impy/arrays/specials.html">impy.arrays.specials</a></li>
+<li><a href="impy/arrays/tiled.html">impy.arrays.tiled</a></li>
 <li><a href="impy/binder.html">impy.binder</a></li>
 <li><a href="impy/collections.html">impy.collections</a></li>
 <li><a href="impy/core.html">impy.core</a></li>
 <li><a href="impy/correlation.html">impy.correlation</a></li>
 <li><a href="impy/frame/frames.html">impy.frame.frames</a></li>
+<li><a href="impy/lazy/core.html">impy.lazy.core</a></li>
+<li><a href="impy/lazy/random.html">impy.lazy.random</a></li>
 <li><a href="impy/random.html">impy.random</a></li>
 <li><a href="impy/roi.html">impy.roi</a></li>
 <li><a href="impy/utils/axesop.html">impy.utils.axesop</a></li>
diff --git a/docs/_sources/apidoc/impy.arrays.rst.txt b/docs/_sources/apidoc/impy.arrays.rst.txt
index c73408d9..94f0d34f 100644
--- a/docs/_sources/apidoc/impy.arrays.rst.txt
+++ b/docs/_sources/apidoc/impy.arrays.rst.txt
@@ -76,6 +76,14 @@ impy.arrays.specials module
    :undoc-members:
    :show-inheritance:
 
+impy.arrays.tiled module
+------------------------
+
+.. automodule:: impy.arrays.tiled
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
 Module contents
 ---------------
 
diff --git a/docs/_sources/apidoc/impy.lazy.rst.txt b/docs/_sources/apidoc/impy.lazy.rst.txt
new file mode 100644
index 00000000..84629d5f
--- /dev/null
+++ b/docs/_sources/apidoc/impy.lazy.rst.txt
@@ -0,0 +1,29 @@
+impy.lazy package
+=================
+
+Submodules
+----------
+
+impy.lazy.core module
+---------------------
+
+.. automodule:: impy.lazy.core
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+impy.lazy.random module
+-----------------------
+
+.. automodule:: impy.lazy.random
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+Module contents
+---------------
+
+.. automodule:: impy.lazy
+   :members:
+   :undoc-members:
+   :show-inheritance:
diff --git a/docs/_sources/apidoc/impy.rst.txt b/docs/_sources/apidoc/impy.rst.txt
index 2dee1ab1..dad37dc5 100644
--- a/docs/_sources/apidoc/impy.rst.txt
+++ b/docs/_sources/apidoc/impy.rst.txt
@@ -10,6 +10,7 @@ Subpackages
    impy.arrays
    impy.axes
    impy.frame
+   impy.lazy
    impy.utils
    impy.viewer
 
diff --git a/docs/_sources/tutorial.rst.txt b/docs/_sources/tutorial.rst.txt
index 80b5db46..2685b32b 100644
--- a/docs/_sources/tutorial.rst.txt
+++ b/docs/_sources/tutorial.rst.txt
@@ -251,12 +251,12 @@ memory map of the image file that is split into smaller chunks, and passes it to
 read" state. The image data is therefore loaded only when it is needed. Many useful functions in ``ImgArray`` 
 are also implemented in ``LazyImgArray`` so that you can easily handle large datasets.
 
-To read large images as ``LazyImgArray``, call ``lazy_imread`` instead. You can specify its chunk size using
+To read large images as ``LazyImgArray``, call ``impy.lazy.imread`` instead. You can specify its chunk size using
 ``chunks`` parameter.
 
 .. code-block:: python
 
-    img = ip.lazy_imread("path/to/image.tif", chunks=(1, "auto", "auto", "auto"))
+    img = ip.lazy.imread("path/to/image.tif", chunks=(1, "auto", "auto", "auto"))
     img
 
 .. code-block::
diff --git a/docs/_static/basic.css b/docs/_static/basic.css
index bf18350b..7577acb1 100644
--- a/docs/_static/basic.css
+++ b/docs/_static/basic.css
@@ -4,7 +4,7 @@
  *
  * Sphinx stylesheet -- basic theme.
  *
- * :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS.
+ * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS.
  * :license: BSD, see LICENSE for details.
  *
  */
@@ -222,7 +222,7 @@ table.modindextable td {
 /* -- general body styles --------------------------------------------------- */
 
 div.body {
-    min-width: 450px;
+    min-width: 360px;
     max-width: 800px;
 }
 
@@ -237,16 +237,6 @@ a.headerlink {
     visibility: hidden;
 }
 
-a.brackets:before,
-span.brackets > a:before{
-    content: "[";
-}
-
-a.brackets:after,
-span.brackets > a:after {
-    content: "]";
-}
-
 h1:hover > a.headerlink,
 h2:hover > a.headerlink,
 h3:hover > a.headerlink,
@@ -335,12 +325,16 @@ p.sidebar-title {
     font-weight: bold;
 }
 
+nav.contents,
+aside.topic,
 div.admonition, div.topic, blockquote {
     clear: left;
 }
 
 /* -- topics ---------------------------------------------------------------- */
 
+nav.contents,
+aside.topic,
 div.topic {
     border: 1px solid #ccc;
     padding: 7px;
@@ -379,6 +373,8 @@ div.body p.centered {
 
 div.sidebar > :last-child,
 aside.sidebar > :last-child,
+nav.contents > :last-child,
+aside.topic > :last-child,
 div.topic > :last-child,
 div.admonition > :last-child {
     margin-bottom: 0;
@@ -386,6 +382,8 @@ div.admonition > :last-child {
 
 div.sidebar::after,
 aside.sidebar::after,
+nav.contents::after,
+aside.topic::after,
 div.topic::after,
 div.admonition::after,
 blockquote::after {
@@ -428,10 +426,6 @@ table.docutils td, table.docutils th {
     border-bottom: 1px solid #aaa;
 }
 
-table.footnote td, table.footnote th {
-    border: 0 !important;
-}
-
 th {
     text-align: left;
     padding-right: 5px;
@@ -615,19 +609,26 @@ ul.simple p {
     margin-bottom: 0;
 }
 
-dl.footnote > dt,
-dl.citation > dt {
+aside.footnote > span,
+div.citation > span {
     float: left;
-    margin-right: 0.5em;
 }
-
-dl.footnote > dd,
-dl.citation > dd {
+aside.footnote > span:last-of-type,
+div.citation > span:last-of-type {
+  padding-right: 0.5em;
+}
+aside.footnote > p {
+  margin-left: 2em;
+}
+div.citation > p {
+  margin-left: 4em;
+}
+aside.footnote > p:last-of-type,
+div.citation > p:last-of-type {
     margin-bottom: 0em;
 }
-
-dl.footnote > dd:after,
-dl.citation > dd:after {
+aside.footnote > p:last-of-type:after,
+div.citation > p:last-of-type:after {
     content: "";
     clear: both;
 }
@@ -644,10 +645,6 @@ dl.field-list > dt {
     padding-right: 5px;
 }
 
-dl.field-list > dt:after {
-    content: ":";
-}
-
 dl.field-list > dd {
     padding-left: 0.5em;
     margin-top: 0em;
diff --git a/docs/_static/css/badge_only.css b/docs/_static/css/badge_only.css
index e380325b..c718cee4 100644
--- a/docs/_static/css/badge_only.css
+++ b/docs/_static/css/badge_only.css
@@ -1 +1 @@
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dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) .k{font-style:italic}html.writer-html4 .rst-content dl:not(.docutils) .descclassname,html.writer-html4 .rst-content dl:not(.docutils) .descname,html.writer-html4 .rst-content dl:not(.docutils) .sig-name,html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) .descclassname,html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) .descname,html.writer-html5 .rst-content dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.citation):not(.glossary):not(.simple) .sig-name{font-family:SFMono-Regular,Menlo,Monaco,Consolas,Liberation Mono,Courier New,Courier,monospace;color:#000}.rst-content .viewcode-back,.rst-content .viewcode-link{display:inline-block;color:#27ae60;font-size:80%;padding-left:24px}.rst-content .viewcode-back{display:block;float:right}.rst-content p.rubric{margin-bottom:12px;font-weight:700}.rst-content code.download,.rst-content tt.download{background:inherit;padding:inherit;font-weight:400;font-family:inherit;font-size:inherit;color:inherit;border:inherit;white-space:inherit}.rst-content code.download span:first-child,.rst-content tt.download span:first-child{-webkit-font-smoothing:subpixel-antialiased}.rst-content code.download span:first-child:before,.rst-content tt.download span:first-child:before{margin-right:4px}.rst-content .guilabel{border:1px solid #7fbbe3;background:#e7f2fa;font-size:80%;font-weight:700;border-radius:4px;padding:2.4px 6px;margin:auto 2px}.rst-content :not(dl.option-list)>:not(dt):not(kbd):not(.kbd)>.kbd,.rst-content :not(dl.option-list)>:not(dt):not(kbd):not(.kbd)>kbd{color:inherit;font-size:80%;background-color:#fff;border:1px solid #a6a6a6;border-radius:4px;box-shadow:0 2px grey;padding:2.4px 6px;margin:auto 0}.rst-content .versionmodified{font-style:italic}@media screen and (max-width:480px){.rst-content .sidebar{width:100%}}span[id*=MathJax-Span]{color:#404040}.math{text-align:center}@font-face{font-family:Lato;src:url(fonts/lato-normal.woff2?bd03a2cc277bbbc338d464e679fe9942) format("woff2"),url(fonts/lato-normal.woff?27bd77b9162d388cb8d4c4217c7c5e2a) format("woff");font-weight:400;font-style:normal;font-display:block}@font-face{font-family:Lato;src:url(fonts/lato-bold.woff2?cccb897485813c7c256901dbca54ecf2) format("woff2"),url(fonts/lato-bold.woff?d878b6c29b10beca227e9eef4246111b) format("woff");font-weight:700;font-style:normal;font-display:block}@font-face{font-family:Lato;src:url(fonts/lato-bold-italic.woff2?0b6bb6725576b072c5d0b02ecdd1900d) format("woff2"),url(fonts/lato-bold-italic.woff?9c7e4e9eb485b4a121c760e61bc3707c) format("woff");font-weight:700;font-style:italic;font-display:block}@font-face{font-family:Lato;src:url(fonts/lato-normal-italic.woff2?4eb103b4d12be57cb1d040ed5e162e9d) format("woff2"),url(fonts/lato-normal-italic.woff?f28f2d6482446544ef1ea1ccc6dd5892) format("woff");font-weight:400;font-style:italic;font-display:block}@font-face{font-family:Roboto Slab;font-style:normal;font-weight:400;src:url(fonts/Roboto-Slab-Regular.woff2?7abf5b8d04d26a2cafea937019bca958) format("woff2"),url(fonts/Roboto-Slab-Regular.woff?c1be9284088d487c5e3ff0a10a92e58c) format("woff");font-display:block}@font-face{font-family:Roboto Slab;font-style:normal;font-weight:700;src:url(fonts/Roboto-Slab-Bold.woff2?9984f4a9bda09be08e83f2506954adbe) format("woff2"),url(fonts/Roboto-Slab-Bold.woff?bed5564a116b05148e3b3bea6fb1162a) format("woff");font-display:block}
\ No newline at end of file
diff --git a/docs/_static/doctools.js b/docs/_static/doctools.js
index e1bfd708..d06a71d7 100644
--- a/docs/_static/doctools.js
+++ b/docs/_static/doctools.js
@@ -2,357 +2,155 @@
  * doctools.js
  * ~~~~~~~~~~~
  *
- * Sphinx JavaScript utilities for all documentation.
+ * Base JavaScript utilities for all Sphinx HTML documentation.
  *
- * :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS.
+ * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS.
  * :license: BSD, see LICENSE for details.
  *
  */
-
-/**
- * select a different prefix for underscore
- */
-$u = _.noConflict();
-
-/**
- * make the code below compatible with browsers without
- * an installed firebug like debugger
-if (!window.console || !console.firebug) {
-  var names = ["log", "debug", "info", "warn", "error", "assert", "dir",
-    "dirxml", "group", "groupEnd", "time", "timeEnd", "count", "trace",
-    "profile", "profileEnd"];
-  window.console = {};
-  for (var i = 0; i < names.length; ++i)
-    window.console[names[i]] = function() {};
-}
- */
-
-/**
- * small helper function to urldecode strings
- *
- * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/decodeURIComponent#Decoding_query_parameters_from_a_URL
- */
-jQuery.urldecode = function(x) {
-  if (!x) {
-    return x
-  }
-  return decodeURIComponent(x.replace(/\+/g, ' '));
-};
-
-/**
- * small helper function to urlencode strings
- */
-jQuery.urlencode = encodeURIComponent;
-
-/**
- * This function returns the parsed url parameters of the
- * current request. Multiple values per key are supported,
- * it will always return arrays of strings for the value parts.
- */
-jQuery.getQueryParameters = function(s) {
-  if (typeof s === 'undefined')
-    s = document.location.search;
-  var parts = s.substr(s.indexOf('?') + 1).split('&');
-  var result = {};
-  for (var i = 0; i < parts.length; i++) {
-    var tmp = parts[i].split('=', 2);
-    var key = jQuery.urldecode(tmp[0]);
-    var value = jQuery.urldecode(tmp[1]);
-    if (key in result)
-      result[key].push(value);
-    else
-      result[key] = [value];
-  }
-  return result;
-};
-
-/**
- * highlight a given string on a jquery object by wrapping it in
- * span elements with the given class name.
- */
-jQuery.fn.highlightText = function(text, className) {
-  function highlight(node, addItems) {
-    if (node.nodeType === 3) {
-      var val = node.nodeValue;
-      var pos = val.toLowerCase().indexOf(text);
-      if (pos >= 0 &&
-          !jQuery(node.parentNode).hasClass(className) &&
-          !jQuery(node.parentNode).hasClass("nohighlight")) {
-        var span;
-        var isInSVG = jQuery(node).closest("body, svg, foreignObject").is("svg");
-        if (isInSVG) {
-          span = document.createElementNS("http://www.w3.org/2000/svg", "tspan");
-        } else {
-          span = document.createElement("span");
-          span.className = className;
-        }
-        span.appendChild(document.createTextNode(val.substr(pos, text.length)));
-        node.parentNode.insertBefore(span, node.parentNode.insertBefore(
-          document.createTextNode(val.substr(pos + text.length)),
-          node.nextSibling));
-        node.nodeValue = val.substr(0, pos);
-        if (isInSVG) {
-          var rect = document.createElementNS("http://www.w3.org/2000/svg", "rect");
-          var bbox = node.parentElement.getBBox();
-          rect.x.baseVal.value = bbox.x;
-          rect.y.baseVal.value = bbox.y;
-          rect.width.baseVal.value = bbox.width;
-          rect.height.baseVal.value = bbox.height;
-          rect.setAttribute('class', className);
-          addItems.push({
-              "parent": node.parentNode,
-              "target": rect});
-        }
-      }
-    }
-    else if (!jQuery(node).is("button, select, textarea")) {
-      jQuery.each(node.childNodes, function() {
-        highlight(this, addItems);
-      });
-    }
-  }
-  var addItems = [];
-  var result = this.each(function() {
-    highlight(this, addItems);
-  });
-  for (var i = 0; i < addItems.length; ++i) {
-    jQuery(addItems[i].parent).before(addItems[i].target);
+"use strict";
+
+const BLACKLISTED_KEY_CONTROL_ELEMENTS = new Set([
+  "TEXTAREA",
+  "INPUT",
+  "SELECT",
+  "BUTTON",
+]);
+
+const _ready = (callback) => {
+  if (document.readyState !== "loading") {
+    callback();
+  } else {
+    document.addEventListener("DOMContentLoaded", callback);
   }
-  return result;
 };
 
-/*
- * backward compatibility for jQuery.browser
- * This will be supported until firefox bug is fixed.
- */
-if (!jQuery.browser) {
-  jQuery.uaMatch = function(ua) {
-    ua = ua.toLowerCase();
-
-    var match = /(chrome)[ \/]([\w.]+)/.exec(ua) ||
-      /(webkit)[ \/]([\w.]+)/.exec(ua) ||
-      /(opera)(?:.*version|)[ \/]([\w.]+)/.exec(ua) ||
-      /(msie) ([\w.]+)/.exec(ua) ||
-      ua.indexOf("compatible") < 0 && /(mozilla)(?:.*? rv:([\w.]+)|)/.exec(ua) ||
-      [];
-
-    return {
-      browser: match[ 1 ] || "",
-      version: match[ 2 ] || "0"
-    };
-  };
-  jQuery.browser = {};
-  jQuery.browser[jQuery.uaMatch(navigator.userAgent).browser] = true;
-}
-
 /**
  * Small JavaScript module for the documentation.
  */
-var Documentation = {
-
-  init : function() {
-    this.fixFirefoxAnchorBug();
-    this.highlightSearchWords();
-    this.initIndexTable();
-    this.initOnKeyListeners();
+const Documentation = {
+  init: () => {
+    Documentation.initDomainIndexTable();
+    Documentation.initOnKeyListeners();
   },
 
   /**
    * i18n support
    */
-  TRANSLATIONS : {},
-  PLURAL_EXPR : function(n) { return n === 1 ? 0 : 1; },
-  LOCALE : 'unknown',
+  TRANSLATIONS: {},
+  PLURAL_EXPR: (n) => (n === 1 ? 0 : 1),
+  LOCALE: "unknown",
 
   // gettext and ngettext don't access this so that the functions
   // can safely bound to a different name (_ = Documentation.gettext)
-  gettext : function(string) {
-    var translated = Documentation.TRANSLATIONS[string];
-    if (typeof translated === 'undefined')
-      return string;
-    return (typeof translated === 'string') ? translated : translated[0];
-  },
-
-  ngettext : function(singular, plural, n) {
-    var translated = Documentation.TRANSLATIONS[singular];
-    if (typeof translated === 'undefined')
-      return (n == 1) ? singular : plural;
-    return translated[Documentation.PLURALEXPR(n)];
-  },
-
-  addTranslations : function(catalog) {
-    for (var key in catalog.messages)
-      this.TRANSLATIONS[key] = catalog.messages[key];
-    this.PLURAL_EXPR = new Function('n', 'return +(' + catalog.plural_expr + ')');
-    this.LOCALE = catalog.locale;
-  },
-
-  /**
-   * add context elements like header anchor links
-   */
-  addContextElements : function() {
-    $('div[id] > :header:first').each(function() {
-      $('<a class="headerlink">\u00B6</a>').
-      attr('href', '#' + this.id).
-      attr('title', _('Permalink to this headline')).
-      appendTo(this);
-    });
-    $('dt[id]').each(function() {
-      $('<a class="headerlink">\u00B6</a>').
-      attr('href', '#' + this.id).
-      attr('title', _('Permalink to this definition')).
-      appendTo(this);
-    });
-  },
-
-  /**
-   * workaround a firefox stupidity
-   * see: https://bugzilla.mozilla.org/show_bug.cgi?id=645075
-   */
-  fixFirefoxAnchorBug : function() {
-    if (document.location.hash && $.browser.mozilla)
-      window.setTimeout(function() {
-        document.location.href += '';
-      }, 10);
-  },
-
-  /**
-   * highlight the search words provided in the url in the text
-   */
-  highlightSearchWords : function() {
-    var params = $.getQueryParameters();
-    var terms = (params.highlight) ? params.highlight[0].split(/\s+/) : [];
-    if (terms.length) {
-      var body = $('div.body');
-      if (!body.length) {
-        body = $('body');
-      }
-      window.setTimeout(function() {
-        $.each(terms, function() {
-          body.highlightText(this.toLowerCase(), 'highlighted');
-        });
-      }, 10);
-      $('<p class="highlight-link"><a href="javascript:Documentation.' +
-        'hideSearchWords()">' + _('Hide Search Matches') + '</a></p>')
-          .appendTo($('#searchbox'));
+  gettext: (string) => {
+    const translated = Documentation.TRANSLATIONS[string];
+    switch (typeof translated) {
+      case "undefined":
+        return string; // no translation
+      case "string":
+        return translated; // translation exists
+      default:
+        return translated[0]; // (singular, plural) translation tuple exists
     }
   },
 
-  /**
-   * init the domain index toggle buttons
-   */
-  initIndexTable : function() {
-    var togglers = $('img.toggler').click(function() {
-      var src = $(this).attr('src');
-      var idnum = $(this).attr('id').substr(7);
-      $('tr.cg-' + idnum).toggle();
-      if (src.substr(-9) === 'minus.png')
-        $(this).attr('src', src.substr(0, src.length-9) + 'plus.png');
-      else
-        $(this).attr('src', src.substr(0, src.length-8) + 'minus.png');
-    }).css('display', '');
-    if (DOCUMENTATION_OPTIONS.COLLAPSE_INDEX) {
-        togglers.click();
-    }
+  ngettext: (singular, plural, n) => {
+    const translated = Documentation.TRANSLATIONS[singular];
+    if (typeof translated !== "undefined")
+      return translated[Documentation.PLURAL_EXPR(n)];
+    return n === 1 ? singular : plural;
   },
 
-  /**
-   * helper function to hide the search marks again
-   */
-  hideSearchWords : function() {
-    $('#searchbox .highlight-link').fadeOut(300);
-    $('span.highlighted').removeClass('highlighted');
-    var url = new URL(window.location);
-    url.searchParams.delete('highlight');
-    window.history.replaceState({}, '', url);
+  addTranslations: (catalog) => {
+    Object.assign(Documentation.TRANSLATIONS, catalog.messages);
+    Documentation.PLURAL_EXPR = new Function(
+      "n",
+      `return (${catalog.plural_expr})`
+    );
+    Documentation.LOCALE = catalog.locale;
   },
 
-   /**
+  /**
    * helper function to focus on search bar
    */
-  focusSearchBar : function() {
-    $('input[name=q]').first().focus();
+  focusSearchBar: () => {
+    document.querySelectorAll("input[name=q]")[0]?.focus();
   },
 
   /**
-   * make the url absolute
+   * Initialise the domain index toggle buttons
    */
-  makeURL : function(relativeURL) {
-    return DOCUMENTATION_OPTIONS.URL_ROOT + '/' + relativeURL;
-  },
+  initDomainIndexTable: () => {
+    const toggler = (el) => {
+      const idNumber = el.id.substr(7);
+      const toggledRows = document.querySelectorAll(`tr.cg-${idNumber}`);
+      if (el.src.substr(-9) === "minus.png") {
+        el.src = `${el.src.substr(0, el.src.length - 9)}plus.png`;
+        toggledRows.forEach((el) => (el.style.display = "none"));
+      } else {
+        el.src = `${el.src.substr(0, el.src.length - 8)}minus.png`;
+        toggledRows.forEach((el) => (el.style.display = ""));
+      }
+    };
 
-  /**
-   * get the current relative url
-   */
-  getCurrentURL : function() {
-    var path = document.location.pathname;
-    var parts = path.split(/\//);
-    $.each(DOCUMENTATION_OPTIONS.URL_ROOT.split(/\//), function() {
-      if (this === '..')
-        parts.pop();
-    });
-    var url = parts.join('/');
-    return path.substring(url.lastIndexOf('/') + 1, path.length - 1);
+    const togglerElements = document.querySelectorAll("img.toggler");
+    togglerElements.forEach((el) =>
+      el.addEventListener("click", (event) => toggler(event.currentTarget))
+    );
+    togglerElements.forEach((el) => (el.style.display = ""));
+    if (DOCUMENTATION_OPTIONS.COLLAPSE_INDEX) togglerElements.forEach(toggler);
   },
 
-  initOnKeyListeners: function() {
+  initOnKeyListeners: () => {
     // only install a listener if it is really needed
-    if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS &&
-        !DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS)
-        return;
-
-    $(document).keydown(function(event) {
-      var activeElementType = document.activeElement.tagName;
-      // don't navigate when in search box, textarea, dropdown or button
-      if (activeElementType !== 'TEXTAREA' && activeElementType !== 'INPUT' && activeElementType !== 'SELECT'
-          && activeElementType !== 'BUTTON') {
-        if (event.altKey || event.ctrlKey || event.metaKey)
-          return;
-
-          if (!event.shiftKey) {
-            switch (event.key) {
-              case 'ArrowLeft':
-                if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS)
-                  break;
-                var prevHref = $('link[rel="prev"]').prop('href');
-                if (prevHref) {
-                  window.location.href = prevHref;
-                  return false;
-                }
-                break;
-              case 'ArrowRight':
-                if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS)
-                  break;
-                var nextHref = $('link[rel="next"]').prop('href');
-                if (nextHref) {
-                  window.location.href = nextHref;
-                  return false;
-                }
-                break;
-              case 'Escape':
-                if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS)
-                  break;
-                Documentation.hideSearchWords();
-                return false;
-          }
-        }
-
-        // some keyboard layouts may need Shift to get /
+    if (
+      !DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS &&
+      !DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS
+    )
+      return;
+
+    document.addEventListener("keydown", (event) => {
+      // bail for input elements
+      if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return;
+      // bail with special keys
+      if (event.altKey || event.ctrlKey || event.metaKey) return;
+
+      if (!event.shiftKey) {
         switch (event.key) {
-          case '/':
-            if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS)
-              break;
-            Documentation.focusSearchBar();
-            return false;
+          case "ArrowLeft":
+            if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break;
+
+            const prevLink = document.querySelector('link[rel="prev"]');
+            if (prevLink && prevLink.href) {
+              window.location.href = prevLink.href;
+              event.preventDefault();
+            }
+            break;
+          case "ArrowRight":
+            if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break;
+
+            const nextLink = document.querySelector('link[rel="next"]');
+            if (nextLink && nextLink.href) {
+              window.location.href = nextLink.href;
+              event.preventDefault();
+            }
+            break;
         }
       }
+
+      // some keyboard layouts may need Shift to get /
+      switch (event.key) {
+        case "/":
+          if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) break;
+          Documentation.focusSearchBar();
+          event.preventDefault();
+      }
     });
-  }
+  },
 };
 
 // quick alias for translations
-_ = Documentation.gettext;
+const _ = Documentation.gettext;
 
-$(document).ready(function() {
-  Documentation.init();
-});
+_ready(Documentation.init);
diff --git a/docs/_static/documentation_options.js b/docs/_static/documentation_options.js
index 8b727b33..0757e291 100644
--- a/docs/_static/documentation_options.js
+++ b/docs/_static/documentation_options.js
@@ -1,7 +1,7 @@
 var DOCUMENTATION_OPTIONS = {
     URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'),
-    VERSION: '2.2.0',
-    LANGUAGE: 'None',
+    VERSION: '2.3.0',
+    LANGUAGE: 'en',
     COLLAPSE_INDEX: false,
     BUILDER: 'html',
     FILE_SUFFIX: '.html',
diff --git a/docs/_static/language_data.js b/docs/_static/language_data.js
index ebe2f03b..250f5665 100644
--- a/docs/_static/language_data.js
+++ b/docs/_static/language_data.js
@@ -5,12 +5,12 @@
  * This script contains the language-specific data used by searchtools.js,
  * namely the list of stopwords, stemmer, scorer and splitter.
  *
- * :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS.
+ * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS.
  * :license: BSD, see LICENSE for details.
  *
  */
 
-var stopwords = ["a","and","are","as","at","be","but","by","for","if","in","into","is","it","near","no","not","of","on","or","such","that","the","their","then","there","these","they","this","to","was","will","with"];
+var stopwords = ["a", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "near", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"];
 
 
 /* Non-minified version is copied as a separate JS file, is available */
@@ -197,101 +197,3 @@ var Stemmer = function() {
   }
 }
 
-
-
-
-var splitChars = (function() {
-    var result = {};
-    var singles = [96, 180, 187, 191, 215, 247, 749, 885, 903, 907, 909, 930, 1014, 1648,
-         1748, 1809, 2416, 2473, 2481, 2526, 2601, 2609, 2612, 2615, 2653, 2702,
-         2706, 2729, 2737, 2740, 2857, 2865, 2868, 2910, 2928, 2948, 2961, 2971,
-         2973, 3085, 3089, 3113, 3124, 3213, 3217, 3241, 3252, 3295, 3341, 3345,
-         3369, 3506, 3516, 3633, 3715, 3721, 3736, 3744, 3748, 3750, 3756, 3761,
-         3781, 3912, 4239, 4347, 4681, 4695, 4697, 4745, 4785, 4799, 4801, 4823,
-         4881, 5760, 5901, 5997, 6313, 7405, 8024, 8026, 8028, 8030, 8117, 8125,
-         8133, 8181, 8468, 8485, 8487, 8489, 8494, 8527, 11311, 11359, 11687, 11695,
-         11703, 11711, 11719, 11727, 11735, 12448, 12539, 43010, 43014, 43019, 43587,
-         43696, 43713, 64286, 64297, 64311, 64317, 64319, 64322, 64325, 65141];
-    var i, j, start, end;
-    for (i = 0; i < singles.length; i++) {
-        result[singles[i]] = true;
-    }
-    var ranges = [[0, 47], [58, 64], [91, 94], [123, 169], [171, 177], [182, 184], [706, 709],
-         [722, 735], [741, 747], [751, 879], [888, 889], [894, 901], [1154, 1161],
-         [1318, 1328], [1367, 1368], [1370, 1376], [1416, 1487], [1515, 1519], [1523, 1568],
-         [1611, 1631], [1642, 1645], [1750, 1764], [1767, 1773], [1789, 1790], [1792, 1807],
-         [1840, 1868], [1958, 1968], [1970, 1983], [2027, 2035], [2038, 2041], [2043, 2047],
-         [2070, 2073], [2075, 2083], [2085, 2087], [2089, 2307], [2362, 2364], [2366, 2383],
-         [2385, 2391], [2402, 2405], [2419, 2424], [2432, 2436], [2445, 2446], [2449, 2450],
-         [2483, 2485], [2490, 2492], [2494, 2509], [2511, 2523], [2530, 2533], [2546, 2547],
-         [2554, 2564], [2571, 2574], [2577, 2578], [2618, 2648], [2655, 2661], [2672, 2673],
-         [2677, 2692], [2746, 2748], [2750, 2767], [2769, 2783], [2786, 2789], [2800, 2820],
-         [2829, 2830], [2833, 2834], [2874, 2876], [2878, 2907], [2914, 2917], [2930, 2946],
-         [2955, 2957], [2966, 2968], [2976, 2978], [2981, 2983], [2987, 2989], [3002, 3023],
-         [3025, 3045], [3059, 3076], [3130, 3132], [3134, 3159], [3162, 3167], [3170, 3173],
-         [3184, 3191], [3199, 3204], [3258, 3260], [3262, 3293], [3298, 3301], [3312, 3332],
-         [3386, 3388], [3390, 3423], [3426, 3429], [3446, 3449], [3456, 3460], [3479, 3481],
-         [3518, 3519], [3527, 3584], [3636, 3647], [3655, 3663], [3674, 3712], [3717, 3718],
-         [3723, 3724], [3726, 3731], [3752, 3753], [3764, 3772], [3774, 3775], [3783, 3791],
-         [3802, 3803], [3806, 3839], [3841, 3871], [3892, 3903], [3949, 3975], [3980, 4095],
-         [4139, 4158], [4170, 4175], [4182, 4185], [4190, 4192], [4194, 4196], [4199, 4205],
-         [4209, 4212], [4226, 4237], [4250, 4255], [4294, 4303], [4349, 4351], [4686, 4687],
-         [4702, 4703], [4750, 4751], [4790, 4791], [4806, 4807], [4886, 4887], [4955, 4968],
-         [4989, 4991], [5008, 5023], [5109, 5120], [5741, 5742], [5787, 5791], [5867, 5869],
-         [5873, 5887], [5906, 5919], [5938, 5951], [5970, 5983], [6001, 6015], [6068, 6102],
-         [6104, 6107], [6109, 6111], [6122, 6127], [6138, 6159], [6170, 6175], [6264, 6271],
-         [6315, 6319], [6390, 6399], [6429, 6469], [6510, 6511], [6517, 6527], [6572, 6592],
-         [6600, 6607], [6619, 6655], [6679, 6687], [6741, 6783], [6794, 6799], [6810, 6822],
-         [6824, 6916], [6964, 6980], [6988, 6991], [7002, 7042], [7073, 7085], [7098, 7167],
-         [7204, 7231], [7242, 7244], [7294, 7400], [7410, 7423], [7616, 7679], [7958, 7959],
-         [7966, 7967], [8006, 8007], [8014, 8015], [8062, 8063], [8127, 8129], [8141, 8143],
-         [8148, 8149], [8156, 8159], [8173, 8177], [8189, 8303], [8306, 8307], [8314, 8318],
-         [8330, 8335], [8341, 8449], [8451, 8454], [8456, 8457], [8470, 8472], [8478, 8483],
-         [8506, 8507], [8512, 8516], [8522, 8525], [8586, 9311], [9372, 9449], [9472, 10101],
-         [10132, 11263], [11493, 11498], [11503, 11516], [11518, 11519], [11558, 11567],
-         [11622, 11630], [11632, 11647], [11671, 11679], [11743, 11822], [11824, 12292],
-         [12296, 12320], [12330, 12336], [12342, 12343], [12349, 12352], [12439, 12444],
-         [12544, 12548], [12590, 12592], [12687, 12689], [12694, 12703], [12728, 12783],
-         [12800, 12831], [12842, 12880], [12896, 12927], [12938, 12976], [12992, 13311],
-         [19894, 19967], [40908, 40959], [42125, 42191], [42238, 42239], [42509, 42511],
-         [42540, 42559], [42592, 42593], [42607, 42622], [42648, 42655], [42736, 42774],
-         [42784, 42785], [42889, 42890], [42893, 43002], [43043, 43055], [43062, 43071],
-         [43124, 43137], [43188, 43215], [43226, 43249], [43256, 43258], [43260, 43263],
-         [43302, 43311], [43335, 43359], [43389, 43395], [43443, 43470], [43482, 43519],
-         [43561, 43583], [43596, 43599], [43610, 43615], [43639, 43641], [43643, 43647],
-         [43698, 43700], [43703, 43704], [43710, 43711], [43715, 43738], [43742, 43967],
-         [44003, 44015], [44026, 44031], [55204, 55215], [55239, 55242], [55292, 55295],
-         [57344, 63743], [64046, 64047], [64110, 64111], [64218, 64255], [64263, 64274],
-         [64280, 64284], [64434, 64466], [64830, 64847], [64912, 64913], [64968, 65007],
-         [65020, 65135], [65277, 65295], [65306, 65312], [65339, 65344], [65371, 65381],
-         [65471, 65473], [65480, 65481], [65488, 65489], [65496, 65497]];
-    for (i = 0; i < ranges.length; i++) {
-        start = ranges[i][0];
-        end = ranges[i][1];
-        for (j = start; j <= end; j++) {
-            result[j] = true;
-        }
-    }
-    return result;
-})();
-
-function splitQuery(query) {
-    var result = [];
-    var start = -1;
-    for (var i = 0; i < query.length; i++) {
-        if (splitChars[query.charCodeAt(i)]) {
-            if (start !== -1) {
-                result.push(query.slice(start, i));
-                start = -1;
-            }
-        } else if (start === -1) {
-            start = i;
-        }
-    }
-    if (start !== -1) {
-        result.push(query.slice(start));
-    }
-    return result;
-}
-
-
diff --git a/docs/_static/pygments.css b/docs/_static/pygments.css
index 582d5c3a..08bec689 100644
--- a/docs/_static/pygments.css
+++ b/docs/_static/pygments.css
@@ -5,22 +5,22 @@ td.linenos .special { color: #000000; background-color: #ffffc0; padding-left: 5
 span.linenos.special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; }
 .highlight .hll { background-color: #ffffcc }
 .highlight { background: #f8f8f8; }
-.highlight .c { color: #408080; font-style: italic } /* Comment */
+.highlight .c { color: #3D7B7B; font-style: italic } /* Comment */
 .highlight .err { border: 1px solid #FF0000 } /* Error */
 .highlight .k { color: #008000; font-weight: bold } /* Keyword */
 .highlight .o { color: #666666 } /* Operator */
-.highlight .ch { color: #408080; font-style: italic } /* Comment.Hashbang */
-.highlight .cm { color: #408080; font-style: italic } /* Comment.Multiline */
-.highlight .cp { color: #BC7A00 } /* Comment.Preproc */
-.highlight .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */
-.highlight .c1 { color: #408080; font-style: italic } /* Comment.Single */
-.highlight .cs { color: #408080; font-style: italic } /* Comment.Special */
+.highlight .ch { color: #3D7B7B; font-style: italic } /* Comment.Hashbang */
+.highlight .cm { color: #3D7B7B; font-style: italic } /* Comment.Multiline */
+.highlight .cp { color: #9C6500 } /* Comment.Preproc */
+.highlight .cpf { color: #3D7B7B; font-style: italic } /* Comment.PreprocFile */
+.highlight .c1 { color: #3D7B7B; font-style: italic } /* Comment.Single */
+.highlight .cs { color: #3D7B7B; font-style: italic } /* Comment.Special */
 .highlight .gd { color: #A00000 } /* Generic.Deleted */
 .highlight .ge { font-style: italic } /* Generic.Emph */
-.highlight .gr { color: #FF0000 } /* Generic.Error */
+.highlight .gr { color: #E40000 } /* Generic.Error */
 .highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
-.highlight .gi { color: #00A000 } /* Generic.Inserted */
-.highlight .go { color: #888888 } /* Generic.Output */
+.highlight .gi { color: #008400 } /* Generic.Inserted */
+.highlight .go { color: #717171 } /* Generic.Output */
 .highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
 .highlight .gs { font-weight: bold } /* Generic.Strong */
 .highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
@@ -33,15 +33,15 @@ span.linenos.special { color: #000000; background-color: #ffffc0; padding-left:
 .highlight .kt { color: #B00040 } /* Keyword.Type */
 .highlight .m { color: #666666 } /* Literal.Number */
 .highlight .s { color: #BA2121 } /* Literal.String */
-.highlight .na { color: #7D9029 } /* Name.Attribute */
+.highlight .na { color: #687822 } /* Name.Attribute */
 .highlight .nb { color: #008000 } /* Name.Builtin */
 .highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
 .highlight .no { color: #880000 } /* Name.Constant */
 .highlight .nd { color: #AA22FF } /* Name.Decorator */
-.highlight .ni { color: #999999; font-weight: bold } /* Name.Entity */
-.highlight .ne { color: #D2413A; font-weight: bold } /* Name.Exception */
+.highlight .ni { color: #717171; font-weight: bold } /* Name.Entity */
+.highlight .ne { color: #CB3F38; font-weight: bold } /* Name.Exception */
 .highlight .nf { color: #0000FF } /* Name.Function */
-.highlight .nl { color: #A0A000 } /* Name.Label */
+.highlight .nl { color: #767600 } /* Name.Label */
 .highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
 .highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
 .highlight .nv { color: #19177C } /* Name.Variable */
@@ -58,11 +58,11 @@ span.linenos.special { color: #000000; background-color: #ffffc0; padding-left:
 .highlight .dl { color: #BA2121 } /* Literal.String.Delimiter */
 .highlight .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */
 .highlight .s2 { color: #BA2121 } /* Literal.String.Double */
-.highlight .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */
+.highlight .se { color: #AA5D1F; font-weight: bold } /* Literal.String.Escape */
 .highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */
-.highlight .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */
+.highlight .si { color: #A45A77; font-weight: bold } /* Literal.String.Interpol */
 .highlight .sx { color: #008000 } /* Literal.String.Other */
-.highlight .sr { color: #BB6688 } /* Literal.String.Regex */
+.highlight .sr { color: #A45A77 } /* Literal.String.Regex */
 .highlight .s1 { color: #BA2121 } /* Literal.String.Single */
 .highlight .ss { color: #19177C } /* Literal.String.Symbol */
 .highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */
diff --git a/docs/_static/searchtools.js b/docs/_static/searchtools.js
index 0a44e858..97d56a74 100644
--- a/docs/_static/searchtools.js
+++ b/docs/_static/searchtools.js
@@ -4,22 +4,24 @@
  *
  * Sphinx JavaScript utilities for the full-text search.
  *
- * :copyright: Copyright 2007-2022 by the Sphinx team, see AUTHORS.
+ * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS.
  * :license: BSD, see LICENSE for details.
  *
  */
+"use strict";
 
-if (!Scorer) {
-  /**
-   * Simple result scoring code.
-   */
+/**
+ * Simple result scoring code.
+ */
+if (typeof Scorer === "undefined") {
   var Scorer = {
     // Implement the following function to further tweak the score for each result
-    // The function takes a result array [filename, title, anchor, descr, score]
+    // The function takes a result array [docname, title, anchor, descr, score, filename]
     // and returns the new score.
     /*
-    score: function(result) {
-      return result[4];
+    score: result => {
+      const [docname, title, anchor, descr, score, filename] = result
+      return score
     },
     */
 
@@ -28,9 +30,11 @@ if (!Scorer) {
     // or matches in the last dotted part of the object name
     objPartialMatch: 6,
     // Additive scores depending on the priority of the object
-    objPrio: {0:  15,   // used to be importantResults
-              1:  5,   // used to be objectResults
-              2: -5},  // used to be unimportantResults
+    objPrio: {
+      0: 15, // used to be importantResults
+      1: 5, // used to be objectResults
+      2: -5, // used to be unimportantResults
+    },
     //  Used when the priority is not in the mapping.
     objPrioDefault: 0,
 
@@ -39,452 +43,495 @@ if (!Scorer) {
     partialTitle: 7,
     // query found in terms
     term: 5,
-    partialTerm: 2
+    partialTerm: 2,
   };
 }
 
-if (!splitQuery) {
-  function splitQuery(query) {
-    return query.split(/\s+/);
+const _removeChildren = (element) => {
+  while (element && element.lastChild) element.removeChild(element.lastChild);
+};
+
+/**
+ * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions#escaping
+ */
+const _escapeRegExp = (string) =>
+  string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string
+
+const _displayItem = (item, searchTerms) => {
+  const docBuilder = DOCUMENTATION_OPTIONS.BUILDER;
+  const docUrlRoot = DOCUMENTATION_OPTIONS.URL_ROOT;
+  const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX;
+  const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX;
+  const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY;
+
+  const [docName, title, anchor, descr, score, _filename] = item;
+
+  let listItem = document.createElement("li");
+  let requestUrl;
+  let linkUrl;
+  if (docBuilder === "dirhtml") {
+    // dirhtml builder
+    let dirname = docName + "/";
+    if (dirname.match(/\/index\/$/))
+      dirname = dirname.substring(0, dirname.length - 6);
+    else if (dirname === "index/") dirname = "";
+    requestUrl = docUrlRoot + dirname;
+    linkUrl = requestUrl;
+  } else {
+    // normal html builders
+    requestUrl = docUrlRoot + docName + docFileSuffix;
+    linkUrl = docName + docLinkSuffix;
   }
+  let linkEl = listItem.appendChild(document.createElement("a"));
+  linkEl.href = linkUrl + anchor;
+  linkEl.dataset.score = score;
+  linkEl.innerHTML = title;
+  if (descr)
+    listItem.appendChild(document.createElement("span")).innerHTML =
+      " (" + descr + ")";
+  else if (showSearchSummary)
+    fetch(requestUrl)
+      .then((responseData) => responseData.text())
+      .then((data) => {
+        if (data)
+          listItem.appendChild(
+            Search.makeSearchSummary(data, searchTerms)
+          );
+      });
+  Search.output.appendChild(listItem);
+};
+const _finishSearch = (resultCount) => {
+  Search.stopPulse();
+  Search.title.innerText = _("Search Results");
+  if (!resultCount)
+    Search.status.innerText = Documentation.gettext(
+      "Your search did not match any documents. Please make sure that all words are spelled correctly and that you've selected enough categories."
+    );
+  else
+    Search.status.innerText = _(
+      `Search finished, found ${resultCount} page(s) matching the search query.`
+    );
+};
+const _displayNextItem = (
+  results,
+  resultCount,
+  searchTerms
+) => {
+  // results left, load the summary and display it
+  // this is intended to be dynamic (don't sub resultsCount)
+  if (results.length) {
+    _displayItem(results.pop(), searchTerms);
+    setTimeout(
+      () => _displayNextItem(results, resultCount, searchTerms),
+      5
+    );
+  }
+  // search finished, update title and status message
+  else _finishSearch(resultCount);
+};
+
+/**
+ * Default splitQuery function. Can be overridden in ``sphinx.search`` with a
+ * custom function per language.
+ *
+ * The regular expression works by splitting the string on consecutive characters
+ * that are not Unicode letters, numbers, underscores, or emoji characters.
+ * This is the same as ``\W+`` in Python, preserving the surrogate pair area.
+ */
+if (typeof splitQuery === "undefined") {
+  var splitQuery = (query) => query
+      .split(/[^\p{Letter}\p{Number}_\p{Emoji_Presentation}]+/gu)
+      .filter(term => term)  // remove remaining empty strings
 }
 
 /**
  * Search Module
  */
-var Search = {
-
-  _index : null,
-  _queued_query : null,
-  _pulse_status : -1,
-
-  htmlToText : function(htmlString) {
-      var virtualDocument = document.implementation.createHTMLDocument('virtual');
-      var htmlElement = $(htmlString, virtualDocument);
-      htmlElement.find('.headerlink').remove();
-      docContent = htmlElement.find('[role=main]')[0];
-      if(docContent === undefined) {
-          console.warn("Content block not found. Sphinx search tries to obtain it " +
-                       "via '[role=main]'. Could you check your theme or template.");
-          return "";
-      }
-      return docContent.textContent || docContent.innerText;
+const Search = {
+  _index: null,
+  _queued_query: null,
+  _pulse_status: -1,
+
+  htmlToText: (htmlString) => {
+    const htmlElement = new DOMParser().parseFromString(htmlString, 'text/html');
+    htmlElement.querySelectorAll(".headerlink").forEach((el) => { el.remove() });
+    const docContent = htmlElement.querySelector('[role="main"]');
+    if (docContent !== undefined) return docContent.textContent;
+    console.warn(
+      "Content block not found. Sphinx search tries to obtain it via '[role=main]'. Could you check your theme or template."
+    );
+    return "";
   },
 
-  init : function() {
-      var params = $.getQueryParameters();
-      if (params.q) {
-          var query = params.q[0];
-          $('input[name="q"]')[0].value = query;
-          this.performSearch(query);
-      }
+  init: () => {
+    const query = new URLSearchParams(window.location.search).get("q");
+    document
+      .querySelectorAll('input[name="q"]')
+      .forEach((el) => (el.value = query));
+    if (query) Search.performSearch(query);
   },
 
-  loadIndex : function(url) {
-    $.ajax({type: "GET", url: url, data: null,
-            dataType: "script", cache: true,
-            complete: function(jqxhr, textstatus) {
-              if (textstatus != "success") {
-                document.getElementById("searchindexloader").src = url;
-              }
-            }});
-  },
+  loadIndex: (url) =>
+    (document.body.appendChild(document.createElement("script")).src = url),
 
-  setIndex : function(index) {
-    var q;
-    this._index = index;
-    if ((q = this._queued_query) !== null) {
-      this._queued_query = null;
-      Search.query(q);
+  setIndex: (index) => {
+    Search._index = index;
+    if (Search._queued_query !== null) {
+      const query = Search._queued_query;
+      Search._queued_query = null;
+      Search.query(query);
     }
   },
 
-  hasIndex : function() {
-      return this._index !== null;
-  },
+  hasIndex: () => Search._index !== null,
 
-  deferQuery : function(query) {
-      this._queued_query = query;
-  },
+  deferQuery: (query) => (Search._queued_query = query),
 
-  stopPulse : function() {
-      this._pulse_status = 0;
-  },
+  stopPulse: () => (Search._pulse_status = -1),
 
-  startPulse : function() {
-    if (this._pulse_status >= 0)
-        return;
-    function pulse() {
-      var i;
+  startPulse: () => {
+    if (Search._pulse_status >= 0) return;
+
+    const pulse = () => {
       Search._pulse_status = (Search._pulse_status + 1) % 4;
-      var dotString = '';
-      for (i = 0; i < Search._pulse_status; i++)
-        dotString += '.';
-      Search.dots.text(dotString);
-      if (Search._pulse_status > -1)
-        window.setTimeout(pulse, 500);
-    }
+      Search.dots.innerText = ".".repeat(Search._pulse_status);
+      if (Search._pulse_status >= 0) window.setTimeout(pulse, 500);
+    };
     pulse();
   },
 
   /**
    * perform a search for something (or wait until index is loaded)
    */
-  performSearch : function(query) {
+  performSearch: (query) => {
     // create the required interface elements
-    this.out = $('#search-results');
-    this.title = $('<h2>' + _('Searching') + '</h2>').appendTo(this.out);
-    this.dots = $('<span></span>').appendTo(this.title);
-    this.status = $('<p class="search-summary">&nbsp;</p>').appendTo(this.out);
-    this.output = $('<ul class="search"/>').appendTo(this.out);
-
-    $('#search-progress').text(_('Preparing search...'));
-    this.startPulse();
+    const searchText = document.createElement("h2");
+    searchText.textContent = _("Searching");
+    const searchSummary = document.createElement("p");
+    searchSummary.classList.add("search-summary");
+    searchSummary.innerText = "";
+    const searchList = document.createElement("ul");
+    searchList.classList.add("search");
+
+    const out = document.getElementById("search-results");
+    Search.title = out.appendChild(searchText);
+    Search.dots = Search.title.appendChild(document.createElement("span"));
+    Search.status = out.appendChild(searchSummary);
+    Search.output = out.appendChild(searchList);
+
+    const searchProgress = document.getElementById("search-progress");
+    // Some themes don't use the search progress node
+    if (searchProgress) {
+      searchProgress.innerText = _("Preparing search...");
+    }
+    Search.startPulse();
 
     // index already loaded, the browser was quick!
-    if (this.hasIndex())
-      this.query(query);
-    else
-      this.deferQuery(query);
+    if (Search.hasIndex()) Search.query(query);
+    else Search.deferQuery(query);
   },
 
   /**
    * execute search (requires search index to be loaded)
    */
-  query : function(query) {
-    var i;
-
-    // stem the searchterms and add them to the correct list
-    var stemmer = new Stemmer();
-    var searchterms = [];
-    var excluded = [];
-    var hlterms = [];
-    var tmp = splitQuery(query);
-    var objectterms = [];
-    for (i = 0; i < tmp.length; i++) {
-      if (tmp[i] !== "") {
-          objectterms.push(tmp[i].toLowerCase());
-      }
+  query: (query) => {
+    const filenames = Search._index.filenames;
+    const docNames = Search._index.docnames;
+    const titles = Search._index.titles;
+    const allTitles = Search._index.alltitles;
+    const indexEntries = Search._index.indexentries;
+
+    // stem the search terms and add them to the correct list
+    const stemmer = new Stemmer();
+    const searchTerms = new Set();
+    const excludedTerms = new Set();
+    const highlightTerms = new Set();
+    const objectTerms = new Set(splitQuery(query.toLowerCase().trim()));
+    splitQuery(query.trim()).forEach((queryTerm) => {
+      const queryTermLower = queryTerm.toLowerCase();
+
+      // maybe skip this "word"
+      // stopwords array is from language_data.js
+      if (
+        stopwords.indexOf(queryTermLower) !== -1 ||
+        queryTerm.match(/^\d+$/)
+      )
+        return;
 
-      if ($u.indexOf(stopwords, tmp[i].toLowerCase()) != -1 || tmp[i] === "") {
-        // skip this "word"
-        continue;
-      }
       // stem the word
-      var word = stemmer.stemWord(tmp[i].toLowerCase());
-      var toAppend;
+      let word = stemmer.stemWord(queryTermLower);
       // select the correct list
-      if (word[0] == '-') {
-        toAppend = excluded;
-        word = word.substr(1);
-      }
+      if (word[0] === "-") excludedTerms.add(word.substr(1));
       else {
-        toAppend = searchterms;
-        hlterms.push(tmp[i].toLowerCase());
+        searchTerms.add(word);
+        highlightTerms.add(queryTermLower);
       }
-      // only add if not already in the list
-      if (!$u.contains(toAppend, word))
-        toAppend.push(word);
-    }
-    var highlightstring = '?highlight=' + $.urlencode(hlterms.join(" "));
+    });
 
-    // console.debug('SEARCH: searching for:');
-    // console.info('required: ', searchterms);
-    // console.info('excluded: ', excluded);
+    if (SPHINX_HIGHLIGHT_ENABLED) {  // set in sphinx_highlight.js
+      localStorage.setItem("sphinx_highlight_terms", [...highlightTerms].join(" "))
+    }
 
-    // prepare search
-    var terms = this._index.terms;
-    var titleterms = this._index.titleterms;
+    // console.debug("SEARCH: searching for:");
+    // console.info("required: ", [...searchTerms]);
+    // console.info("excluded: ", [...excludedTerms]);
+
+    // array of [docname, title, anchor, descr, score, filename]
+    let results = [];
+    _removeChildren(document.getElementById("search-progress"));
+
+    const queryLower = query.toLowerCase();
+    for (const [title, foundTitles] of Object.entries(allTitles)) {
+      if (title.toLowerCase().includes(queryLower) && (queryLower.length >= title.length/2)) {
+        for (const [file, id] of foundTitles) {
+          let score = Math.round(100 * queryLower.length / title.length)
+          results.push([
+            docNames[file],
+            titles[file] !== title ? `${titles[file]} > ${title}` : title,
+            id !== null ? "#" + id : "",
+            null,
+            score,
+            filenames[file],
+          ]);
+        }
+      }
+    }
 
-    // array of [filename, title, anchor, descr, score]
-    var results = [];
-    $('#search-progress').empty();
+    // search for explicit entries in index directives
+    for (const [entry, foundEntries] of Object.entries(indexEntries)) {
+      if (entry.includes(queryLower) && (queryLower.length >= entry.length/2)) {
+        for (const [file, id] of foundEntries) {
+          let score = Math.round(100 * queryLower.length / entry.length)
+          results.push([
+            docNames[file],
+            titles[file],
+            id ? "#" + id : "",
+            null,
+            score,
+            filenames[file],
+          ]);
+        }
+      }
+    }
 
     // lookup as object
-    for (i = 0; i < objectterms.length; i++) {
-      var others = [].concat(objectterms.slice(0, i),
-                             objectterms.slice(i+1, objectterms.length));
-      results = results.concat(this.performObjectSearch(objectterms[i], others));
-    }
+    objectTerms.forEach((term) =>
+      results.push(...Search.performObjectSearch(term, objectTerms))
+    );
 
     // lookup as search terms in fulltext
-    results = results.concat(this.performTermsSearch(searchterms, excluded, terms, titleterms));
+    results.push(...Search.performTermsSearch(searchTerms, excludedTerms));
 
     // let the scorer override scores with a custom scoring function
-    if (Scorer.score) {
-      for (i = 0; i < results.length; i++)
-        results[i][4] = Scorer.score(results[i]);
-    }
+    if (Scorer.score) results.forEach((item) => (item[4] = Scorer.score(item)));
 
     // now sort the results by score (in opposite order of appearance, since the
     // display function below uses pop() to retrieve items) and then
     // alphabetically
-    results.sort(function(a, b) {
-      var left = a[4];
-      var right = b[4];
-      if (left > right) {
-        return 1;
-      } else if (left < right) {
-        return -1;
-      } else {
+    results.sort((a, b) => {
+      const leftScore = a[4];
+      const rightScore = b[4];
+      if (leftScore === rightScore) {
         // same score: sort alphabetically
-        left = a[1].toLowerCase();
-        right = b[1].toLowerCase();
-        return (left > right) ? -1 : ((left < right) ? 1 : 0);
+        const leftTitle = a[1].toLowerCase();
+        const rightTitle = b[1].toLowerCase();
+        if (leftTitle === rightTitle) return 0;
+        return leftTitle > rightTitle ? -1 : 1; // inverted is intentional
       }
+      return leftScore > rightScore ? 1 : -1;
     });
 
+    // remove duplicate search results
+    // note the reversing of results, so that in the case of duplicates, the highest-scoring entry is kept
+    let seen = new Set();
+    results = results.reverse().reduce((acc, result) => {
+      let resultStr = result.slice(0, 4).concat([result[5]]).map(v => String(v)).join(',');
+      if (!seen.has(resultStr)) {
+        acc.push(result);
+        seen.add(resultStr);
+      }
+      return acc;
+    }, []);
+
+    results = results.reverse();
+
     // for debugging
     //Search.lastresults = results.slice();  // a copy
-    //console.info('search results:', Search.lastresults);
+    // console.info("search results:", Search.lastresults);
 
     // print the results
-    var resultCount = results.length;
-    function displayNextItem() {
-      // results left, load the summary and display it
-      if (results.length) {
-        var item = results.pop();
-        var listItem = $('<li></li>');
-        var requestUrl = "";
-        var linkUrl = "";
-        if (DOCUMENTATION_OPTIONS.BUILDER === 'dirhtml') {
-          // dirhtml builder
-          var dirname = item[0] + '/';
-          if (dirname.match(/\/index\/$/)) {
-            dirname = dirname.substring(0, dirname.length-6);
-          } else if (dirname == 'index/') {
-            dirname = '';
-          }
-          requestUrl = DOCUMENTATION_OPTIONS.URL_ROOT + dirname;
-          linkUrl = requestUrl;
-
-        } else {
-          // normal html builders
-          requestUrl = DOCUMENTATION_OPTIONS.URL_ROOT + item[0] + DOCUMENTATION_OPTIONS.FILE_SUFFIX;
-          linkUrl = item[0] + DOCUMENTATION_OPTIONS.LINK_SUFFIX;
-        }
-        listItem.append($('<a/>').attr('href',
-            linkUrl +
-            highlightstring + item[2]).html(item[1]));
-        if (item[3]) {
-          listItem.append($('<span> (' + item[3] + ')</span>'));
-          Search.output.append(listItem);
-          setTimeout(function() {
-            displayNextItem();
-          }, 5);
-        } else if (DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY) {
-          $.ajax({url: requestUrl,
-                  dataType: "text",
-                  complete: function(jqxhr, textstatus) {
-                    var data = jqxhr.responseText;
-                    if (data !== '' && data !== undefined) {
-                      var summary = Search.makeSearchSummary(data, searchterms, hlterms);
-                      if (summary) {
-                        listItem.append(summary);
-                      }
-                    }
-                    Search.output.append(listItem);
-                    setTimeout(function() {
-                      displayNextItem();
-                    }, 5);
-                  }});
-        } else {
-          // just display title
-          Search.output.append(listItem);
-          setTimeout(function() {
-            displayNextItem();
-          }, 5);
-        }
-      }
-      // search finished, update title and status message
-      else {
-        Search.stopPulse();
-        Search.title.text(_('Search Results'));
-        if (!resultCount)
-          Search.status.text(_('Your search did not match any documents. Please make sure that all words are spelled correctly and that you\'ve selected enough categories.'));
-        else
-            Search.status.text(_('Search finished, found %s page(s) matching the search query.').replace('%s', resultCount));
-        Search.status.fadeIn(500);
-      }
-    }
-    displayNextItem();
+    _displayNextItem(results, results.length, searchTerms);
   },
 
   /**
    * search for object names
    */
-  performObjectSearch : function(object, otherterms) {
-    var filenames = this._index.filenames;
-    var docnames = this._index.docnames;
-    var objects = this._index.objects;
-    var objnames = this._index.objnames;
-    var titles = this._index.titles;
-
-    var i;
-    var results = [];
-
-    for (var prefix in objects) {
-      for (var iMatch = 0; iMatch != objects[prefix].length; ++iMatch) {
-        var match = objects[prefix][iMatch];
-        var name = match[4];
-        var fullname = (prefix ? prefix + '.' : '') + name;
-        var fullnameLower = fullname.toLowerCase()
-        if (fullnameLower.indexOf(object) > -1) {
-          var score = 0;
-          var parts = fullnameLower.split('.');
-          // check for different match types: exact matches of full name or
-          // "last name" (i.e. last dotted part)
-          if (fullnameLower == object || parts[parts.length - 1] == object) {
-            score += Scorer.objNameMatch;
-          // matches in last name
-          } else if (parts[parts.length - 1].indexOf(object) > -1) {
-            score += Scorer.objPartialMatch;
-          }
-          var objname = objnames[match[1]][2];
-          var title = titles[match[0]];
-          // If more than one term searched for, we require other words to be
-          // found in the name/title/description
-          if (otherterms.length > 0) {
-            var haystack = (prefix + ' ' + name + ' ' +
-                            objname + ' ' + title).toLowerCase();
-            var allfound = true;
-            for (i = 0; i < otherterms.length; i++) {
-              if (haystack.indexOf(otherterms[i]) == -1) {
-                allfound = false;
-                break;
-              }
-            }
-            if (!allfound) {
-              continue;
-            }
-          }
-          var descr = objname + _(', in ') + title;
-
-          var anchor = match[3];
-          if (anchor === '')
-            anchor = fullname;
-          else if (anchor == '-')
-            anchor = objnames[match[1]][1] + '-' + fullname;
-          // add custom score for some objects according to scorer
-          if (Scorer.objPrio.hasOwnProperty(match[2])) {
-            score += Scorer.objPrio[match[2]];
-          } else {
-            score += Scorer.objPrioDefault;
-          }
-          results.push([docnames[match[0]], fullname, '#'+anchor, descr, score, filenames[match[0]]]);
-        }
+  performObjectSearch: (object, objectTerms) => {
+    const filenames = Search._index.filenames;
+    const docNames = Search._index.docnames;
+    const objects = Search._index.objects;
+    const objNames = Search._index.objnames;
+    const titles = Search._index.titles;
+
+    const results = [];
+
+    const objectSearchCallback = (prefix, match) => {
+      const name = match[4]
+      const fullname = (prefix ? prefix + "." : "") + name;
+      const fullnameLower = fullname.toLowerCase();
+      if (fullnameLower.indexOf(object) < 0) return;
+
+      let score = 0;
+      const parts = fullnameLower.split(".");
+
+      // check for different match types: exact matches of full name or
+      // "last name" (i.e. last dotted part)
+      if (fullnameLower === object || parts.slice(-1)[0] === object)
+        score += Scorer.objNameMatch;
+      else if (parts.slice(-1)[0].indexOf(object) > -1)
+        score += Scorer.objPartialMatch; // matches in last name
+
+      const objName = objNames[match[1]][2];
+      const title = titles[match[0]];
+
+      // If more than one term searched for, we require other words to be
+      // found in the name/title/description
+      const otherTerms = new Set(objectTerms);
+      otherTerms.delete(object);
+      if (otherTerms.size > 0) {
+        const haystack = `${prefix} ${name} ${objName} ${title}`.toLowerCase();
+        if (
+          [...otherTerms].some((otherTerm) => haystack.indexOf(otherTerm) < 0)
+        )
+          return;
       }
-    }
 
+      let anchor = match[3];
+      if (anchor === "") anchor = fullname;
+      else if (anchor === "-") anchor = objNames[match[1]][1] + "-" + fullname;
+
+      const descr = objName + _(", in ") + title;
+
+      // add custom score for some objects according to scorer
+      if (Scorer.objPrio.hasOwnProperty(match[2]))
+        score += Scorer.objPrio[match[2]];
+      else score += Scorer.objPrioDefault;
+
+      results.push([
+        docNames[match[0]],
+        fullname,
+        "#" + anchor,
+        descr,
+        score,
+        filenames[match[0]],
+      ]);
+    };
+    Object.keys(objects).forEach((prefix) =>
+      objects[prefix].forEach((array) =>
+        objectSearchCallback(prefix, array)
+      )
+    );
     return results;
   },
 
-  /**
-   * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions
-   */
-  escapeRegExp : function(string) {
-    return string.replace(/[.*+\-?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string
-  },
-
   /**
    * search for full-text terms in the index
    */
-  performTermsSearch : function(searchterms, excluded, terms, titleterms) {
-    var docnames = this._index.docnames;
-    var filenames = this._index.filenames;
-    var titles = this._index.titles;
+  performTermsSearch: (searchTerms, excludedTerms) => {
+    // prepare search
+    const terms = Search._index.terms;
+    const titleTerms = Search._index.titleterms;
+    const filenames = Search._index.filenames;
+    const docNames = Search._index.docnames;
+    const titles = Search._index.titles;
 
-    var i, j, file;
-    var fileMap = {};
-    var scoreMap = {};
-    var results = [];
+    const scoreMap = new Map();
+    const fileMap = new Map();
 
     // perform the search on the required terms
-    for (i = 0; i < searchterms.length; i++) {
-      var word = searchterms[i];
-      var files = [];
-      var _o = [
-        {files: terms[word], score: Scorer.term},
-        {files: titleterms[word], score: Scorer.title}
+    searchTerms.forEach((word) => {
+      const files = [];
+      const arr = [
+        { files: terms[word], score: Scorer.term },
+        { files: titleTerms[word], score: Scorer.title },
       ];
       // add support for partial matches
       if (word.length > 2) {
-        var word_regex = this.escapeRegExp(word);
-        for (var w in terms) {
-          if (w.match(word_regex) && !terms[word]) {
-            _o.push({files: terms[w], score: Scorer.partialTerm})
-          }
-        }
-        for (var w in titleterms) {
-          if (w.match(word_regex) && !titleterms[word]) {
-              _o.push({files: titleterms[w], score: Scorer.partialTitle})
-          }
-        }
+        const escapedWord = _escapeRegExp(word);
+        Object.keys(terms).forEach((term) => {
+          if (term.match(escapedWord) && !terms[word])
+            arr.push({ files: terms[term], score: Scorer.partialTerm });
+        });
+        Object.keys(titleTerms).forEach((term) => {
+          if (term.match(escapedWord) && !titleTerms[word])
+            arr.push({ files: titleTerms[word], score: Scorer.partialTitle });
+        });
       }
 
       // no match but word was a required one
-      if ($u.every(_o, function(o){return o.files === undefined;})) {
-        break;
-      }
+      if (arr.every((record) => record.files === undefined)) return;
+
       // found search word in contents
-      $u.each(_o, function(o) {
-        var _files = o.files;
-        if (_files === undefined)
-          return
-
-        if (_files.length === undefined)
-          _files = [_files];
-        files = files.concat(_files);
-
-        // set score for the word in each file to Scorer.term
-        for (j = 0; j < _files.length; j++) {
-          file = _files[j];
-          if (!(file in scoreMap))
-            scoreMap[file] = {};
-          scoreMap[file][word] = o.score;
-        }
+      arr.forEach((record) => {
+        if (record.files === undefined) return;
+
+        let recordFiles = record.files;
+        if (recordFiles.length === undefined) recordFiles = [recordFiles];
+        files.push(...recordFiles);
+
+        // set score for the word in each file
+        recordFiles.forEach((file) => {
+          if (!scoreMap.has(file)) scoreMap.set(file, {});
+          scoreMap.get(file)[word] = record.score;
+        });
       });
 
       // create the mapping
-      for (j = 0; j < files.length; j++) {
-        file = files[j];
-        if (file in fileMap && fileMap[file].indexOf(word) === -1)
-          fileMap[file].push(word);
-        else
-          fileMap[file] = [word];
-      }
-    }
+      files.forEach((file) => {
+        if (fileMap.has(file) && fileMap.get(file).indexOf(word) === -1)
+          fileMap.get(file).push(word);
+        else fileMap.set(file, [word]);
+      });
+    });
 
     // now check if the files don't contain excluded terms
-    for (file in fileMap) {
-      var valid = true;
-
+    const results = [];
+    for (const [file, wordList] of fileMap) {
       // check if all requirements are matched
-      var filteredTermCount = // as search terms with length < 3 are discarded: ignore
-        searchterms.filter(function(term){return term.length > 2}).length
+
+      // as search terms with length < 3 are discarded
+      const filteredTermCount = [...searchTerms].filter(
+        (term) => term.length > 2
+      ).length;
       if (
-        fileMap[file].length != searchterms.length &&
-        fileMap[file].length != filteredTermCount
-      ) continue;
+        wordList.length !== searchTerms.size &&
+        wordList.length !== filteredTermCount
+      )
+        continue;
 
       // ensure that none of the excluded terms is in the search result
-      for (i = 0; i < excluded.length; i++) {
-        if (terms[excluded[i]] == file ||
-            titleterms[excluded[i]] == file ||
-            $u.contains(terms[excluded[i]] || [], file) ||
-            $u.contains(titleterms[excluded[i]] || [], file)) {
-          valid = false;
-          break;
-        }
-      }
+      if (
+        [...excludedTerms].some(
+          (term) =>
+            terms[term] === file ||
+            titleTerms[term] === file ||
+            (terms[term] || []).includes(file) ||
+            (titleTerms[term] || []).includes(file)
+        )
+      )
+        break;
 
-      // if we have still a valid result we can add it to the result list
-      if (valid) {
-        // select one (max) score for the file.
-        // for better ranking, we should calculate ranking by using words statistics like basic tf-idf...
-        var score = $u.max($u.map(fileMap[file], function(w){return scoreMap[file][w]}));
-        results.push([docnames[file], titles[file], '', null, score, filenames[file]]);
-      }
+      // select one (max) score for the file.
+      const score = Math.max(...wordList.map((w) => scoreMap.get(file)[w]));
+      // add result to the result list
+      results.push([
+        docNames[file],
+        titles[file],
+        "",
+        null,
+        score,
+        filenames[file],
+      ]);
     }
     return results;
   },
@@ -492,34 +539,28 @@ var Search = {
   /**
    * helper function to return a node containing the
    * search summary for a given text. keywords is a list
-   * of stemmed words, hlwords is the list of normal, unstemmed
-   * words. the first one is used to find the occurrence, the
-   * latter for highlighting it.
+   * of stemmed words.
    */
-  makeSearchSummary : function(htmlText, keywords, hlwords) {
-    var text = Search.htmlToText(htmlText);
-    if (text == "") {
-      return null;
-    }
-    var textLower = text.toLowerCase();
-    var start = 0;
-    $.each(keywords, function() {
-      var i = textLower.indexOf(this.toLowerCase());
-      if (i > -1)
-        start = i;
-    });
-    start = Math.max(start - 120, 0);
-    var excerpt = ((start > 0) ? '...' : '') +
-      $.trim(text.substr(start, 240)) +
-      ((start + 240 - text.length) ? '...' : '');
-    var rv = $('<p class="context"></p>').text(excerpt);
-    $.each(hlwords, function() {
-      rv = rv.highlightText(this, 'highlighted');
-    });
-    return rv;
-  }
+  makeSearchSummary: (htmlText, keywords) => {
+    const text = Search.htmlToText(htmlText);
+    if (text === "") return null;
+
+    const textLower = text.toLowerCase();
+    const actualStartPosition = [...keywords]
+      .map((k) => textLower.indexOf(k.toLowerCase()))
+      .filter((i) => i > -1)
+      .slice(-1)[0];
+    const startWithContext = Math.max(actualStartPosition - 120, 0);
+
+    const top = startWithContext === 0 ? "" : "...";
+    const tail = startWithContext + 240 < text.length ? "..." : "";
+
+    let summary = document.createElement("p");
+    summary.classList.add("context");
+    summary.textContent = top + text.substr(startWithContext, 240).trim() + tail;
+
+    return summary;
+  },
 };
 
-$(document).ready(function() {
-  Search.init();
-});
+_ready(Search.init);
diff --git a/docs/_static/sphinx_highlight.js b/docs/_static/sphinx_highlight.js
new file mode 100644
index 00000000..aae669d7
--- /dev/null
+++ b/docs/_static/sphinx_highlight.js
@@ -0,0 +1,144 @@
+/* Highlighting utilities for Sphinx HTML documentation. */
+"use strict";
+
+const SPHINX_HIGHLIGHT_ENABLED = true
+
+/**
+ * highlight a given string on a node by wrapping it in
+ * span elements with the given class name.
+ */
+const _highlight = (node, addItems, text, className) => {
+  if (node.nodeType === Node.TEXT_NODE) {
+    const val = node.nodeValue;
+    const parent = node.parentNode;
+    const pos = val.toLowerCase().indexOf(text);
+    if (
+      pos >= 0 &&
+      !parent.classList.contains(className) &&
+      !parent.classList.contains("nohighlight")
+    ) {
+      let span;
+
+      const closestNode = parent.closest("body, svg, foreignObject");
+      const isInSVG = closestNode && closestNode.matches("svg");
+      if (isInSVG) {
+        span = document.createElementNS("http://www.w3.org/2000/svg", "tspan");
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+        span.classList.add(className);
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+
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+        span,
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+          document.createTextNode(val.substr(pos + text.length)),
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+        )
+      );
+      node.nodeValue = val.substr(0, pos);
+
+      if (isInSVG) {
+        const rect = document.createElementNS(
+          "http://www.w3.org/2000/svg",
+          "rect"
+        );
+        const bbox = parent.getBBox();
+        rect.x.baseVal.value = bbox.x;
+        rect.y.baseVal.value = bbox.y;
+        rect.width.baseVal.value = bbox.width;
+        rect.height.baseVal.value = bbox.height;
+        rect.setAttribute("class", className);
+        addItems.push({ parent: parent, target: rect });
+      }
+    }
+  } else if (node.matches && !node.matches("button, select, textarea")) {
+    node.childNodes.forEach((el) => _highlight(el, addItems, text, className));
+  }
+};
+const _highlightText = (thisNode, text, className) => {
+  let addItems = [];
+  _highlight(thisNode, addItems, text, className);
+  addItems.forEach((obj) =>
+    obj.parent.insertAdjacentElement("beforebegin", obj.target)
+  );
+};
+
+/**
+ * Small JavaScript module for the documentation.
+ */
+const SphinxHighlight = {
+
+  /**
+   * highlight the search words provided in localstorage in the text
+   */
+  highlightSearchWords: () => {
+    if (!SPHINX_HIGHLIGHT_ENABLED) return;  // bail if no highlight
+
+    // get and clear terms from localstorage
+    const url = new URL(window.location);
+    const highlight =
+        localStorage.getItem("sphinx_highlight_terms")
+        || url.searchParams.get("highlight")
+        || "";
+    localStorage.removeItem("sphinx_highlight_terms")
+    url.searchParams.delete("highlight");
+    window.history.replaceState({}, "", url);
+
+    // get individual terms from highlight string
+    const terms = highlight.toLowerCase().split(/\s+/).filter(x => x);
+    if (terms.length === 0) return; // nothing to do
+
+    // There should never be more than one element matching "div.body"
+    const divBody = document.querySelectorAll("div.body");
+    const body = divBody.length ? divBody[0] : document.querySelector("body");
+    window.setTimeout(() => {
+      terms.forEach((term) => _highlightText(body, term, "highlighted"));
+    }, 10);
+
+    const searchBox = document.getElementById("searchbox");
+    if (searchBox === null) return;
+    searchBox.appendChild(
+      document
+        .createRange()
+        .createContextualFragment(
+          '<p class="highlight-link">' +
+            '<a href="javascript:SphinxHighlight.hideSearchWords()">' +
+            _("Hide Search Matches") +
+            "</a></p>"
+        )
+    );
+  },
+
+  /**
+   * helper function to hide the search marks again
+   */
+  hideSearchWords: () => {
+    document
+      .querySelectorAll("#searchbox .highlight-link")
+      .forEach((el) => el.remove());
+    document
+      .querySelectorAll("span.highlighted")
+      .forEach((el) => el.classList.remove("highlighted"));
+    localStorage.removeItem("sphinx_highlight_terms")
+  },
+
+  initEscapeListener: () => {
+    // only install a listener if it is really needed
+    if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return;
+
+    document.addEventListener("keydown", (event) => {
+      // bail for input elements
+      if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return;
+      // bail with special keys
+      if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) return;
+      if (DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS && (event.key === "Escape")) {
+        SphinxHighlight.hideSearchWords();
+        event.preventDefault();
+      }
+    });
+  },
+};
+
+_ready(SphinxHighlight.highlightSearchWords);
+_ready(SphinxHighlight.initEscapeListener);
diff --git a/docs/api.html b/docs/api.html
index cc456af1..333b327f 100644
--- a/docs/api.html
+++ b/docs/api.html
@@ -1,10 +1,10 @@
 <!DOCTYPE html>
 <html class="writer-html5" lang="en" >
 <head>
-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
+  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>API References &mdash; impy 2.2.0 documentation</title>
+  <title>API References &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -12,9 +12,8 @@
   <![endif]-->
   
         <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
-        <script src="_static/jquery.js"></script>
-        <script src="_static/underscore.js"></script>
         <script src="_static/doctools.js"></script>
+        <script src="_static/sphinx_highlight.js"></script>
     <script src="_static/js/theme.js"></script>
     <link rel="index" title="Index" href="genindex.html" />
     <link rel="search" title="Search" href="search.html" />
@@ -27,14 +26,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -66,8 +69,8 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="index.html" class="icon icon-home"></a> &raquo;</li>
-      <li>API References</li>
+      <li><a href="index.html" class="icon icon-home" aria-label="Home"></a></li>
+      <li class="breadcrumb-item active">API References</li>
       <li class="wy-breadcrumbs-aside">
             <a href="_sources/api.rst.txt" rel="nofollow"> View page source</a>
       </li>
@@ -78,7 +81,7 @@
            <div itemprop="articleBody">
              
   <section id="api-references">
-<h1>API References<a class="headerlink" href="#api-references" title="Permalink to this headline">¶</a></h1>
+<h1>API References<a class="headerlink" href="#api-references" title="Permalink to this heading">¶</a></h1>
 <div class="toctree-wrapper compound">
 <p class="caption" role="heading"><span class="caption-text">Contents:</span></p>
 <ul>
@@ -107,6 +110,7 @@ <h1>API References<a class="headerlink" href="#api-references" title="Permalink
 <li class="toctree-l2"><a class="reference internal" href="apidoc/impy.arrays.html#module-impy.arrays.lazy">impy.arrays.lazy module</a></li>
 <li class="toctree-l2"><a class="reference internal" href="apidoc/impy.arrays.html#module-impy.arrays.phasearray">impy.arrays.phasearray module</a></li>
 <li class="toctree-l2"><a class="reference internal" href="apidoc/impy.arrays.html#module-impy.arrays.specials">impy.arrays.specials module</a></li>
+<li class="toctree-l2"><a class="reference internal" href="apidoc/impy.arrays.html#module-impy.arrays.tiled">impy.arrays.tiled module</a></li>
 <li class="toctree-l2"><a class="reference internal" href="apidoc/impy.arrays.html#module-impy.arrays">Module contents</a></li>
 </ul>
 </li>
diff --git a/docs/apidoc/impy.arrays.bases.html b/docs/apidoc/impy.arrays.bases.html
index 77693191..9d223a3e 100644
--- a/docs/apidoc/impy.arrays.bases.html
+++ b/docs/apidoc/impy.arrays.bases.html
@@ -1,10 +1,10 @@
 <!DOCTYPE html>
 <html class="writer-html5" lang="en" >
 <head>
-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
+  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.arrays.bases package &mdash; impy 2.2.0 documentation</title>
+  <title>impy.arrays.bases package &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -12,9 +12,8 @@
   <![endif]-->
   
         <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-        <script src="../_static/jquery.js"></script>
-        <script src="../_static/underscore.js"></script>
         <script src="../_static/doctools.js"></script>
+        <script src="../_static/sphinx_highlight.js"></script>
     <script src="../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
@@ -27,14 +26,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -61,11 +64,11 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../api.html">API References</a> &raquo;</li>
-          <li><a href="impy.html">impy package</a> &raquo;</li>
-          <li><a href="impy.arrays.html">impy.arrays package</a> &raquo;</li>
-      <li>impy.arrays.bases package</li>
+      <li><a href="../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../api.html">API References</a></li>
+          <li class="breadcrumb-item"><a href="impy.html">impy package</a></li>
+          <li class="breadcrumb-item"><a href="impy.arrays.html">impy.arrays package</a></li>
+      <li class="breadcrumb-item active">impy.arrays.bases package</li>
       <li class="wy-breadcrumbs-aside">
             <a href="../_sources/apidoc/impy.arrays.bases.rst.txt" rel="nofollow"> View page source</a>
       </li>
@@ -76,39 +79,41 @@
            <div itemprop="articleBody">
              
   <section id="impy-arrays-bases-package">
-<h1>impy.arrays.bases package<a class="headerlink" href="#impy-arrays-bases-package" title="Permalink to this headline">¶</a></h1>
+<h1>impy.arrays.bases package<a class="headerlink" href="#impy-arrays-bases-package" title="Permalink to this heading">¶</a></h1>
 <section id="submodules">
-<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline">¶</a></h2>
+<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this heading">¶</a></h2>
 </section>
 <section id="module-impy.arrays.bases.metaarray">
-<span id="impy-arrays-bases-metaarray-module"></span><h2>impy.arrays.bases.metaarray module<a class="headerlink" href="#module-impy.arrays.bases.metaarray" title="Permalink to this headline">¶</a></h2>
+<span id="impy-arrays-bases-metaarray-module"></span><h2>impy.arrays.bases.metaarray module<a class="headerlink" href="#module-impy.arrays.bases.metaarray" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.arrays.bases.metaarray.MetaArray">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.bases.metaarray.</span></span><span class="sig-name descname"><span class="pre">MetaArray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">obj</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">Hashable</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">source</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Path</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metadata</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/bases/metaarray.html#MetaArray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin" title="impy.arrays.axesmixin.AxesMixin"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.arrays.axesmixin.AxesMixin</span></code></a>, <code class="xref py py-class docutils literal notranslate"><span class="pre">numpy.ndarray</span></code></p>
+<dd><p>Bases: <a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin" title="impy.arrays.axesmixin.AxesMixin"><code class="xref py py-class docutils literal notranslate"><span class="pre">AxesMixin</span></code></a>, <code class="xref py py-class docutils literal notranslate"><span class="pre">ndarray</span></code>[<code class="xref py py-obj docutils literal notranslate"><span class="pre">Any</span></code>, <code class="xref py py-class docutils literal notranslate"><span class="pre">dtype</span></code>[<code class="xref py py-class docutils literal notranslate"><span class="pre">number</span></code>]]</p>
 <dl class="py attribute">
 <dt class="sig sig-object py" id="impy.arrays.bases.metaarray.MetaArray.NP_DISPATCH">
-<span class="sig-name descname"><span class="pre">NP_DISPATCH</span></span><em class="property"><span class="w"> </span><span class="p"><span class="pre">=</span></span><span class="w"> </span><span class="pre">{&lt;function</span> <span class="pre">squeeze&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">take&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">stack&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">concatenate&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">block&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">zeros_like&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">empty_like&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">expand_dims&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">transpose&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">split&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">broadcast_to&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">moveaxis&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">swapaxes&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">cross&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;}</span></em><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.NP_DISPATCH" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">NP_DISPATCH</span></span><em class="property"><span class="w"> </span><span class="p"><span class="pre">=</span></span><span class="w"> </span><span class="pre">{&lt;function</span> <span class="pre">squeeze&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">take&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">stack&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">concatenate&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">block&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">zeros_like&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">empty_like&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">expand_dims&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">transpose&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">split&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">broadcast_to&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">moveaxis&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">swapaxes&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">argmax&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">argmin&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">cross&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">diff&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;,</span> <span class="pre">&lt;function</span> <span class="pre">gradient&gt;:</span> <span class="pre">&lt;function</span> <span class="pre">_&gt;}</span></em><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.NP_DISPATCH" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.arrays.bases.metaarray.MetaArray.T">
 <em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">T</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">Self</span></em><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.T" title="Permalink to this definition">¶</a></dt>
-<dd><p>The transposed array.</p>
+<dd><p>View of the transposed array.</p>
 <p>Same as <code class="docutils literal notranslate"><span class="pre">self.transpose()</span></code>.</p>
 <p class="rubric">Examples</p>
-<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mf">1.</span><span class="p">,</span><span class="mf">2.</span><span class="p">],[</span><span class="mf">3.</span><span class="p">,</span><span class="mf">4.</span><span class="p">]])</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span>
-<span class="go">array([[ 1.,  2.],</span>
-<span class="go">       [ 3.,  4.]])</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">T</span>
-<span class="go">array([[ 1.,  3.],</span>
-<span class="go">       [ 2.,  4.]])</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mf">1.</span><span class="p">,</span><span class="mf">2.</span><span class="p">,</span><span class="mf">3.</span><span class="p">,</span><span class="mf">4.</span><span class="p">])</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span>
-<span class="go">array([ 1.,  2.,  3.,  4.])</span>
-<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span><span class="o">.</span><span class="n">T</span>
-<span class="go">array([ 1.,  2.,  3.,  4.])</span>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">a</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">],</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">]])</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">a</span>
+<span class="go">array([[1, 2],</span>
+<span class="go">       [3, 4]])</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">a</span><span class="o">.</span><span class="n">T</span>
+<span class="go">array([[1, 3],</span>
+<span class="go">       [2, 4]])</span>
+</pre></div>
+</div>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">a</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">])</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">a</span>
+<span class="go">array([1, 2, 3, 4])</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">a</span><span class="o">.</span><span class="n">T</span>
+<span class="go">array([1, 2, 3, 4])</span>
 </pre></div>
 </div>
 <div class="admonition seealso">
@@ -129,10 +134,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <p>For instance, if yx-array takes its maximum at (5, 8), this function returns
 <code class="docutils literal notranslate"><span class="pre">AxesShape(y=5,</span> <span class="pre">x=8)</span></code>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Argmax of the array.</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p>AxesShape</p>
 </dd>
 </dl>
@@ -143,7 +148,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">as_rgba</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cmap</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="pre">np.ndarray</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">np.ndarray</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxisLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'c'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">clim</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">np.ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/bases/metaarray.html#MetaArray.as_rgba"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.as_rgba" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convert array to an RGBA image with given colormap.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>cmap</strong> (<em>str</em><em> or </em><em>callable</em>) – Colormap. Can be a string name of a colormap registered in vispy.</p></li>
 <li><p><strong>axis</strong> (<em>AxisLike</em><em>, </em><em>default is &quot;c&quot;</em>) – The axis name used for the color axis.</p></li>
@@ -151,10 +156,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 array will be used.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Colored image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray">MetaArray</a></p>
 </dd>
 </dl>
@@ -165,17 +170,17 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">broadcast_to</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/bases/metaarray.html#MetaArray.broadcast_to"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.broadcast_to" title="Permalink to this definition">¶</a></dt>
 <dd><p>Broadcast array to specified shape and axes.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>shape</strong> (<em>shape-like</em>) – Shape of output array.</p></li>
 <li><p><strong>axes</strong> (<em>AxesLike</em><em>, </em><em>optional</em>) – Axes of output array. If given, it must match the dimensionality of
 input shape.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Broadcasted array.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray">MetaArray</a></p>
 </dd>
 </dl>
@@ -200,13 +205,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.bases.metaarray.MetaArray.max">
-<span class="sig-name descname"><span class="pre">max</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out:</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keepdims:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">&lt;no</span> <span class="pre">value&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">where:</span> <span class="pre">numpy.ndarray</span> <span class="pre">=</span> <span class="pre">&lt;no</span> <span class="pre">value&gt;</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/bases/metaarray.html#MetaArray.max"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.max" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">max</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out:</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keepdims:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">where:</span> <span class="pre">~numpy.ndarray</span> <span class="pre">=</span> <span class="pre">&lt;no</span> <span class="pre">value&gt;</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/bases/metaarray.html#MetaArray.max"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.max" title="Permalink to this definition">¶</a></dt>
 <dd><p>Maximum value of the array along a given axis.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.bases.metaarray.MetaArray.mean">
-<span class="sig-name descname"><span class="pre">mean</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="pre">axis=None,</span> <span class="pre">dtype:</span> <span class="pre">typing.Union[numpy.dtype[typing.Any],</span> <span class="pre">None,</span> <span class="pre">typing.Type[typing.Any],</span> <span class="pre">numpy._typing._dtype_like._SupportsDType[numpy.dtype[typing.Any]],</span> <span class="pre">str,</span> <span class="pre">typing.Tuple[typing.Any,</span> <span class="pre">int],</span> <span class="pre">typing.Tuple[typing.Any,</span> <span class="pre">typing.Union[typing.SupportsIndex,</span> <span class="pre">typing.Sequence[typing.SupportsIndex]]],</span> <span class="pre">typing.List[typing.Any],</span> <span class="pre">numpy._typing._dtype_like._DTypeDict,</span> <span class="pre">typing.Tuple[typing.Any,</span> <span class="pre">typing.Any]]</span> <span class="pre">=</span> <span class="pre">None,</span> <span class="pre">out:</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None,</span> <span class="pre">keepdims:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">&lt;no</span> <span class="pre">value&gt;,</span> <span class="pre">*,</span> <span class="pre">where:</span> <span class="pre">numpy.ndarray</span> <span class="pre">=</span> <span class="pre">&lt;no</span> <span class="pre">value&gt;</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/bases/metaarray.html#MetaArray.mean"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.mean" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">mean</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">~numpy.dtype[~typing.Any]</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">|</span> <span class="pre">type[typing.Any]</span> <span class="pre">|</span> <span class="pre">~numpy._typing._dtype_like._SupportsDType[~numpy.dtype[~typing.Any]]</span> <span class="pre">|</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">tuple[typing.Any</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">int]</span> <span class="pre">|</span> <span class="pre">tuple[typing.Any</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">typing.Union[typing.SupportsIndex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">collections.abc.Sequence[typing.SupportsIndex]]]</span> <span class="pre">|</span> <span class="pre">list[typing.Any]</span> <span class="pre">|</span> <span class="pre">~numpy._typing._dtype_like._DTypeDict</span> <span class="pre">|</span> <span class="pre">tuple[typing.Any</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">typing.Any]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out:</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keepdims:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">where:</span> <span class="pre">~numpy.ndarray</span> <span class="pre">=</span> <span class="pre">&lt;no</span> <span class="pre">value&gt;</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/bases/metaarray.html#MetaArray.mean"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.mean" title="Permalink to this definition">¶</a></dt>
 <dd><p>Mean value of the array along a given axis.</p>
 </dd></dl>
 
@@ -218,7 +223,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.bases.metaarray.MetaArray.min">
-<span class="sig-name descname"><span class="pre">min</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out:</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keepdims:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">&lt;no</span> <span class="pre">value&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">where:</span> <span class="pre">numpy.ndarray</span> <span class="pre">=</span> <span class="pre">&lt;no</span> <span class="pre">value&gt;</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/bases/metaarray.html#MetaArray.min"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.min" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">min</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out:</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keepdims:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">where:</span> <span class="pre">~numpy.ndarray</span> <span class="pre">=</span> <span class="pre">&lt;no</span> <span class="pre">value&gt;</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/bases/metaarray.html#MetaArray.min"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.min" title="Permalink to this definition">¶</a></dt>
 <dd><p>Minimum value of the array along a given axis.</p>
 </dd></dl>
 
@@ -314,10 +319,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">sort_axes</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/bases/metaarray.html#MetaArray.sort_axes"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.sort_axes" title="Permalink to this definition">¶</a></dt>
 <dd><p>Sort image dimensions to ptzcyx-order</p>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Sorted image</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray">MetaArray</a></p>
 </dd>
 </dl>
@@ -334,13 +339,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">split</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.html#impy.collections.DataList" title="impy.collections.DataList"><span class="pre">DataList</span></a><span class="p"><span class="pre">[</span></span><span class="pre">Self</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/bases/metaarray.html#MetaArray.split"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.split" title="Permalink to this definition">¶</a></dt>
 <dd><p>Split n-dimensional image into (n-1)-dimensional images.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>axis</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Along which axis the original image will be split, by default “c”</p>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Separate images</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>list of arrays</p>
 </dd>
 </dl>
@@ -348,13 +353,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.bases.metaarray.MetaArray.std">
-<span class="sig-name descname"><span class="pre">std</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="pre">axis=None,</span> <span class="pre">dtype:</span> <span class="pre">typing.Union[numpy.dtype[typing.Any],</span> <span class="pre">None,</span> <span class="pre">typing.Type[typing.Any],</span> <span class="pre">numpy._typing._dtype_like._SupportsDType[numpy.dtype[typing.Any]],</span> <span class="pre">str,</span> <span class="pre">typing.Tuple[typing.Any,</span> <span class="pre">int],</span> <span class="pre">typing.Tuple[typing.Any,</span> <span class="pre">typing.Union[typing.SupportsIndex,</span> <span class="pre">typing.Sequence[typing.SupportsIndex]]],</span> <span class="pre">typing.List[typing.Any],</span> <span class="pre">numpy._typing._dtype_like._DTypeDict,</span> <span class="pre">typing.Tuple[typing.Any,</span> <span class="pre">typing.Any]]</span> <span class="pre">=</span> <span class="pre">None,</span> <span class="pre">out:</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None,</span> <span class="pre">ddof:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0,</span> <span class="pre">keepdims:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">&lt;no</span> <span class="pre">value&gt;,</span> <span class="pre">*,</span> <span class="pre">where:</span> <span class="pre">numpy.ndarray</span> <span class="pre">=</span> <span class="pre">&lt;no</span> <span class="pre">value&gt;</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/bases/metaarray.html#MetaArray.std"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.std" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">std</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">~numpy.dtype[~typing.Any]</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">|</span> <span class="pre">type[typing.Any]</span> <span class="pre">|</span> <span class="pre">~numpy._typing._dtype_like._SupportsDType[~numpy.dtype[~typing.Any]]</span> <span class="pre">|</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">tuple[typing.Any</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">int]</span> <span class="pre">|</span> <span class="pre">tuple[typing.Any</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">typing.Union[typing.SupportsIndex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">collections.abc.Sequence[typing.SupportsIndex]]]</span> <span class="pre">|</span> <span class="pre">list[typing.Any]</span> <span class="pre">|</span> <span class="pre">~numpy._typing._dtype_like._DTypeDict</span> <span class="pre">|</span> <span class="pre">tuple[typing.Any</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">typing.Any]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out:</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ddof:</span> <span class="pre">int</span> <span class="pre">=</span> <span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keepdims:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">where:</span> <span class="pre">~numpy.ndarray</span> <span class="pre">=</span> <span class="pre">&lt;no</span> <span class="pre">value&gt;</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/bases/metaarray.html#MetaArray.std"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.std" title="Permalink to this definition">¶</a></dt>
 <dd><p>Standard deviation of the array along a given axis.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.bases.metaarray.MetaArray.sum">
-<span class="sig-name descname"><span class="pre">sum</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="pre">axis=None,</span> <span class="pre">dtype:</span> <span class="pre">typing.Union[numpy.dtype[typing.Any],</span> <span class="pre">None,</span> <span class="pre">typing.Type[typing.Any],</span> <span class="pre">numpy._typing._dtype_like._SupportsDType[numpy.dtype[typing.Any]],</span> <span class="pre">str,</span> <span class="pre">typing.Tuple[typing.Any,</span> <span class="pre">int],</span> <span class="pre">typing.Tuple[typing.Any,</span> <span class="pre">typing.Union[typing.SupportsIndex,</span> <span class="pre">typing.Sequence[typing.SupportsIndex]]],</span> <span class="pre">typing.List[typing.Any],</span> <span class="pre">numpy._typing._dtype_like._DTypeDict,</span> <span class="pre">typing.Tuple[typing.Any,</span> <span class="pre">typing.Any]]</span> <span class="pre">=</span> <span class="pre">None,</span> <span class="pre">out:</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None,</span> <span class="pre">keepdims:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">&lt;no</span> <span class="pre">value&gt;,</span> <span class="pre">*,</span> <span class="pre">where:</span> <span class="pre">numpy.ndarray</span> <span class="pre">=</span> <span class="pre">&lt;no</span> <span class="pre">value&gt;</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/bases/metaarray.html#MetaArray.sum"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.sum" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">sum</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">~numpy.dtype[~typing.Any]</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">|</span> <span class="pre">type[typing.Any]</span> <span class="pre">|</span> <span class="pre">~numpy._typing._dtype_like._SupportsDType[~numpy.dtype[~typing.Any]]</span> <span class="pre">|</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">tuple[typing.Any</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">int]</span> <span class="pre">|</span> <span class="pre">tuple[typing.Any</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">typing.Union[typing.SupportsIndex</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">collections.abc.Sequence[typing.SupportsIndex]]]</span> <span class="pre">|</span> <span class="pre">list[typing.Any]</span> <span class="pre">|</span> <span class="pre">~numpy._typing._dtype_like._DTypeDict</span> <span class="pre">|</span> <span class="pre">tuple[typing.Any</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">typing.Any]</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out:</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keepdims:</span> <span class="pre">bool</span> <span class="pre">=</span> <span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">where:</span> <span class="pre">~numpy.ndarray</span> <span class="pre">=</span> <span class="pre">&lt;no</span> <span class="pre">value&gt;</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/bases/metaarray.html#MetaArray.sum"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.sum" title="Permalink to this definition">¶</a></dt>
 <dd><p>Sum value of the array along a given axis.</p>
 </dd></dl>
 
@@ -367,7 +372,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.arrays.bases.metaarray.MetaArray.value">
-<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">value</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">numpy.ndarray</span></em><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.value" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">value</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">ndarray</span></em><a class="headerlink" href="#impy.arrays.bases.metaarray.MetaArray.value" title="Permalink to this definition">¶</a></dt>
 <dd><p>Numpy view of the array.</p>
 </dd></dl>
 
@@ -381,7 +386,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.arrays.bases.overload">
-<span id="impy-arrays-bases-overload-module"></span><h2>impy.arrays.bases.overload module<a class="headerlink" href="#module-impy.arrays.bases.overload" title="Permalink to this headline">¶</a></h2>
+<span id="impy-arrays-bases-overload-module"></span><h2>impy.arrays.bases.overload module<a class="headerlink" href="#module-impy.arrays.bases.overload" title="Permalink to this heading">¶</a></h2>
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.arrays.bases.overload.np_normalize_axis_tuple">
 <span class="sig-prename descclassname"><span class="pre">impy.arrays.bases.overload.</span></span><span class="sig-name descname"><span class="pre">np_normalize_axis_tuple</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ndim</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">argname</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">allow_duplicate</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/bases/overload.html#np_normalize_axis_tuple"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.bases.overload.np_normalize_axis_tuple" title="Permalink to this definition">¶</a></dt>
@@ -389,7 +394,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.arrays.bases">
-<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-impy.arrays.bases" title="Permalink to this headline">¶</a></h2>
+<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-impy.arrays.bases" title="Permalink to this heading">¶</a></h2>
 </section>
 </section>
 
diff --git a/docs/apidoc/impy.arrays.html b/docs/apidoc/impy.arrays.html
index 1ff075c4..a31532b3 100644
--- a/docs/apidoc/impy.arrays.html
+++ b/docs/apidoc/impy.arrays.html
@@ -1,10 +1,10 @@
 <!DOCTYPE html>
 <html class="writer-html5" lang="en" >
 <head>
-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
+  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.arrays package &mdash; impy 2.2.0 documentation</title>
+  <title>impy.arrays package &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -12,9 +12,8 @@
   <![endif]-->
   
         <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-        <script src="../_static/jquery.js"></script>
-        <script src="../_static/underscore.js"></script>
         <script src="../_static/doctools.js"></script>
+        <script src="../_static/sphinx_highlight.js"></script>
         <script async="async" src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
     <script src="../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../genindex.html" />
@@ -28,14 +27,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -62,10 +65,10 @@
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           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../api.html">API References</a> &raquo;</li>
-          <li><a href="impy.html">impy package</a> &raquo;</li>
-      <li>impy.arrays package</li>
+      <li><a href="../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../api.html">API References</a></li>
+          <li class="breadcrumb-item"><a href="impy.html">impy package</a></li>
+      <li class="breadcrumb-item active">impy.arrays package</li>
       <li class="wy-breadcrumbs-aside">
             <a href="../_sources/apidoc/impy.arrays.rst.txt" rel="nofollow"> View page source</a>
       </li>
@@ -76,15 +79,47 @@
            <div itemprop="articleBody">
              
   <section id="impy-arrays-package">
-<h1>impy.arrays package<a class="headerlink" href="#impy-arrays-package" title="Permalink to this headline">¶</a></h1>
+<h1>impy.arrays package<a class="headerlink" href="#impy-arrays-package" title="Permalink to this heading">¶</a></h1>
 <section id="subpackages">
-<h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to this headline">¶</a></h2>
+<h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to this heading">¶</a></h2>
 <div class="toctree-wrapper compound">
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="impy.arrays.bases.html">impy.arrays.bases package</a><ul>
 <li class="toctree-l2"><a class="reference internal" href="impy.arrays.bases.html#submodules">Submodules</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.arrays.bases.html#module-impy.arrays.bases.metaarray">impy.arrays.bases.metaarray module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.arrays.bases.html#module-impy.arrays.bases.overload">impy.arrays.bases.overload module</a></li>
+<li class="toctree-l2"><a class="reference internal" href="impy.arrays.bases.html#module-impy.arrays.bases.metaarray">impy.arrays.bases.metaarray module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray"><code class="docutils literal notranslate"><span class="pre">MetaArray</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.NP_DISPATCH"><code class="docutils literal notranslate"><span class="pre">MetaArray.NP_DISPATCH</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.T"><code class="docutils literal notranslate"><span class="pre">MetaArray.T</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.additional_props"><code class="docutils literal notranslate"><span class="pre">MetaArray.additional_props</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.argmax_nd"><code class="docutils literal notranslate"><span class="pre">MetaArray.argmax_nd()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.as_rgba"><code class="docutils literal notranslate"><span class="pre">MetaArray.as_rgba()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.broadcast_to"><code class="docutils literal notranslate"><span class="pre">MetaArray.broadcast_to()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.implements"><code class="docutils literal notranslate"><span class="pre">MetaArray.implements()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.isel"><code class="docutils literal notranslate"><span class="pre">MetaArray.isel()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.max"><code class="docutils literal notranslate"><span class="pre">MetaArray.max()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.mean"><code class="docutils literal notranslate"><span class="pre">MetaArray.mean()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.metadata"><code class="docutils literal notranslate"><span class="pre">MetaArray.metadata</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.min"><code class="docutils literal notranslate"><span class="pre">MetaArray.min()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.name"><code class="docutils literal notranslate"><span class="pre">MetaArray.name</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.reshape"><code class="docutils literal notranslate"><span class="pre">MetaArray.reshape()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.sel"><code class="docutils literal notranslate"><span class="pre">MetaArray.sel()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.shape"><code class="docutils literal notranslate"><span class="pre">MetaArray.shape</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.sort_axes"><code class="docutils literal notranslate"><span class="pre">MetaArray.sort_axes()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.source"><code class="docutils literal notranslate"><span class="pre">MetaArray.source</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.split"><code class="docutils literal notranslate"><span class="pre">MetaArray.split()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.std"><code class="docutils literal notranslate"><span class="pre">MetaArray.std()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.sum"><code class="docutils literal notranslate"><span class="pre">MetaArray.sum()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.transpose"><code class="docutils literal notranslate"><span class="pre">MetaArray.transpose()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.value"><code class="docutils literal notranslate"><span class="pre">MetaArray.value</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.NotMe"><code class="docutils literal notranslate"><span class="pre">NotMe</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.arrays.bases.html#module-impy.arrays.bases.overload">impy.arrays.bases.overload module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.overload.np_normalize_axis_tuple"><code class="docutils literal notranslate"><span class="pre">np_normalize_axis_tuple()</span></code></a></li>
+</ul>
+</li>
 <li class="toctree-l2"><a class="reference internal" href="impy.arrays.bases.html#module-impy.arrays.bases">Module contents</a></li>
 </ul>
 </li>
@@ -92,10 +127,10 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 </div>
 </section>
 <section id="submodules">
-<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline">¶</a></h2>
+<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this heading">¶</a></h2>
 </section>
 <section id="module-impy.arrays.axesmixin">
-<span id="impy-arrays-axesmixin-module"></span><h2>impy.arrays.axesmixin module<a class="headerlink" href="#module-impy.arrays.axesmixin" title="Permalink to this headline">¶</a></h2>
+<span id="impy-arrays-axesmixin-module"></span><h2>impy.arrays.axesmixin module<a class="headerlink" href="#module-impy.arrays.axesmixin" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.arrays.axesmixin.AxesMixin">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.axesmixin.</span></span><span class="sig-name descname"><span class="pre">AxesMixin</span></span><a class="reference internal" href="../_modules/impy/arrays/axesmixin.html#AxesMixin"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.axesmixin.AxesMixin" title="Permalink to this definition">¶</a></dt>
@@ -103,7 +138,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <p>Abstract class with shape, ndim and axes are defined.</p>
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.arrays.axesmixin.AxesMixin.axes">
-<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">axes</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">impy.axes._axes.Axes</span></em><a class="headerlink" href="#impy.arrays.axesmixin.AxesMixin.axes" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">axes</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">Axes</span></em><a class="headerlink" href="#impy.arrays.axesmixin.AxesMixin.axes" title="Permalink to this definition">¶</a></dt>
 <dd><p>Axes of the array.</p>
 </dd></dl>
 
@@ -112,11 +147,16 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">axisof</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">symbol</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">int</span></span></span><a class="reference internal" href="../_modules/impy/arrays/axesmixin.html#AxesMixin.axisof"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.axesmixin.AxesMixin.axisof" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
+<dl class="py attribute">
+<dt class="sig sig-object py" id="impy.arrays.axesmixin.AxesMixin.dtype">
+<span class="sig-name descname"><span class="pre">dtype</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">dtype</span></em><a class="headerlink" href="#impy.arrays.axesmixin.AxesMixin.dtype" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.axesmixin.AxesMixin.iter">
-<span class="sig-name descname"><span class="pre">iter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">israw</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="k"><span class="pre">False</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exclude</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Iterator</span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">slice</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">numpy.ndarray</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/axesmixin.html#AxesMixin.iter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.axesmixin.AxesMixin.iter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">iter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">israw</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="k"><span class="pre">False</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exclude</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Iterator</span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">slice</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">numpy.ndarray</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/axesmixin.html#AxesMixin.iter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.axesmixin.AxesMixin.iter" title="Permalink to this definition">¶</a></dt>
 <dt class="sig sig-object py">
-<span class="sig-name descname"><span class="pre">iter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">israw</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="k"><span class="pre">True</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exclude</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Iterator</span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">Slices</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Self</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></span></dt>
+<span class="sig-name descname"><span class="pre">iter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">israw</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="k"><span class="pre">True</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exclude</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">''</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Iterator</span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">Slices</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Self</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></span></dt>
 <dd><p>Iteration along axes. If axes=”tzc”, then equivalent to following pseudo code:</p>
 <blockquote>
 <div><div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">all_t</span><span class="p">:</span>
@@ -127,7 +167,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </div>
 </div></blockquote>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>axes</strong> (<em>str</em><em> or </em><em>int</em>) – On which axes iteration is performed. Or the number of spatial dimension.</p></li>
 <li><p><strong>israw</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, MetaArray will be returned. If False, np.ndarray will be returned.</p></li>
@@ -136,7 +176,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 arranged.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Yields</dt>
+<dt class="field-even">Yields<span class="colon">:</span></dt>
 <dd class="field-even"><p><em>slice and (np.ndarray or AxesMixin)</em> – slice and a subimage=self[sl]</p>
 </dd>
 </dl>
@@ -154,7 +194,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.arrays.axesmixin.AxesMixin.scale">
-<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">scale</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">impy.axes._axes.ScaleView</span></em><a class="headerlink" href="#impy.arrays.axesmixin.AxesMixin.scale" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">scale</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">ScaleView</span></em><a class="headerlink" href="#impy.arrays.axesmixin.AxesMixin.scale" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py property">
@@ -167,13 +207,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">set_axes</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/axesmixin.html#AxesMixin.set_axes"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.axesmixin.AxesMixin.set_axes" title="Permalink to this definition">¶</a></dt>
 <dd><p>Set axes of the array and return the updated one.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>axes</strong> (<em>AxesLike</em>) – New axes.</p>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Array with updated axes.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Self</p>
 </dd>
 </dl>
@@ -184,7 +224,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">set_axis_label</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">_dict</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">MutableMapping</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">/</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/axesmixin.html#AxesMixin.set_axis_label"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.axesmixin.AxesMixin.set_axis_label" title="Permalink to this definition">¶</a></dt>
 <dd><p>Set labels to an axis (axes).</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>_dict</strong> (<em>mapping</em><em>, </em><em>optional</em>) – Mapping from axis to its labels. Labels must have the same length as its
 dimensionality.</p>
 </dd>
@@ -200,7 +240,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">set_scale</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">other</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/axesmixin.html#AxesMixin.set_scale"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.axesmixin.AxesMixin.set_scale" title="Permalink to this definition">¶</a></dt>
 <dd><p>Set scales of each axis.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>other</strong> (<em>dict</em><em> or </em><em>object with axes</em>) – New scales. If dict, it should be like {“x”: 0.1, “y”: 0.1}. If MetaArray, only
 scales of common axes are copied.</p></li>
@@ -223,7 +263,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.axesmixin.AxesMixin.sizeof">
-<span class="sig-name descname"><span class="pre">sizeof</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">int</span></span></span><a class="reference internal" href="../_modules/impy/arrays/axesmixin.html#AxesMixin.sizeof"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.axesmixin.AxesMixin.sizeof" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">sizeof</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">int</span></span></span><a class="reference internal" href="../_modules/impy/arrays/axesmixin.html#AxesMixin.sizeof"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.axesmixin.AxesMixin.sizeof" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
@@ -245,19 +285,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.arrays.axesmixin.get_axes_tuple">
-<span class="sig-prename descclassname"><span class="pre">impy.arrays.axesmixin.</span></span><span class="sig-name descname"><span class="pre">get_axes_tuple</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#impy.arrays.axesmixin.AxesMixin" title="impy.arrays.axesmixin.AxesMixin"><span class="pre">impy.arrays.axesmixin.AxesMixin</span></a></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/axesmixin.html#get_axes_tuple"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.axesmixin.get_axes_tuple" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.arrays.axesmixin.</span></span><span class="sig-name descname"><span class="pre">get_axes_tuple</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#impy.arrays.axesmixin.AxesMixin" title="impy.arrays.axesmixin.AxesMixin"><span class="pre">AxesMixin</span></a></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/axesmixin.html#get_axes_tuple"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.axesmixin.get_axes_tuple" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </section>
 <section id="module-impy.arrays.big">
-<span id="impy-arrays-big-module"></span><h2>impy.arrays.big module<a class="headerlink" href="#module-impy.arrays.big" title="Permalink to this headline">¶</a></h2>
+<span id="impy-arrays-big-module"></span><h2>impy.arrays.big module<a class="headerlink" href="#module-impy.arrays.big" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.big.</span></span><span class="sig-name descname"><span class="pre">BigImgArray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">obj</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DaskArray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">source</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metadata</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/big.html#BigImgArray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.big.BigImgArray" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.arrays.lazy.LazyImgArray</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">LazyImgArray</span></code></a></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.affine">
-<span class="sig-name descname"><span class="pre">affine</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">matrix</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rotation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shear</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">translation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.affine" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">affine</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">matrix</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rotation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shear</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">translation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.affine" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.affine. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Convert image by Affine transformation. 2D Affine transformation is written as:</p>
 <div class="math notranslate nohighlight">
@@ -268,7 +308,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
                 \begin{bmatrix} y \\x\\ 1 \end{bmatrix}\end{split}\]</div>
 <p>and similarly, n-D Affine transformation can be described as (n+1)-D matrix.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>matrix</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
 <li><p><strong>scale</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
@@ -279,16 +319,16 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p></li>
 <li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
 <li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
-<li><p><strong>output_shape</strong> (<em>tuple of int</em><em>, </em><em>optional</em>) – Shape of output array.</p></li>
+<li><p><strong>output_shape</strong> (<em>tuple</em><em> of </em><em>int</em><em>, </em><em>optional</em>) – Shape of output array.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Transformed image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -296,33 +336,33 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.as_float">
-<span class="sig-name descname"><span class="pre">as_float</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.as_float" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">as_float</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.as_float" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.as_img_type">
-<span class="sig-name descname"><span class="pre">as_img_type</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dtype=&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.as_img_type" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">as_img_type</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dtype=&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.as_img_type" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.as_uint16">
-<span class="sig-name descname"><span class="pre">as_uint16</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.as_uint16" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">as_uint16</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.as_uint16" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.as_uint8">
-<span class="sig-name descname"><span class="pre">as_uint8</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.as_uint8" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">as_uint8</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.as_uint8" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.binning">
-<span class="sig-name descname"><span class="pre">binning</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">binsize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_edges</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.binning" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">binning</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">binsize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_edges</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.binning" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.binning. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Binning of images. This function is similar to <code class="docutils literal notranslate"><span class="pre">rescale</span></code> but is strictly
 binned by <span class="math notranslate nohighlight">\(N \times N\)</span> blocks. Also, any numpy functions that accept
 “axis” argument are supported for reduce functions.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>binsize</strong> (<em>int</em><em>, </em><em>default is 2</em>) – Bin size, such as 2x2.</p></li>
 <li><p><strong>method</strong> (<em>str</em><em> or </em><em>callable</em><em>, </em><em>default is numpy.mean</em>) – Reduce function applied to each bin.</p></li>
@@ -332,10 +372,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Binned image</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -343,13 +383,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.closing">
-<span class="sig-name descname"><span class="pre">closing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.closing" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">closing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.closing" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.closing. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Morphological closing.</p>
 <p>If input is binary image, the running function will automatically switched to
 <code class="docutils literal notranslate"><span class="pre">binary_closing</span></code> to speed up calculation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -376,10 +416,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -387,11 +427,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.convolve">
-<span class="sig-name descname"><span class="pre">convolve</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kernel</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.convolve" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">convolve</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kernel</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.convolve" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.convolve. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>General linear convolution by running kernel filtering.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>kernel</strong> (<em>array-like</em>) – Convolution kernel.</p></li>
 <li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
@@ -401,10 +441,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Convolved image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -412,12 +452,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.dilation">
-<span class="sig-name descname"><span class="pre">dilation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.dilation" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">dilation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.dilation" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.dilation. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Morphological dilation. If input is binary image, the running function will automatically switched to
 <code class="docutils literal notranslate"><span class="pre">binary_dilation</span></code> to speed up calculation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -444,10 +484,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -460,7 +500,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <p>Drift correction using iterative Affine translation. If translation vectors <code class="docutils literal notranslate"><span class="pre">shift</span></code>
 is not given, then it will be determined using <code class="docutils literal notranslate"><span class="pre">track_drift</span></code> method of ImgArray.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>shift</strong> (<em>DataFrame</em><em> or </em><em>(</em><em>N</em><em>, </em><em>D</em><em>) </em><em>array</em><em>, </em><em>optional</em>) – Translation vectors. If DataFrame, it must have columns named with all the symbols
 contained in <code class="docutils literal notranslate"><span class="pre">dims</span></code>.</p></li>
@@ -473,10 +513,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>affine_kwargs</strong> – Keyword arguments that will be passed to <code class="docutils literal notranslate"><span class="pre">warp</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Corrected image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -491,11 +531,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.edge_filter">
-<span class="sig-name descname"><span class="pre">edge_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'sobel'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.edge_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">edge_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'sobel'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.edge_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.edge_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Sobel filter. This filter is useful for edge detection.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>method</strong> (<em>str</em><em>, </em><em>{&quot;sobel&quot;</em><em>, </em><em>&quot;farid&quot;</em><em>, </em><em>&quot;scharr&quot;</em><em>, </em><em>&quot;prewitt&quot;}</em><em>, </em><em>default is &quot;sobel&quot;</em>) – Edge operator name.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
@@ -503,10 +543,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -514,13 +554,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.erosion">
-<span class="sig-name descname"><span class="pre">erosion</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.erosion" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">erosion</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.erosion" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.erosion. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Morphological erosion.</p>
 <p>If input is binary image, the running function will automatically switched to
 <code class="docutils literal notranslate"><span class="pre">binary_erosion</span></code> to speed up calculation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -547,10 +587,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -558,14 +598,14 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.fft">
-<span class="sig-name descname"><span class="pre">fft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'same'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.fft" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'same'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.fft" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.fft. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Fast Fourier transformation. This function returns complex array, which is
 inconpatible with some ImgArray functions.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable of int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
+<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable</em><em> of </em><em>int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
 - integers: padded or cropped to the specified shape.
 - “square”: padded to smallest 2^N-long square.
 - “same” (default): no padding or cropping.</p></li>
@@ -575,10 +615,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>FFT image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -590,23 +630,25 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.gaussian_filter">
-<span class="sig-name descname"><span class="pre">gaussian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.gaussian_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">gaussian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.gaussian_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.gaussian_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Run Gaussian filter (Gaussian blur).</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array of float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
 If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
+<li><p><strong>fourier</strong> (<em>bool</em><em>, </em><em>default is False</em>) – Whether to run the convolution in Fourier space. This option is useful when the kernel or the image is large.
+Note that discrete Fourier transform assumes that the image is periodic, so that if intensities of the input image are not consecutive at img[0] and img[-1], you may get some artifacts at the boundary.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -614,11 +656,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.ifft">
-<span class="sig-name descname"><span class="pre">ifft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">real</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.ifft" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">ifft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">real</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.ifft" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.ifft. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Fast Inverse Fourier transformation. Complementary function with <cite>fft()</cite>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>real</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, only the real part is returned.</p></li>
 <li><p><strong>shift</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, call <code class="docutils literal notranslate"><span class="pre">np.fft.ifftshift</span></code> at the first.</p></li>
@@ -627,10 +669,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>IFFT image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -638,12 +680,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.kalman_filter">
-<span class="sig-name descname"><span class="pre">kalman_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">gain</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">noise_var</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'t'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.kalman_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">kalman_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">gain</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">noise_var</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'t'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.kalman_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.kalman_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Kalman filter for image smoothing. This function is same as “Kalman Stack Filter” in ImageJ but support
 batch processing. This filter is useful for preprocessing of particle tracking.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>gain</strong> (<em>float</em><em>, </em><em>default is 0.8</em>) – Filter gain.</p></li>
 <li><p><strong>noise_var</strong> (<em>float</em><em>, </em><em>default is 0.05</em>) – Initial estimate of noise variance.</p></li>
@@ -653,10 +695,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -664,11 +706,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.laplacian_filter">
-<span class="sig-name descname"><span class="pre">laplacian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.laplacian_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">laplacian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.laplacian_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.laplacian_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Edge detection using Laplacian filter. Kernel is made by <cite>skimage</cite>’s function.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>int</em><em>, </em><em>default is 1</em>) – Radius of kernel. Shape of kernel will be (2*radius+1, 2*radius+1).</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
@@ -676,10 +718,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -687,26 +729,27 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.lucy">
-<span class="sig-name descname"><span class="pre">lucy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">numpy.ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">niter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1e-05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.lucy" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">lucy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">niter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1e-05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.lucy" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.lucy. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Deconvolution of N-dimensional image, using Richardson-Lucy’s algorithm.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>psf</strong> (<em>np.ndarray</em>) – Point spread function.</p></li>
+<li><p><strong>psf</strong> (<em>ndarray</em><em> or </em><em>callable</em>) – Point spread function. If a function is given, <cite>psf(shape)</cite> will be
+called to generate the PSF.</p></li>
 <li><p><strong>niter</strong> (<em>int</em><em>, </em><em>default is 50.</em>) – Number of iterations.</p></li>
-<li><p><strong>eps</strong> (<em>float</em><em>, </em><em>default is 1e-5</em>) – During deconvolution, division by small values in the convolve image of estimation and
-PSF may cause divergence. Therefore, division by values under <cite>eps</cite> is substituted
-to zero.</p></li>
+<li><p><strong>eps</strong> (<em>float</em><em>, </em><em>default is 1e-5</em>) – During deconvolution, division by small values in the convolve image
+of estimation and PSF may cause divergence. Therefore, division by
+values under <cite>eps</cite> is substituted to zero.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Deconvolved image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -718,11 +761,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.mean_filter">
-<span class="sig-name descname"><span class="pre">mean_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.mean_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">mean_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.mean_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.mean_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Mean filter. Kernel is filled with same values.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -749,10 +792,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -760,12 +803,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.median_filter">
-<span class="sig-name descname"><span class="pre">median_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.median_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">median_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.median_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.median_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Running multi-dimensional median filter.</p>
 <p>This filter is useful for deleting outliers generated by noise.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -792,10 +835,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -803,12 +846,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.opening">
-<span class="sig-name descname"><span class="pre">opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.opening" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.opening" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.opening. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Morphological opening. If input is binary image, the running function will automatically switched to
 <code class="docutils literal notranslate"><span class="pre">binary_opening</span></code> to speed up calculation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -835,10 +878,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -846,28 +889,29 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.power_spectra">
-<span class="sig-name descname"><span class="pre">power_spectra</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'same'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">zero_norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.power_spectra" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">power_spectra</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'same'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">zero_norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.power_spectra" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.power_spectra. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Return n-D power spectra of images, which is defined as:</p>
 <div class="math notranslate nohighlight">
 \[P = Re(F[I_{img}])^2 + Im(F[I_{img}])^2\]</div>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable of int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
+<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable</em><em> of </em><em>int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
 - integers: padded or cropped to the specified shape.
 - “square”: padded to smallest 2^N-long square.
 - “same” (default): no padding or cropping.</p></li>
 <li><p><strong>norm</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, maximum value of power spectra is adjusted to 1.</p></li>
 <li><p><strong>double_precision</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, FFT will be calculated using 64-bit float and 128-bit complex.</p></li>
+<li><p><strong>shift</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, call <code class="docutils literal notranslate"><span class="pre">np.fft.fftshift</span></code> at the first.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Power spectra</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -879,11 +923,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.proj">
-<span class="sig-name descname"><span class="pre">proj</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.proj" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">proj</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.proj" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.proj. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Projection along any axis.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>axis</strong> (<em>str</em><em>, </em><em>optional</em>) – Along which axis projection will be calculated. If None, most plausible one will be chosen.</p></li>
 <li><p><strong>method</strong> (<em>str</em><em> or </em><em>callable</em><em>, </em><em>default is mean-projection.</em>) – Projection method. If str is given, it will converted to numpy function.</p></li>
@@ -892,10 +936,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>**kwargs</strong> – Other keyword arguments that will passed to projection function.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Projected image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -903,16 +947,16 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.radon">
-<span class="sig-name descname"><span class="pre">radon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degrees</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">central_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxisLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.radon" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">radon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degrees</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">central_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.radon" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.radon. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Discrete Radon transformation of 2D or 3D image.</p>
 <p>Radon transformation is a list of projection of a same image from different angles.
 It generates tomographic n-D image slices from (n+1)-D image.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>degrees</strong> (<em>float</em><em> or </em><em>iterable of float</em>) – Rotation angles around the central axis in degrees.</p></li>
-<li><p><strong>central_axis</strong> (<em>axis-like</em><em> or </em><em>sequence of float</em><em>, </em><em>optional</em>) – Vector that defines the central axis of rotation.</p></li>
+<li><p><strong>degrees</strong> (<em>float</em><em> or </em><em>iterable</em><em> of </em><em>float</em>) – Rotation angles around the central axis in degrees.</p></li>
+<li><p><strong>central_axis</strong> (<em>axis-like</em><em> or </em><em>sequence</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Vector that defines the central axis of rotation.</p></li>
 <li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
 For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
 </p></li>
@@ -920,13 +964,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Tomographic image slices. The first spatial axis (“z” for zyx-image) will be dropped.
 If sequence of float is given as <code class="docutils literal notranslate"><span class="pre">degrees</span></code>, “degree” axis will be newly added at
 the position 0. For instance, if a zyx-image and <code class="docutils literal notranslate"><span class="pre">degrees=np.linspace(0,</span> <span class="pre">180,</span> <span class="pre">100)</span></code>
 are given, returned image has axes [“degree”, “y”, “x”].</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -938,11 +982,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.spline_filter">
-<span class="sig-name descname"><span class="pre">spline_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mirror'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.spline_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">spline_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mirror'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.spline_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of LabeledArray.spline_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Run spline filter.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
 For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
@@ -953,10 +997,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -964,30 +1008,8 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.tiled_lowpass_filter">
-<span class="sig-name descname"><span class="pre">tiled_lowpass_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">overlap</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">16</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.tiled_lowpass_filter" title="Permalink to this definition">¶</a></dt>
-<dd><p>Copy of ImgArray.tiled_lowpass_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
-<p>Tile-by-tile Butterworth low-pass filter. This method is an approximation of the standard
-low-pass filter, which would be useful when the image is large.</p>
-<dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><ul class="simple">
-<li><p><strong>cutoff</strong> (<em>float</em><em> or </em><em>array-like</em><em>, </em><em>default is 0.2</em>) – Cutoff frequency.</p></li>
-<li><p><strong>chunks</strong> (<em>str</em><em> or </em><em>sequence of int</em>) – Chunk size of each lowpass filter task.</p></li>
-<li><p><strong>order</strong> (<em>float</em><em>, </em><em>default is 2</em>) – Steepness of cutoff.</p></li>
-<li><p><strong>overlap</strong> (<em>int</em><em>, </em><em>default is 16</em>) – Overlapping pixels at the edges of tiles.</p></li>
-<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
-For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
-<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
-</ul>
-</dd>
-<dt class="field-even">Returns</dt>
-<dd class="field-even"><p>Filtered image.</p>
-</dd>
-<dt class="field-odd">Return type</dt>
-<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
-</dd>
-</dl>
-</dd></dl>
+<span class="sig-name descname"><span class="pre">tiled_lowpass_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">overlap</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">16</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.tiled_lowpass_filter" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.track_drift">
@@ -996,30 +1018,25 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <p>Calculate yx-directional drift using the method equivalent to
 <code class="docutils literal notranslate"><span class="pre">skimage.registration.phase_cross_correlation</span></code>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>along</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Along which axis drift will be calculated.</p></li>
 <li><p><strong>show_drift</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, plot the result.</p></li>
 <li><p><strong>upsample_factor</strong> (<em>int</em><em>, </em><em>default is 10</em>) – Up-sampling factor when calculating phase cross correlation.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>DataFrame structure with x,y columns</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
 </dd>
 </dl>
 </dd></dl>
 
-<dl class="py attribute">
-<dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.value">
-<span class="sig-name descname"><span class="pre">value</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">Any</span></em><a class="headerlink" href="#impy.arrays.big.BigImgArray.value" title="Permalink to this definition">¶</a></dt>
-<dd></dd></dl>
-
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.big.BigImgArray.wiener">
-<span class="sig-name descname"><span class="pre">wiener</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">numpy.ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.wiener" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">wiener</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.big.BigImgArray.wiener" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.wiener. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Classical wiener deconvolution. This algorithm has the serious ringing problem
 if parameters are set to wrong values.</p>
@@ -1028,19 +1045,20 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="math notranslate nohighlight">\(Y_{res}\)</span>: restored image;
 <span class="math notranslate nohighlight">\(H\)</span> : FFT of point spread function (PSF);</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>psf</strong> (<em>np.ndarray</em>) – Point spread function.</p></li>
+<li><p><strong>psf</strong> (<em>ndarray</em><em> or </em><em>callable</em>) – Point spread function. If a function is given, <cite>psf(shape)</cite> will be
+called to generate the PSF.</p></li>
 <li><p><strong>lmd</strong> (<em>float</em><em>, </em><em>default is 0.1</em>) – Constant value used in the deconvolution. See Formulation below.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Deconvolved image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -1059,18 +1077,18 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.arrays.imgarray">
-<span id="impy-arrays-imgarray-module"></span><h2>impy.arrays.imgarray module<a class="headerlink" href="#module-impy.arrays.imgarray" title="Permalink to this headline">¶</a></h2>
+<span id="impy-arrays-imgarray-module"></span><h2>impy.arrays.imgarray module<a class="headerlink" href="#module-impy.arrays.imgarray" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.imgarray.</span></span><span class="sig-name descname"><span class="pre">ImgArray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">obj</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">source</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Path</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metadata</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="#impy.arrays.labeledarray.LabeledArray" title="impy.arrays.labeledarray.LabeledArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.arrays.labeledarray.LabeledArray</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="#impy.arrays.labeledarray.LabeledArray" title="impy.arrays.labeledarray.LabeledArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">LabeledArray</span></code></a></p>
 <p>An n-D array for image analysis.</p>
 <dl class="py attribute">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.axes">
 <span class="sig-name descname"><span class="pre">axes</span></span><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.axes" title="Permalink to this definition">¶</a></dt>
 <dd><p>Image axes, such as “zyx” or “tcyx”.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Type</dt>
+<dt class="field-odd">Type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>str</p>
 </dd>
 </dl>
@@ -1082,7 +1100,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dd><p>Physical scale along each axis. For instance, scale of x-axis can be referred
 to by <code class="docutils literal notranslate"><span class="pre">img.scale[&quot;x&quot;]</span></code> or <a href="#id3"><span class="problematic" id="id4">``</span></a>img.scale.x</p>
 <dl class="field-list simple">
-<dt class="field-odd">Type</dt>
+<dt class="field-odd">Type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>ScaleDict</p>
 </dd>
 </dl>
@@ -1093,7 +1111,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">metadata</span></span><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.metadata" title="Permalink to this definition">¶</a></dt>
 <dd><p>Metadata tagged to the image.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Type</dt>
+<dt class="field-odd">Type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>dict</p>
 </dd>
 </dl>
@@ -1104,7 +1122,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">source</span></span><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.source" title="Permalink to this definition">¶</a></dt>
 <dd><p>Source file of the image.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Type</dt>
+<dt class="field-odd">Type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Path</p>
 </dd>
 </dl>
@@ -1112,7 +1130,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.affine">
-<span class="sig-name descname"><span class="pre">affine</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">matrix</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rotation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shear</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">translation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">PaddingMode</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefilter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.affine"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.affine" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">affine</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">matrix</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rotation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shear</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">translation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefilter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.affine"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.affine" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convert image by Affine transformation. 2D Affine transformation is written as:</p>
 <div class="math notranslate nohighlight">
 \[\begin{split}\begin{bmatrix} y'\\ x' \\1 \end{bmatrix} =
@@ -1122,7 +1140,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
                 \begin{bmatrix} y \\x\\ 1 \end{bmatrix}\end{split}\]</div>
 <p>and similarly, n-D Affine transformation can be described as (n+1)-D matrix.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>matrix</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
 <li><p><strong>scale</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
@@ -1134,16 +1152,16 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </p></li>
 <li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
 <li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
-<li><p><strong>output_shape</strong> (<em>tuple of int</em><em>, </em><em>optional</em>) – Shape of output array.</p></li>
+<li><p><strong>output_shape</strong> (<em>tuple</em><em> of </em><em>int</em><em>, </em><em>optional</em>) – Shape of output array.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Transformed image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1151,22 +1169,22 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.area_closing">
-<span class="sig-name descname"><span class="pre">area_closing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">area</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">64</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.area_closing"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.area_closing" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">area_closing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">area</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">64</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.area_closing"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.area_closing" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.area_opening">
-<span class="sig-name descname"><span class="pre">area_opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">area</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">64</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.area_opening"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.area_opening" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">area_opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">area</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">64</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.area_opening"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.area_opening" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.binning">
-<span class="sig-name descname"><span class="pre">binning</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">binsize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_edges</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.binning"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.binning" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">binning</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">binsize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_edges</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.binning"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.binning" title="Permalink to this definition">¶</a></dt>
 <dd><p>Binning of images. This function is similar to <code class="docutils literal notranslate"><span class="pre">rescale</span></code> but is strictly
 binned by <span class="math notranslate nohighlight">\(N \times N\)</span> blocks. Also, any numpy functions that accept
 “axis” argument are supported for reduce functions.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>binsize</strong> (<em>int</em><em>, </em><em>default is 2</em>) – Bin size, such as 2x2.</p></li>
 <li><p><strong>method</strong> (<em>str</em><em> or </em><em>callable</em><em>, </em><em>default is numpy.mean</em>) – Reduce function applied to each bin.</p></li>
@@ -1176,21 +1194,41 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Binned image</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
 </dd></dl>
 
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.center_of_mass">
+<span class="sig-name descname"><span class="pre">center_of_mass</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.center_of_mass"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.center_of_mass" title="Permalink to this definition">¶</a></dt>
+<dd><p>Calculate the center of mass of the image.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Center of mass. Axes will be the input axes minus <code class="docutils literal notranslate"><span class="pre">dims</span></code>, plus a new axis
+<code class="docutils literal notranslate"><span class="pre">dim</span></code> at the first position, which represents the dimensions of the
+results.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray">PropArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.centroid_sm">
 <span class="sig-name descname"><span class="pre">centroid_sm</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coords</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Coords</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">nDInt</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">bool</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">find_sm_kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><span class="pre">MarkerFrame</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.centroid_sm"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.centroid_sm" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate positions of particles in subpixel precision using centroid.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>coords</strong> (<a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><em>MarkerFrame</em></a><em> or </em><em>(</em><em>N</em><em>, </em><em>2</em><em>) </em><em>array</em><em>, </em><em>optional</em>) – Coordinates of peaks. If None, this will be determined by find_sm.</p></li>
 <li><p><strong>radius</strong> (<em>int</em><em>, </em><em>default is 4.</em>) – Range to calculate centroids. Rectangular image with size 2r+1 x 2r+1 will be send
@@ -1199,10 +1237,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>find_sm_kwargs</strong> (<em>keyword arguments</em>) – Parameters passed to <a class="reference internal" href="#impy.arrays.imgarray.ImgArray.find_sm" title="impy.arrays.imgarray.ImgArray.find_sm"><code class="xref py py-func docutils literal notranslate"><span class="pre">find_sm()</span></code></a>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Coordinates of peaks.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
 </dd>
 </dl>
@@ -1217,13 +1255,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">clip</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">in_range</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">('0%',</span> <span class="pre">'100%')</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.clip"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.clip" title="Permalink to this definition">¶</a></dt>
 <dd><p>Saturate low/high intensity using np.clip().</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>in_range</strong> (<em>two scalar values</em><em>, </em><em>optional</em>) – range of lower/upper limits, by default (0%, 100%).</p>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Clipped image with temporal attribute</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1231,12 +1269,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.closing">
-<span class="sig-name descname"><span class="pre">closing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.closing"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.closing" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">closing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.closing"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.closing" title="Permalink to this definition">¶</a></dt>
 <dd><p>Morphological closing.</p>
 <p>If input is binary image, the running function will automatically switched to
 <code class="docutils literal notranslate"><span class="pre">binary_closing</span></code> to speed up calculation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -1263,10 +1301,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1274,12 +1312,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.coef_filter">
-<span class="sig-name descname"><span class="pre">coef_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.coef_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.coef_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">coef_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.coef_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.coef_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Coefficient of variance filter.</p>
 <p>For kernel area X, <span class="math notranslate nohighlight">\(\frac{\sqrt{V[X]}}{E[X]}\)</span> is calculated. This filter
 is useful for feature extraction from images with uneven background intensity.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -1305,10 +1343,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1316,20 +1354,20 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.convex_hull">
-<span class="sig-name descname"><span class="pre">convex_hull</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.convex_hull"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.convex_hull" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">convex_hull</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.convex_hull"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.convex_hull" title="Permalink to this definition">¶</a></dt>
 <dd><p>Compute convex hull image.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Convex hull image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1337,10 +1375,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.convolve">
-<span class="sig-name descname"><span class="pre">convolve</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kernel</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.convolve"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.convolve" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">convolve</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kernel</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.convolve"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.convolve" title="Permalink to this definition">¶</a></dt>
 <dd><p>General linear convolution by running kernel filtering.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>kernel</strong> (<em>array-like</em>) – Convolution kernel.</p></li>
 <li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
@@ -1350,10 +1388,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Convolved image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1361,12 +1399,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.corner_harris">
-<span class="sig-name descname"><span class="pre">corner_harris</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.corner_harris"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.corner_harris" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">corner_harris</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.corner_harris"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.corner_harris" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate Harris response image.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array of float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
 If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
 <li><p><strong>k</strong> (<em>float</em><em>, </em><em>optional</em>) – Sensitivity factor to separate corners from edges, typically in range [0, 0.2].
 Small values of k result in detection of sharp corners.</p></li>
@@ -1374,10 +1412,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Harris response</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1388,7 +1426,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">corner_peaks</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_distance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">percentile</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">topn</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">inf</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">topn_per_label</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">inf</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exclude_border</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_labels</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><span class="pre">MarkerFrame</span></a></span></span><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.corner_peaks" title="Permalink to this definition">¶</a></dt>
 <dd><p>Find local corner maxima. Slightly different from peak_local_max.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>min_distance</strong> (<em>int</em><em>, </em><em>default is 1</em>) – Minimum distance allowed for each two peaks. This parameter is slightly
 different from that in <code class="docutils literal notranslate"><span class="pre">skimage.feature.peak_local_max</span></code> because here float
@@ -1400,12 +1438,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>{dims}</strong> – </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>DataFrame with columns same as axes of self. For example, if self.axes is “tcyx” then
 return value has “t”, “c”, “y” and “x” columns, and sub-frame at t=0, c=0 contains all
 the coordinates of corners in the slice at t=0, c=0.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
 </dd>
 </dl>
@@ -1413,11 +1451,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.count_neighbors">
-<span class="sig-name descname"><span class="pre">count_neighbors</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.count_neighbors"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.count_neighbors" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">count_neighbors</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.count_neighbors"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.count_neighbors" title="Permalink to this definition">¶</a></dt>
 <dd><p>Count the number or neighbors of binary images. This function can be used for cross section
 or branch detection. Only works for binary images.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>connectivity</strong> (<em>int</em><em>, </em><em>optional</em>) – Connectivity of pixels. See <code class="docutils literal notranslate"><span class="pre">skimage.measure.label</span></code>.</p></li>
 <li><p><strong>mask</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, only neighbors of pixels that satisfy self==True is returned.</p></li>
@@ -1425,10 +1463,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>uint8 array of the number of neighbors.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1443,21 +1481,21 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.diameter_closing">
-<span class="sig-name descname"><span class="pre">diameter_closing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">diameter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">8</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.diameter_closing"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.diameter_closing" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">diameter_closing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">diameter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">8</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.diameter_closing"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.diameter_closing" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.diameter_opening">
-<span class="sig-name descname"><span class="pre">diameter_opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">diameter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">8</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.diameter_opening"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.diameter_opening" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">diameter_opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">diameter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">8</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.diameter_opening"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.diameter_opening" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.dilation">
-<span class="sig-name descname"><span class="pre">dilation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.dilation"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.dilation" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">dilation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.dilation"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.dilation" title="Permalink to this definition">¶</a></dt>
 <dd><p>Morphological dilation. If input is binary image, the running function will automatically switched to
 <code class="docutils literal notranslate"><span class="pre">binary_dilation</span></code> to speed up calculation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -1484,10 +1522,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1495,20 +1533,20 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.distance_map">
-<span class="sig-name descname"><span class="pre">distance_map</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.distance_map"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.distance_map" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">distance_map</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.distance_map"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.distance_map" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate distance map from binary images.
 For instance, <code class="docutils literal notranslate"><span class="pre">[1,</span> <span class="pre">1,</span> <span class="pre">1,</span> <span class="pre">0,</span> <span class="pre">0,</span> <span class="pre">0,</span> <span class="pre">1,</span> <span class="pre">1,</span> <span class="pre">1]</span></code> will be converted to
 <code class="docutils literal notranslate"><span class="pre">[3,</span> <span class="pre">2,</span> <span class="pre">1,</span> <span class="pre">0,</span> <span class="pre">0,</span> <span class="pre">0,</span> <span class="pre">1,</span> <span class="pre">2,</span> <span class="pre">3]</span></code>. Note that returned array will be float in n-D
 images.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Distance map, the further the brighter</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1516,22 +1554,24 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.dog_filter">
-<span class="sig-name descname"><span class="pre">dog_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">low_sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">high_sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.dog_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.dog_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">dog_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">low_sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">high_sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fourier</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.dog_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.dog_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Run Difference of Gaussian filter. This function does not support <cite>update</cite>
 argument because intensity can be negative.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>low_sigma</strong> (<em>scalar</em><em> or </em><em>array of scalars</em><em>, </em><em>default is 1.</em>) – lower standard deviation(s) of Gaussian.</p></li>
-<li><p><strong>high_sigma</strong> (<em>scalar</em><em> or </em><em>array of scalars</em><em>, </em><em>default is x1.6 of low_sigma.</em>) – higher standard deviation(s) of Gaussian.</p></li>
+<li><p><strong>low_sigma</strong> (<em>scalar</em><em> or </em><em>array</em><em> of </em><em>scalars</em><em>, </em><em>default is 1.</em>) – lower standard deviation(s) of Gaussian.</p></li>
+<li><p><strong>high_sigma</strong> (<em>scalar</em><em> or </em><em>array</em><em> of </em><em>scalars</em><em>, </em><em>default is x1.6</em><em> of </em><em>low_sigma.</em>) – higher standard deviation(s) of Gaussian.</p></li>
+<li><p><strong>fourier</strong> (<em>bool</em><em>, </em><em>default is False</em>) – Whether to run the convolution in Fourier space. This option is useful when the kernel or the image is large.
+Note that discrete Fourier transform assumes that the image is periodic, so that if intensities of the input image are not consecutive at img[0] and img[-1], you may get some artifacts at the boundary.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1539,7 +1579,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.doh_filter">
-<span class="sig-name descname"><span class="pre">doh_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.doh_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.doh_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">doh_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.doh_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.doh_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Determinant of Hessian filter. This function does not support <cite>update</cite>
 argument because output has total different scale of intensity.</p>
 <blockquote>
@@ -1550,18 +1590,18 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </div>
 </div></blockquote>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array of float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
 If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1573,7 +1613,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dd><p>Drift correction using iterative Affine translation. If translation vectors <code class="docutils literal notranslate"><span class="pre">shift</span></code>
 is not given, then it will be determined using <code class="docutils literal notranslate"><span class="pre">track_drift</span></code> method of ImgArray.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>shift</strong> (<em>DataFrame</em><em> or </em><em>(</em><em>N</em><em>, </em><em>D</em><em>) </em><em>array</em><em>, </em><em>optional</em>) – Translation vectors. If DataFrame, it must have columns named with all the symbols
 contained in <code class="docutils literal notranslate"><span class="pre">dims</span></code>.</p></li>
@@ -1586,10 +1626,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>affine_kwargs</strong> – Keyword arguments that will be passed to <code class="docutils literal notranslate"><span class="pre">warp</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Corrected image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1604,10 +1644,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.edge_filter">
-<span class="sig-name descname"><span class="pre">edge_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'sobel'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.edge_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.edge_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">edge_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'sobel'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.edge_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.edge_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Sobel filter. This filter is useful for edge detection.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>method</strong> (<em>str</em><em>, </em><em>{&quot;sobel&quot;</em><em>, </em><em>&quot;farid&quot;</em><em>, </em><em>&quot;scharr&quot;</em><em>, </em><em>&quot;prewitt&quot;}</em><em>, </em><em>default is &quot;sobel&quot;</em>) – Edge operator name.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
@@ -1615,10 +1655,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1626,13 +1666,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.edge_grad">
-<span class="sig-name descname"><span class="pre">edge_grad</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'sobel'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">deg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">impy.arrays.phasearray.PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.edge_grad"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.edge_grad" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">edge_grad</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'sobel'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">deg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.edge_grad"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.edge_grad" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate gradient direction using horizontal and vertical edge operation. Gradient direction
 is the direction with maximum gradient, i.e., intensity increase is largest.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array of float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
 If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
 <li><p><strong>method</strong> (<em>str</em><em>, </em><em>{&quot;sobel&quot;</em><em>, </em><em>&quot;farid&quot;</em><em>, </em><em>&quot;scharr&quot;</em><em>, </em><em>&quot;prewitt&quot;}</em><em>, </em><em>default is &quot;sobel&quot;</em>) – Edge operator name.</p></li>
 <li><p><strong>deg</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, degree rather than radian is returned.</p></li>
@@ -1640,10 +1680,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Phase image with range [-180, 180) if deg==True, otherwise [-pi, pi).</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray">PhaseArray</a></p>
 </dd>
 </dl>
@@ -1662,10 +1702,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.enhance_contrast">
-<span class="sig-name descname"><span class="pre">enhance_contrast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.enhance_contrast"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.enhance_contrast" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">enhance_contrast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.enhance_contrast"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.enhance_contrast" title="Permalink to this definition">¶</a></dt>
 <dd><p>Enhance contrast filter.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -1690,10 +1730,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Contrast enhanced image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1701,10 +1741,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.entropy_filter">
-<span class="sig-name descname"><span class="pre">entropy_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.entropy_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.entropy_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">entropy_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.entropy_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.entropy_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Running entropy filter. This filter is useful for detecting change in background distribution.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -1728,10 +1768,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1739,12 +1779,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.erosion">
-<span class="sig-name descname"><span class="pre">erosion</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.erosion"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.erosion" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">erosion</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.erosion"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.erosion" title="Permalink to this definition">¶</a></dt>
 <dd><p>Morphological erosion.</p>
 <p>If input is binary image, the running function will automatically switched to
 <code class="docutils literal notranslate"><span class="pre">binary_erosion</span></code> to speed up calculation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -1771,10 +1811,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1782,21 +1822,21 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.estimate_sigma">
-<span class="sig-name descname"><span class="pre">estimate_sigma</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.estimate_sigma"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.estimate_sigma" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">estimate_sigma</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.estimate_sigma"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.estimate_sigma" title="Permalink to this definition">¶</a></dt>
 <dd><p>Wavelet-based estimation of Gaussian noise.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>squeeze</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True and output can be converted to a scalar, then convert it.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Estimated standard deviation. sigma[“t=0;c=1”] means the estimated value of
 image slice at t=0 and c=1.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray">PropArray</a> or float</p>
 </dd>
 </dl>
@@ -1808,9 +1848,9 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dd><p>Fast Fourier transformation. This function returns complex array, which is
 inconpatible with some ImgArray functions.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable of int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
+<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable</em><em> of </em><em>int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
 - integers: padded or cropped to the specified shape.
 - “square”: padded to smallest 2^N-long square.
 - “same” (default): no padding or cropping.</p></li>
@@ -1820,10 +1860,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>FFT image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1835,11 +1875,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.fill_hole">
-<span class="sig-name descname"><span class="pre">fill_hole</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">thr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'otsu'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.fill_hole"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.fill_hole" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fill_hole</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">thr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'otsu'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.fill_hole"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.fill_hole" title="Permalink to this definition">¶</a></dt>
 <dd><p>Filling holes. See skimage’s documents
 <a class="reference external" href="https://scikit-image.org/docs/stable/auto_examples/features_detection/plot_holes_and_peaks.html">here</a>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>thr</strong> (<em>scalar</em><em> or </em><em>str</em><em>, </em><em>optional</em>) – Threshold (value or method) to apply if image is not binary.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
@@ -1847,10 +1887,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Hole-filled image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1861,8 +1901,8 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">find_corners</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">nDFloat</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.find_corners" title="Permalink to this definition">¶</a></dt>
 <dd><p>Corner detection using Harris response.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array of float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
 If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p>
 </dd>
 </dl>
@@ -1877,10 +1917,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Coordinates of corners. For details see <code class="docutils literal notranslate"><span class="pre">corner_peaks</span></code> method.</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
 </dd>
 </dl>
@@ -1892,7 +1932,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dd><p>Single molecule detection using difference of Gaussian, determinant of Hessian, Laplacian of
 Gaussian or normalized cross correlation method.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>sigma</strong> (<em>float</em><em>, </em><em>optional</em>) – Standard deviation of puncta.</p></li>
 <li><p><strong>method</strong> (<em>str {&quot;dog&quot;</em><em>, </em><em>&quot;doh&quot;</em><em>, </em><em>&quot;log&quot;</em><em>, </em><em>&quot;gaussian&quot;</em><em>, </em><em>&quot;ncc&quot;}</em><em>, </em><em>default is &quot;dog&quot;</em>) – Which filter is used prior to finding local maxima. If “ncc”, a Gaussian particle is used as
@@ -1904,10 +1944,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>dims</strong> – Passed to <code class="docutils literal notranslate"><span class="pre">peak_local_max()</span></code></p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Peaks in uint16 type.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
 </dd>
 </dl>
@@ -1931,7 +1971,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dd><p>Flood filling with a list of seed points. By repeating skimage’s <code class="docutils literal notranslate"><span class="pre">flood</span></code> function,
 this method can perform segmentation of an image.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>seeds</strong> (<a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><em>MarkerFrame</em></a><em> or </em><em>(</em><em>N</em><em>, </em><em>D</em><em>) </em><em>array-like</em>) – Seed points to start flood filling.</p></li>
 <li><p><strong>connectivity</strong> (<em>int</em><em>, </em><em>optional</em>) – Connectivity of pixels. See <code class="docutils literal notranslate"><span class="pre">skimage.measure.label</span></code>.</p></li>
@@ -1940,10 +1980,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Labeled image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1951,20 +1991,20 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.focus_map">
-<span class="sig-name descname"><span class="pre">focus_map</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">impy.arrays.specials.PropArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.focus_map"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.focus_map" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">focus_map</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.focus_map"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.focus_map" title="Permalink to this definition">¶</a></dt>
 <dd><p>Compute focus map using variance of Laplacian method. yx-plane with higher variance is likely a
 focal plane because sharper image causes higher value of Laplacian on the edges.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>int</em><em>, </em><em>default is 1</em>) – Radius of Laplacian filter’s kernel.</p></li>
 <li><p><strong>{dims}</strong> – </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Array of variance of Laplacian</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray">PropArray</a></p>
 </dd>
 </dl>
@@ -1982,11 +2022,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.gabor_angle">
-<span class="sig-name descname"><span class="pre">gabor_angle</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_sample</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">180</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gamma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">phi</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">deg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">impy.arrays.phasearray.PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.gabor_angle"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.gabor_angle" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">gabor_angle</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_sample</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">180</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gamma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">phi</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">deg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.gabor_angle"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.gabor_angle" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate filament angles using Gabor filter. For all the candidates of angles, Gabor response is
 calculated, and the strongest response is returned as output array.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>n_sample</strong> (<em>int</em><em>, </em><em>default is 180</em>) – Number of <a href="#id7"><span class="problematic" id="id8">`</span></a>theta`s to calculate. By default, -90, -89, …, 89 degree are calculated.</p></li>
 <li><p><strong>lmd</strong> (<em>float</em><em>, </em><em>default is 5</em>) – Wave length of Gabor kernel. Make sure that the diameter of the objects you want to detect is
@@ -1999,10 +2039,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Phase image with range [-90, 90) if deg==True, otherwise [-pi/2, pi/2).</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2014,15 +2054,15 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.gabor_filter">
-<span class="sig-name descname"><span class="pre">gabor_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gamma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">phi</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_imag</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.gabor_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.gabor_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">gabor_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gamma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">phi</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_imag</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.gabor_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.gabor_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Make a Gabor kernel and convolve it.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>lmd</strong> (<em>float</em><em>, </em><em>default is 5</em>) – Wave length of Gabor kernel. Make sure that the diameter of the objects you want to detect is
 around <cite>lmd/2</cite>.</p></li>
 <li><p><strong>theta</strong> (<em>float</em><em>, </em><em>default is 0</em>) – Orientation of harmonic factor of Gabor kernel in radian (x-directional if <cite>theta==0</cite>).</p></li>
-<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array of float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
 If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
 <li><p><strong>gamma</strong> (<em>float</em><em>, </em><em>default is 1</em>) – Anisotropy of Gabor kernel, i.e. the standard deviation orthogonal to theta will be sigma/gamma.</p></li>
 <li><p><strong>phi</strong> (<em>float</em><em>, </em><em>default is 0</em>) – Phase offset of harmonic factor of Gabor kernel.</p></li>
@@ -2031,10 +2071,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a> (dtype is float32 or complex64)</p>
 </dd>
 </dl>
@@ -2053,23 +2093,23 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.gauss_correction">
-<span class="sig-name descname"><span class="pre">gauss_correction</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ref</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0625</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">median_radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">15</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.gauss_correction"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.gauss_correction" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">gauss_correction</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ref</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0625</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">median_radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">15</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.gauss_correction"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.gauss_correction" title="Permalink to this definition">¶</a></dt>
 <dd><p>Correct unevenly distributed excitation light using Gaussian fitting. This method subtracts
 background intensity at the same time. If input image is uint, then output value under 0 will
 replaced with 0. If you want to quantify background, it is necessary to first convert input
 image to float image.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>ref</strong> (ImgArray, default is <cite>self</cite>.) – Reference image to estimate background.</p></li>
 <li><p><strong>scale</strong> (<em>float</em><em>, </em><em>default is 1/16.</em>) – Scale of rough image (to speed up fitting).</p></li>
 <li><p><strong>median_radius</strong> (<em>float</em><em>, </em><em>default is 15.</em>) – Radius of median prefilter’s kernel. If smaller than 1, prefiltering will be skipped.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Corrected and background subtracted image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2091,7 +2131,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">gauss_sm</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coords</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filt</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">percentile</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">95</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_all</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.gauss_sm" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate positions of particles in subpixel precision using Gaussian fitting.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>coords</strong> (<a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><em>MarkerFrame</em></a><em> or </em><em>(</em><em>N</em><em>, </em><em>2</em><em>) </em><em>array</em><em>, </em><em>optional</em>) – Coordinates of peaks. If None, this will be determined by find_sm.</p></li>
 <li><p><strong>radius</strong> (<em>int</em><em>, </em><em>default is 4.</em>) – Fitting range. Rectangular image with size 2r+1 x 2r+1 will be send to Gaussian
@@ -2106,7 +2146,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>{dims}</strong> – </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p><ul class="simple">
 <li><p><em>MarkerFrame, if return_all == False</em> – Gaussian centers.</p></li>
 <li><p><em>DataDict with keys {means, sigmas, errors}, if return_all == True</em> – Dictionary that contains means, standard deviations and fitting errors.</p></li>
@@ -2118,22 +2158,22 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.gaussfit">
-<span class="sig-name descname"><span class="pre">gaussfit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0625</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Powell'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">np.ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'yx'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.gaussfit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.gaussfit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">gaussfit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0625</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Powell'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'yx'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.gaussfit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.gaussfit" title="Permalink to this definition">¶</a></dt>
 <dd><p>Fit the image to 2-D Gaussian background.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>scale</strong> (<em>float</em><em>, </em><em>default is 1/16.</em>) – Scale of rough image (to speed up fitting).</p></li>
-<li><p><strong>p0</strong> (<em>sequence of float</em><em>, </em><em>optional</em>) – Initial parameters.</p></li>
+<li><p><strong>p0</strong> (<em>sequence</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Initial parameters.</p></li>
 <li><p><strong>method</strong> (<em>str</em><em>, </em><em>optional</em>) – Fitting method. See <cite>scipy.optimize.minimize</cite>.</p></li>
 <li><p><strong>mask</strong> (<em>np.ndarray</em><em>, </em><em>optional</em><em>,</em>) – If given, ignore the True region from fitting.</p></li>
 <li><p><strong>{dims}</strong> – </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Fit image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2141,22 +2181,24 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.gaussian_filter">
-<span class="sig-name descname"><span class="pre">gaussian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.gaussian_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.gaussian_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">gaussian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fourier</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.gaussian_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.gaussian_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Run Gaussian filter (Gaussian blur).</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array of float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
 If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
+<li><p><strong>fourier</strong> (<em>bool</em><em>, </em><em>default is False</em>) – Whether to run the convolution in Fourier space. This option is useful when the kernel or the image is large.
+Note that discrete Fourier transform assumes that the image is periodic, so that if intensities of the input image are not consecutive at img[0] and img[-1], you may get some artifacts at the boundary.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2164,28 +2206,28 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.glcm_props">
-<span class="sig-name descname"><span class="pre">glcm_props</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">distances</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">angles</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">properties</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bins</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rescale_max</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.glcm_props"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.glcm_props" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">glcm_props</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">distances</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">angles</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">properties</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bins</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rescale_max</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.glcm_props"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.glcm_props" title="Permalink to this definition">¶</a></dt>
 <dd><p>Compute properties of “Gray Level Coocurrence Matrix”. This will take long time
 because of pure Python for-loop.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>distances</strong> (<em>array_like</em>) – List of pixel pair distance offsets.</p></li>
 <li><p><strong>angles</strong> (<em>array_like</em>) – List of pixel pair angles in radians.</p></li>
 <li><p><strong>radius</strong> (<em>int</em>) – Window radius.</p></li>
-<li><p><strong>properties</strong> (<em>tuple of str</em>) – contrast, dissimilarity, homogeneity, energy, mean, std, asm, max, entropy</p></li>
+<li><p><strong>properties</strong> (<em>tuple</em><em> of </em><em>str</em>) – contrast, dissimilarity, homogeneity, energy, mean, std, asm, max, entropy</p></li>
 <li><p><strong>bins</strong> (<em>int</em><em>, </em><em>optional</em>) – Number of bins.</p></li>
 <li><p><strong>rescale_max</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, the contrast of the input image is maximized by multiplying an integer.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>GLCM with additional axes “da”, where “d” means distance and “a” means angle.
 If input image has “tzyx” axes then output will have “tzd&lt;yx” axes.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
-<dd class="field-odd"><p>DataDict of ImgArray</p>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.html#impy.collections.DataDict" title="impy.collections.DataDict">DataDict</a> of <a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
 <p class="rubric">Examples</p>
@@ -2201,12 +2243,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.hessian_angle">
-<span class="sig-name descname"><span class="pre">hessian_angle</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">deg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">impy.arrays.phasearray.PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.hessian_angle"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.hessian_angle" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">hessian_angle</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">deg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.hessian_angle"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.hessian_angle" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate filament angles using Hessian’s eigenvectors.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array of float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
 If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
 <li><p><strong>deg</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, returned array will be in degree. Otherwise, radian will be the unit
 of angle.</p></li>
@@ -2214,10 +2256,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Phase image with range [-90, 90] if <code class="docutils literal notranslate"><span class="pre">deg==True</span></code>, otherwise [-pi/2, pi/2].</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2229,23 +2271,23 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.hessian_eig">
-<span class="sig-name descname"><span class="pre">hessian_eig</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.hessian_eig"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.hessian_eig" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">hessian_eig</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.hessian_eig"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.hessian_eig" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate Hessian’s eigenvalues and eigenvectors.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array of float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
 If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Arrays of eigenvalues and eigenvectors. The axis <code class="docutils literal notranslate"><span class="pre">&quot;base&quot;</span></code> denotes the index of
 eigenvalues. l=0 means the smallest eigenvalue. <code class="docutils literal notranslate"><span class="pre">&quot;dim&quot;</span></code> denotes the index of
 spatial dimensions. For 3D image, dim=0 means z-element of an eigenvector.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>ImgArray and ImgArray</p>
 </dd>
 </dl>
@@ -2253,22 +2295,22 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.hessian_eigval">
-<span class="sig-name descname"><span class="pre">hessian_eigval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.hessian_eigval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.hessian_eigval" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">hessian_eigval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.hessian_eigval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.hessian_eigval" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate Hessian’s eigenvalues for each image.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array of float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
 If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Array of eigenvalues. The axis <code class="docutils literal notranslate"><span class="pre">&quot;base&quot;</span></code> denotes the index of eigenvalues.
 l=0 means the smallest eigenvalue.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2284,10 +2326,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.highpass_filter">
-<span class="sig-name descname"><span class="pre">highpass_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.highpass_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.highpass_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">highpass_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.highpass_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.highpass_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Butterworth high-pass filter.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>cutoff</strong> (<em>float</em><em> or </em><em>array-like</em><em>, </em><em>default is 0.2</em>) – Cutoff frequency.</p></li>
 <li><p><strong>order</strong> (<em>float</em><em>, </em><em>default is 2</em>) – Steepness of cutoff.</p></li>
@@ -2296,10 +2338,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2307,10 +2349,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.ifft">
-<span class="sig-name descname"><span class="pre">ifft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">real</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">double_precision</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.ifft"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.ifft" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">ifft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">real</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">double_precision</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.ifft"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.ifft" title="Permalink to this definition">¶</a></dt>
 <dd><p>Fast Inverse Fourier transformation. Complementary function with <cite>fft()</cite>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>real</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, only the real part is returned.</p></li>
 <li><p><strong>shift</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, call <code class="docutils literal notranslate"><span class="pre">np.fft.ifftshift</span></code> at the first.</p></li>
@@ -2319,10 +2361,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>IFFT image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2330,10 +2372,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.inpaint">
-<span class="sig-name descname"><span class="pre">inpaint</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">numpy.ndarray</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mean'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'biharmonic'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'biharmonic'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.inpaint"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.inpaint" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">inpaint</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mean'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'biharmonic'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'biharmonic'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.inpaint"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.inpaint" title="Permalink to this definition">¶</a></dt>
 <dd><p>Image inpainting.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>mask</strong> (<em>np.ndarray</em>) – Mask image. The True region will be inpainted.</p></li>
 <li><p><strong>method</strong> (<em>&quot;mean&quot;</em><em> or </em><em>&quot;biharmonic&quot;</em><em>, </em><em>default is &quot;biharmonic&quot;</em>) – Inpainting method.</p></li>
@@ -2342,10 +2384,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Inpainted image of same data type.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2353,14 +2395,14 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.iradon">
-<span class="sig-name descname"><span class="pre">iradon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degrees</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">central_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxisLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'y'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">degree_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxisLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">height_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxisLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">height</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'hamming'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.iradon"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.iradon" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">iradon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degrees</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">central_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'y'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">degree_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">height_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">height</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'hamming'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.iradon"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.iradon" title="Permalink to this definition">¶</a></dt>
 <dd><p>Inverse Radon transformation (weighted back projection) of a tile series.</p>
 <p>Input array must be a tilt series of 1D or 2D images. They are back-
 projected into a 2D or 3D image with arbitrary height.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>degrees</strong> (<em>sequence of float</em>) – Projection angles in degree. Length must match the length of the degree
+<li><p><strong>degrees</strong> (<em>sequence</em><em> of </em><em>float</em>) – Projection angles in degree. Length must match the length of the degree
 axis of the input image.</p></li>
 <li><p><strong>central_axis</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Axis parallel to the rotation axis.</p></li>
 <li><p><strong>degree_axis</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Axis of rotation degree. By default, the first axis will be used.</p></li>
@@ -2378,10 +2420,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Reconstruction.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2393,11 +2435,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.kalman_filter">
-<span class="sig-name descname"><span class="pre">kalman_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">gain</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">noise_var</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'t'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.kalman_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.kalman_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">kalman_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">gain</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">noise_var</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'t'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.kalman_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.kalman_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Kalman filter for image smoothing. This function is same as “Kalman Stack Filter” in ImageJ but support
 batch processing. This filter is useful for preprocessing of particle tracking.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>gain</strong> (<em>float</em><em>, </em><em>default is 0.8</em>) – Filter gain.</p></li>
 <li><p><strong>noise_var</strong> (<em>float</em><em>, </em><em>default is 0.05</em>) – Initial estimate of noise variance.</p></li>
@@ -2407,10 +2449,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2423,17 +2465,17 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 different (in most cases for &gt;4D images) between threshold() and label().
 In this function, both function will have the same <code class="docutils literal notranslate"><span class="pre">dims</span></code> for simplicity.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>thr</strong> (<em>float</em><em> or </em><em>str</em><em> or </em><em>None</em><em>, </em><em>optional</em>) – Threshold value, or thresholding algorithm.</p></li>
 <li><p><strong>{dims}</strong> – </p></li>
 <li><p><strong>**kwargs</strong> – Keyword arguments that will passed to function indicated in ‘method’.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Newly created label.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label">Label</a></p>
 </dd>
 </dl>
@@ -2441,10 +2483,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.laplacian_filter">
-<span class="sig-name descname"><span class="pre">laplacian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.laplacian_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.laplacian_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">laplacian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.laplacian_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.laplacian_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Edge detection using Laplacian filter. Kernel is made by <cite>skimage</cite>’s function.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>int</em><em>, </em><em>default is 1</em>) – Radius of kernel. Shape of kernel will be (2*radius+1, 2*radius+1).</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
@@ -2452,10 +2494,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2463,10 +2505,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.lbp">
-<span class="sig-name descname"><span class="pre">lbp</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">12</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'default'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'ror'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'uniform'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'var'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.lbp"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.lbp" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">lbp</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">12</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'default'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'ror'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'uniform'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'var'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.lbp"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.lbp" title="Permalink to this definition">¶</a></dt>
 <dd><p>Local binary pattern feature extraction.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>p</strong> (<em>int</em><em>, </em><em>default is 12</em>) – Number of circular neighbors</p></li>
 <li><p><strong>radius</strong> (<em>int</em><em>, </em><em>default is 1</em>) – Radius of neighbours.</p></li>
@@ -2475,10 +2517,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Local binary pattern image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2486,7 +2528,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.local_dft">
-<span class="sig-name descname"><span class="pre">local_dft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesTargetedSlicer</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">nDInt</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">double_precision</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.local_dft"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.local_dft" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">local_dft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Slicer</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">double_precision</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.local_dft"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.local_dft" title="Permalink to this definition">¶</a></dt>
 <dd><p>Local discrete Fourier transformation (DFT). This function will be useful
 for Fourier transformation of small region of an image with a certain
 factor of up-sampling. In general FFT takes <span class="math notranslate nohighlight">\(O(N\log{N})\)</span> time, much
@@ -2505,23 +2547,23 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <p>Even whole spectrum is returned, <code class="docutils literal notranslate"><span class="pre">local_dft</span></code> may be faster than FFT with
 small and/or non-FFT-friendly shaped image.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>key</strong> (<em>str</em>) – Key string that specify region to DFT, such as “y=-50:10;x=:80”. With
 upsampled spectra, keys corresponds to the coordinate <strong>before</strong>
 up-sampling. If you want certain region, say “x=10:20”, this value
 will not change with different <code class="docutils literal notranslate"><span class="pre">upsample_factor</span></code>.</p></li>
-<li><p><strong>upsample_factor</strong> (<em>int</em><em> or </em><em>array of int</em><em>, </em><em>default is 1</em>) – Up-sampling factor. For instance, when <code class="docutils literal notranslate"><span class="pre">upsample_factor=10</span></code> a single
+<li><p><strong>upsample_factor</strong> (<em>int</em><em> or </em><em>array</em><em> of </em><em>int</em><em>, </em><em>default is 1</em>) – Up-sampling factor. For instance, when <code class="docutils literal notranslate"><span class="pre">upsample_factor=10</span></code> a single
 pixel will be expanded to 10 pixels.</p></li>
 <li><p><strong>double_precision</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, FFT will be calculated using 64-bit float and 128-bit complex.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>DFT output.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2533,15 +2575,15 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.local_power_spectra">
-<span class="sig-name descname"><span class="pre">local_power_spectra</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesTargetedSlicer</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">nDInt</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">double_precision</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.local_power_spectra"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.local_power_spectra" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">local_power_spectra</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Slicer</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">double_precision</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.local_power_spectra"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.local_power_spectra" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return local n-D power spectra of images. See <code class="docutils literal notranslate"><span class="pre">local_dft</span></code>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>key</strong> (<em>str</em>) – Key string that specify region to DFT, such as “y=-50:10;x=:80”. With Upsampled spectra, keys
 corresponds to the coordinate <strong>before</strong> up-sampling. If you want certain region, say “x=10:20”,
 this value will not change with different <code class="docutils literal notranslate"><span class="pre">upsample_factor</span></code>.</p></li>
-<li><p><strong>upsample_factor</strong> (<em>int</em><em> or </em><em>array of int</em><em>, </em><em>default is 1</em>) – Up-sampling factor. For instance, when <code class="docutils literal notranslate"><span class="pre">upsample_factor=10</span></code> a single pixel will be expanded to
+<li><p><strong>upsample_factor</strong> (<em>int</em><em> or </em><em>array</em><em> of </em><em>int</em><em>, </em><em>default is 1</em>) – Up-sampling factor. For instance, when <code class="docutils literal notranslate"><span class="pre">upsample_factor=10</span></code> a single pixel will be expanded to
 10 pixels.</p></li>
 <li><p><strong>norm</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, maximum value of power spectra is adjusted to 1.</p></li>
 <li><p><strong>double_precision</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, FFT will be calculated using 64-bit float and 128-bit complex.</p></li>
@@ -2549,10 +2591,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Power spectra</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2564,21 +2606,21 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.log_filter">
-<span class="sig-name descname"><span class="pre">log_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.log_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.log_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">log_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.log_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.log_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Laplacian of Gaussian filter.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array of float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
 If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2586,11 +2628,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.lowpass_conv_filter">
-<span class="sig-name descname"><span class="pre">lowpass_conv_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.lowpass_conv_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.lowpass_conv_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">lowpass_conv_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.lowpass_conv_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.lowpass_conv_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Butterworth low-pass filter in real space. Butterworth kernel is created first using inverse
 Fourier transform of weight function.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>cutoff</strong> (<em>float</em><em> or </em><em>array-like</em><em>, </em><em>default is 0.2</em>) – Cutoff frequency.</p></li>
 <li><p><strong>order</strong> (<em>float</em><em>, </em><em>default is 2</em>) – Steepness of cutoff.</p></li>
@@ -2599,10 +2641,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2610,10 +2652,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.lowpass_filter">
-<span class="sig-name descname"><span class="pre">lowpass_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.lowpass_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.lowpass_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">lowpass_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.lowpass_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.lowpass_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Butterworth low-pass filter.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>cutoff</strong> (<em>float</em><em> or </em><em>array-like</em><em>, </em><em>default is 0.2</em>) – Cutoff frequency.</p></li>
 <li><p><strong>order</strong> (<em>float</em><em>, </em><em>default is 2</em>) – Steepness of cutoff.</p></li>
@@ -2622,10 +2664,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2633,25 +2675,26 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.lucy">
-<span class="sig-name descname"><span class="pre">lucy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">numpy.ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">niter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1e-05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.lucy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.lucy" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">lucy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">niter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1e-05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.lucy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.lucy" title="Permalink to this definition">¶</a></dt>
 <dd><p>Deconvolution of N-dimensional image, using Richardson-Lucy’s algorithm.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>psf</strong> (<em>np.ndarray</em>) – Point spread function.</p></li>
+<li><p><strong>psf</strong> (<em>ndarray</em><em> or </em><em>callable</em>) – Point spread function. If a function is given, <cite>psf(shape)</cite> will be
+called to generate the PSF.</p></li>
 <li><p><strong>niter</strong> (<em>int</em><em>, </em><em>default is 50.</em>) – Number of iterations.</p></li>
-<li><p><strong>eps</strong> (<em>float</em><em>, </em><em>default is 1e-5</em>) – During deconvolution, division by small values in the convolve image of estimation and
-PSF may cause divergence. Therefore, division by values under <cite>eps</cite> is substituted
-to zero.</p></li>
+<li><p><strong>eps</strong> (<em>float</em><em>, </em><em>default is 1e-5</em>) – During deconvolution, division by small values in the convolve image
+of estimation and PSF may cause divergence. Therefore, division by
+values under <cite>eps</cite> is substituted to zero.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Deconvolved image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2663,7 +2706,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.lucy_tv">
-<span class="sig-name descname"><span class="pre">lucy_tv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">numpy.ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_iter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tol</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1e-05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.lucy_tv"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.lucy_tv" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">lucy_tv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_iter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tol</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1e-05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.lucy_tv"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.lucy_tv" title="Permalink to this definition">¶</a></dt>
 <dd><blockquote>
 <div><p>Deconvolution of N-dimensional image, using Richardson-Lucy’s algorithm with
 total variance regularization (so called RL-TV algorithm). The TV regularization
@@ -2673,7 +2716,8 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <p>(<span class="math notranslate nohighlight">\(I(x)\)</span>: image, <span class="math notranslate nohighlight">\(\lambda\)</span>: constant)</p>
 <p>and this factor is multiplied for every estimation made in each iteration.</p>
 <dl>
-<dt>psf<span class="classifier">np.ndarray</span></dt><dd><p>Point spread function.</p>
+<dt>psf<span class="classifier">ndarray or callable</span></dt><dd><p>Point spread function. If a function is given, <cite>psf(shape)</cite> will be
+called to generate the PSF.</p>
 </dd>
 <dt>max_iter<span class="classifier">int, default is 50.</span></dt><dd><p>Maximum number of iterations.</p>
 </dd>
@@ -2718,10 +2762,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.mean_filter">
-<span class="sig-name descname"><span class="pre">mean_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.mean_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.mean_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">mean_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.mean_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.mean_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Mean filter. Kernel is filled with same values.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -2748,10 +2792,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2759,11 +2803,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.median_filter">
-<span class="sig-name descname"><span class="pre">median_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.median_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.median_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">median_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.median_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.median_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Running multi-dimensional median filter.</p>
 <p>This filter is useful for deleting outliers generated by noise.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -2790,10 +2834,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2801,12 +2845,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.ncc_filter">
-<span class="sig-name descname"><span class="pre">ncc_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="pre">template:</span> <span class="pre">np.ndarray,</span> <span class="pre">mode:</span> <span class="pre">str</span> <span class="pre">=</span> <span class="pre">'constant',</span> <span class="pre">cval:</span> <span class="pre">float</span> <span class="pre">|</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">Callable[[np.ndarray],</span> <span class="pre">float]</span> <span class="pre">=</span> <span class="pre">&lt;function</span> <span class="pre">mean&gt;,</span> <span class="pre">*,</span> <span class="pre">dims:</span> <span class="pre">Dims</span> <span class="pre">=</span> <span class="pre">None</span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.ncc_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.ncc_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">ncc_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="pre">template:</span> <span class="pre">~numpy.ndarray,</span> <span class="pre">mode:</span> <span class="pre">str</span> <span class="pre">=</span> <span class="pre">'constant',</span> <span class="pre">cval:</span> <span class="pre">float</span> <span class="pre">|</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">~typing.Callable[[~numpy.ndarray],</span> <span class="pre">float]</span> <span class="pre">=</span> <span class="pre">&lt;function</span> <span class="pre">mean&gt;,</span> <span class="pre">*,</span> <span class="pre">dims:</span> <span class="pre">~typing.Sequence[str</span> <span class="pre">|</span> <span class="pre">~impy.axes._axis.Axis]</span> <span class="pre">|</span> <span class="pre">int</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.ncc_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.ncc_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Template matching using normalized cross correlation (NCC) method. This function is basically
 identical to that in <cite>skimage.feature</cite>, but is optimized for batch processing and improved
 readability.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>template</strong> (<em>np.ndarray</em>) – Template image. Must be 2 or 3 dimensional.</p></li>
 <li><p><strong>{mode}</strong> – </p></li>
@@ -2815,10 +2859,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>{dims}</strong> – </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Response image with values between -1 and 1.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2826,11 +2870,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.opening">
-<span class="sig-name descname"><span class="pre">opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.opening"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.opening" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.opening"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.opening" title="Permalink to this definition">¶</a></dt>
 <dd><p>Morphological opening. If input is binary image, the running function will automatically switched to
 <code class="docutils literal notranslate"><span class="pre">binary_opening</span></code> to speed up calculation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -2857,10 +2901,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2868,10 +2912,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.pad">
-<span class="sig-name descname"><span class="pre">pad</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pad_width</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">PaddingMode</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.pad"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.pad" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">pad</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pad_width</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.pad"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.pad" title="Permalink to this definition">¶</a></dt>
 <dd><p>Pad image only for spatial dimensions.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>pad_width</strong> – See documentation of np.pad().</p></li>
 <li><p><strong>mode</strong> – See documentation of np.pad().</p></li>
@@ -2879,10 +2923,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>dims</strong> (<em>int</em><em> or </em><em>str</em><em>, </em><em>optional</em>) – Which dimension to pad.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Padded image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2922,11 +2966,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.pad_defocus">
-<span class="sig-name descname"><span class="pre">pad_defocus</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kernel</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">width</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">6</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.pad_defocus"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.pad_defocus" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">pad_defocus</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kernel</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">width</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">6</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.pad_defocus"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.pad_defocus" title="Permalink to this definition">¶</a></dt>
 <dd><p>Make a z-directional padded image by defocusing the original image. This padding is
 useful when applying FFT to a 3D image.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>kernel</strong> (<em>0-</em><em>, </em><em>1-</em><em> or </em><em>3-dimensional array.</em>) – If 0- (scalar) or 1-dimensional array was given, this is interpreted as standard
 deviation of Gaussian kernel. If 3-dimensional array was given, this is directly
@@ -2939,10 +2983,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 the original image.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Padded image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2961,7 +3005,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">peak_local_max</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_distance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">percentile</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">topn</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">inf</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">topn_per_label</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">inf</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exclude_border</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_labels</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><span class="pre">MarkerFrame</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.peak_local_max"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.peak_local_max" title="Permalink to this definition">¶</a></dt>
 <dd><p>Find local maxima. This algorithm corresponds to ImageJ’s ‘Find Maxima’ but is more flexible.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>min_distance</strong> (<em>float</em><em>, </em><em>default is 1.0</em>) – Minimum distance allowed for each two peaks. This parameter is slightly
 different from that in <code class="docutils literal notranslate"><span class="pre">skimage.feature.peak_local_max</span></code> because here float
@@ -2974,12 +3018,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>DataFrame with columns same as axes of self. For example, if self.axes is “tcyx” then
 return value has “t”, “c”, “y” and “x” columns, and sub-frame at t=0, c=0 contains all
 the coordinates of peaks in the slice at t=0, c=0.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
 </dd>
 </dl>
@@ -2987,27 +3031,28 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.power_spectra">
-<span class="sig-name descname"><span class="pre">power_spectra</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">FftShape</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'same'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">zero_norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">double_precision</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.power_spectra"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.power_spectra" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">power_spectra</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">FftShape</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'same'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">zero_norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">double_precision</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.power_spectra"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.power_spectra" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return n-D power spectra of images, which is defined as:</p>
 <div class="math notranslate nohighlight">
 \[P = Re(F[I_{img}])^2 + Im(F[I_{img}])^2\]</div>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable of int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
+<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable</em><em> of </em><em>int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
 - integers: padded or cropped to the specified shape.
 - “square”: padded to smallest 2^N-long square.
 - “same” (default): no padding or cropping.</p></li>
 <li><p><strong>norm</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, maximum value of power spectra is adjusted to 1.</p></li>
 <li><p><strong>double_precision</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, FFT will be calculated using 64-bit float and 128-bit complex.</p></li>
+<li><p><strong>shift</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, call <code class="docutils literal notranslate"><span class="pre">np.fft.fftshift</span></code> at the first.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Power spectra</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3019,10 +3064,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.proj">
-<span class="sig-name descname"><span class="pre">proj</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxisLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.proj"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.proj" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">proj</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.proj"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.proj" title="Permalink to this definition">¶</a></dt>
 <dd><p>Projection along any axis.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>axis</strong> (<em>str</em><em>, </em><em>optional</em>) – Along which axis projection will be calculated. If None, most plausible one will be chosen.</p></li>
 <li><p><strong>method</strong> (<em>str</em><em> or </em><em>callable</em><em>, </em><em>default is mean-projection.</em>) – Projection method. If str is given, it will converted to numpy function.</p></li>
@@ -3031,10 +3076,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>**kwargs</strong> – Other keyword arguments that will passed to projection function.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Projected image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3042,15 +3087,15 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.radial_profile">
-<span class="sig-name descname"><span class="pre">radial_profile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">nbin</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">r_max</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">impy.arrays.specials.PropArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.radial_profile"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.radial_profile" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">radial_profile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">nbin</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">r_max</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.radial_profile"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.radial_profile" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate radial profile of images. Scale along each axis will be considered,
 i.e., rather ellipsoidal profile will be calculated instead if scales are
 different between axes.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>nbin</strong> (<em>int</em><em>, </em><em>default is 32</em>) – Number of bins.</p></li>
-<li><p><strong>center</strong> (<em>iterable of float</em><em>, </em><em>optional</em>) – The coordinate of center of radial profile. By default, the center of image
+<li><p><strong>center</strong> (<em>iterable</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – The coordinate of center of radial profile. By default, the center of image
 is used.</p></li>
 <li><p><strong>r_max</strong> (<em>float</em><em>, </em><em>optional</em>) – Maximum radius to make profile. Region 0 &lt;= r &lt; r_max will be split into
 <code class="docutils literal notranslate"><span class="pre">nbin</span></code> rings (or shells). <strong>Scale must be considered</strong> because scales of
@@ -3062,11 +3107,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Radial profile stored in x-axis by default. If input image has tzcyx-axes, then an array
 with tcx-axes will be returned.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray">PropArray</a></p>
 </dd>
 </dl>
@@ -3074,15 +3119,15 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.radon">
-<span class="sig-name descname"><span class="pre">radon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degrees</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">central_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxisLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.radon"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.radon" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">radon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degrees</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">central_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.radon"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.radon" title="Permalink to this definition">¶</a></dt>
 <dd><p>Discrete Radon transformation of 2D or 3D image.</p>
 <p>Radon transformation is a list of projection of a same image from different angles.
 It generates tomographic n-D image slices from (n+1)-D image.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>degrees</strong> (<em>float</em><em> or </em><em>iterable of float</em>) – Rotation angles around the central axis in degrees.</p></li>
-<li><p><strong>central_axis</strong> (<em>axis-like</em><em> or </em><em>sequence of float</em><em>, </em><em>optional</em>) – Vector that defines the central axis of rotation.</p></li>
+<li><p><strong>degrees</strong> (<em>float</em><em> or </em><em>iterable</em><em> of </em><em>float</em>) – Rotation angles around the central axis in degrees.</p></li>
+<li><p><strong>central_axis</strong> (<em>axis-like</em><em> or </em><em>sequence</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Vector that defines the central axis of rotation.</p></li>
 <li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
 For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
 </p></li>
@@ -3090,13 +3135,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Tomographic image slices. The first spatial axis (“z” for zyx-image) will be dropped.
 If sequence of float is given as <code class="docutils literal notranslate"><span class="pre">degrees</span></code>, “degree” axis will be newly added at
 the position 0. For instance, if a zyx-image and <code class="docutils literal notranslate"><span class="pre">degrees=np.linspace(0,</span> <span class="pre">180,</span> <span class="pre">100)</span></code>
 are given, returned image has axes [“degree”, “y”, “x”].</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3108,11 +3153,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.random_walker">
-<span class="sig-name descname"><span class="pre">random_walker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">beta</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">130</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'cg'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'cg_j'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'cg_mg'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'bf'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'cg_j'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tol</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">impy.arrays.label.Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.random_walker"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.random_walker" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">random_walker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">beta</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">130</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'cg'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'cg_j'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'cg_mg'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'bf'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'cg_j'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tol</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.random_walker"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.random_walker" title="Permalink to this definition">¶</a></dt>
 <dd><p>Random walker segmentation. Only wrapped skimage segmentation.</p>
 <p><code class="docutils literal notranslate"><span class="pre">self.labels</span></code> will be segmented and updated inplace.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>beta</strong> – see skimage.segmentation.random_walker</p></li>
 <li><p><strong>mode</strong> – see skimage.segmentation.random_walker</p></li>
@@ -3121,10 +3166,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Relabeled image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3139,18 +3184,18 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 analyzed with <code class="docutils literal notranslate"><span class="pre">properties=(&quot;X&quot;,</span> <span class="pre">&quot;Y&quot;)</span></code>, then you can get X’s time-course profile
 of channel 1 at label 3 by <code class="docutils literal notranslate"><span class="pre">prop[&quot;X&quot;][&quot;p=5;c=1&quot;]</span></code> or <code class="docutils literal notranslate"><span class="pre">prop.X[&quot;p=5;c=1&quot;]</span></code>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>properties</strong> (<em>iterable</em><em>, </em><em>optional</em>) – properties to analyze, see <code class="docutils literal notranslate"><span class="pre">skimage.measure.regionprops</span></code>.</p></li>
-<li><p><strong>extra_properties</strong> (<em>iterable of callable</em><em>, </em><em>optional</em>) – extra properties to analyze, see <code class="docutils literal notranslate"><span class="pre">skimage.measure.regionprops</span></code>.</p></li>
+<li><p><strong>extra_properties</strong> (<em>iterable</em><em> of </em><em>callable</em><em>, </em><em>optional</em>) – extra properties to analyze, see <code class="docutils literal notranslate"><span class="pre">skimage.measure.regionprops</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Dictionary has keys of properties that are specified by <cite>properties</cite>. Each value
 has the array of properties.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
-<dd class="field-odd"><p>DataDict of PropArray</p>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.html#impy.collections.DataDict" title="impy.collections.DataDict">DataDict</a> of <a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray">PropArray</a></p>
 </dd>
 </dl>
 <p class="rubric">Examples</p>
@@ -3164,10 +3209,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.remove_fine_objects">
-<span class="sig-name descname"><span class="pre">remove_fine_objects</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.remove_fine_objects"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.remove_fine_objects" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">remove_fine_objects</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.remove_fine_objects"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.remove_fine_objects" title="Permalink to this definition">¶</a></dt>
 <dd><p>Remove fine objects using diameter_opening.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>length</strong> (<em>float</em><em>, </em><em>default is 10</em>) – Objects longer than this will be removed.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
@@ -3175,10 +3220,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Image with large objects removed.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3190,11 +3235,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.remove_large_objects">
-<span class="sig-name descname"><span class="pre">remove_large_objects</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.remove_large_objects"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.remove_large_objects" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">remove_large_objects</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.remove_large_objects"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.remove_large_objects" title="Permalink to this definition">¶</a></dt>
 <dd><p>Remove large objects using opening. Those objects that were not removed by opening
 will be removed in output.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – Objects with radius larger than this value will be removed.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
@@ -3202,10 +3247,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Image with large objects removed.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3217,10 +3262,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.remove_skeleton_structure">
-<span class="sig-name descname"><span class="pre">remove_skeleton_structure</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">structure</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'tip'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'branch'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'cross'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'tip'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.remove_skeleton_structure"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.remove_skeleton_structure" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">remove_skeleton_structure</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">structure</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'tip'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'branch'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'cross'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'tip'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.remove_skeleton_structure"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.remove_skeleton_structure" title="Permalink to this definition">¶</a></dt>
 <dd><p>Remove certain structure from skeletonized images.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>structure</strong> (<em>str</em><em>, </em><em>default is &quot;tip&quot;</em>) – What type of structure to remove.</p></li>
 <li><p><strong>connectivity</strong> (<em>int</em><em>, </em><em>optional</em>) – Connectivity of pixels. See <code class="docutils literal notranslate"><span class="pre">skimage.measure.label</span></code>.</p></li>
@@ -3229,10 +3274,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Processed image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3240,12 +3285,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.rescale">
-<span class="sig-name descname"><span class="pre">rescale</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0625</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.rescale"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.rescale" title="Permalink to this definition">¶</a></dt>
-<dd><p>Rescale image.</p>
+<span class="sig-name descname"><span class="pre">rescale</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0625</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.rescale"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.rescale" title="Permalink to this definition">¶</a></dt>
+<dd><p>Rescale image by applying the diagonal component of Affine matrix.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>scale</strong> (<em>float</em><em>, </em><em>optional</em>) – scale of the new image.</p></li>
+<li><p><strong>scale</strong> (<em>float</em><em>, </em><em>optional</em>) – Relative scale of the new image. scale 1/2 means that the shape of
+the output image will be (N/2, …).</p></li>
 <li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
 For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
 </p></li>
@@ -3255,10 +3301,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Rescaled image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3269,16 +3315,16 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">rescale_intensity</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">in_range:</span> <span class="pre">tuple[int</span> <span class="pre">|</span> <span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">int</span> <span class="pre">|</span> <span class="pre">str]</span> <span class="pre">=</span> <span class="pre">('0%'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">'100%')</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype=&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.rescale_intensity"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.rescale_intensity" title="Permalink to this definition">¶</a></dt>
 <dd><p>Rescale the intensity of the image using skimage.exposure.rescale_intensity().</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>in_range</strong> (<em>two scalar values</em><em>, </em><em>default is</em><em> (</em><em>0%</em><em>, </em><em>100%</em><em>)</em>) – Range of lower/upper limit.</p></li>
 <li><p><strong>dtype</strong> (<em>numpy dtype</em><em>, </em><em>default is np.uint16</em>) – Output dtype.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Rescaled image with temporal attribute</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3286,10 +3332,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.rof_filter">
-<span class="sig-name descname"><span class="pre">rof_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tol</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_iter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.rof_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.rof_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">rof_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tol</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_iter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.rof_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.rof_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Rudin-Osher-Fatemi’s total variation denoising.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>lmd</strong> (<em>float</em><em>, </em><em>default is 0.05</em>) – Constant value in total variation.</p></li>
 <li><p><strong>tol</strong> (<em>float</em><em>, </em><em>default is 1e-4</em>) – Iteration stops when gain is under this value.</p></li>
@@ -3299,10 +3345,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3310,10 +3356,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.rolling_ball">
-<span class="sig-name descname"><span class="pre">rolling_ball</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefilter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mean'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'median'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'none'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_bg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.rolling_ball"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.rolling_ball" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">rolling_ball</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefilter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mean'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'median'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'none'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_bg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.rolling_ball"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.rolling_ball" title="Permalink to this definition">¶</a></dt>
 <dd><p>Subtract Background using rolling-ball algorithm.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -3339,10 +3385,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Background subtracted image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3350,11 +3396,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.rotate">
-<span class="sig-name descname"><span class="pre">rotate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'center'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'center'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">PaddingMode</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.rotate"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.rotate" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">rotate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'center'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'center'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.rotate"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.rotate" title="Permalink to this definition">¶</a></dt>
 <dd><p>2D rotation of an image around a point. Outside will be padded with zero. For n-D images,
 this implementation is faster than <code class="docutils literal notranslate"><span class="pre">scipy.ndimage.rotate</span></code>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>degree</strong> (<em>float</em>) – Clockwise degree of rotation. Not radian.</p></li>
 <li><p><strong>center</strong> (<em>str</em><em> or </em><em>array-like</em><em>, </em><em>optional</em>) – Rotation center coordinate. By default the center of image will be the rotation center.</p></li>
@@ -3368,10 +3414,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Rotated image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3379,10 +3425,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.skeletonize">
-<span class="sig-name descname"><span class="pre">skeletonize</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.skeletonize"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.skeletonize" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">skeletonize</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.skeletonize"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.skeletonize" title="Permalink to this definition">¶</a></dt>
 <dd><p>Skeletonize images. Only works for binary images.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – Radius of skeleton. This is achieved simply by dilation of skeletonized results.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
@@ -3390,10 +3436,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Skeletonized image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3401,12 +3447,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.smooth_mask">
-<span class="sig-name descname"><span class="pre">smooth_mask</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dilate_radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask_light</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.smooth_mask"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.smooth_mask" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">smooth_mask</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dilate_radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask_light</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.smooth_mask"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.smooth_mask" title="Permalink to this definition">¶</a></dt>
 <dd><p>Smoothen binary mask image at its edges. This is useful to make a “soft mask”.</p>
 <p>This method applies erosion/dilation to a binary image and then smooth its edges by Gaussian.
 The total value is always larger after Gaussian smoothing.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>sigma</strong> (<em>float</em><em>, </em><em>default is 2.0</em>) – Standard deviation of Gaussian blur.</p></li>
 <li><p><strong>dilate_radius</strong> (<em>float</em><em>, </em><em>default is 2.0</em>) – Radius in pixel that will be used to dilate mask before smoothing.</p></li>
@@ -3416,10 +3462,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Smoothened mask image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3427,19 +3473,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.split_pixel_unit">
-<span class="sig-name descname"><span class="pre">split_pixel_unit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">(0.5,</span> <span class="pre">0.5)</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">angle_order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">newaxis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxisLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'a'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.split_pixel_unit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.split_pixel_unit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">split_pixel_unit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">(0.5,</span> <span class="pre">0.5)</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">angle_order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">newaxis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'a'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.split_pixel_unit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.split_pixel_unit" title="Permalink to this definition">¶</a></dt>
 <dd><p>Split a (2N, 2M)-image into four (N, M)-images for each other pixels.</p>
 <p>Generally, image acquisition with a polarization camera will output
 <span class="math notranslate nohighlight">\((2N, 2M)\)</span>-image with <span class="math notranslate nohighlight">\(N \times M\)</span> pixel units:</p>
 <table class="docutils align-default">
-<colgroup>
-<col style="width: 17%" />
-<col style="width: 17%" />
-<col style="width: 17%" />
-<col style="width: 17%" />
-<col style="width: 17%" />
-<col style="width: 17%" />
-</colgroup>
 <tbody>
 <tr class="row-odd"><td><p>0</p></td>
 <td><p>1</p></td>
@@ -3477,7 +3515,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 acquired from different positions). This function also complements for
 this difference by interpolation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>center</strong> (<em>tuple</em><em>, </em><em>default is</em><em> (</em><em>0</em><em>, </em><em>0</em><em>)</em>) – Coordinate that will be considered as the center of the returned
 image. Input (a, b) must satisfy 0 &lt; a &lt; 1 and 0 &lt; b &lt; 1. For example,
 center=(0, 0) means the most upper left pixel, and center=(0.5, 0.5)
@@ -3504,11 +3542,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Axis “a” is added in the first dimension. For example, If input is
 “tyx”-axes, then output will be “atyx”-axes.</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3524,10 +3562,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.std_filter">
-<span class="sig-name descname"><span class="pre">std_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.std_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.std_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">std_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.std_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.std_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Standard deviation filter.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -3553,10 +3591,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3564,7 +3602,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.stokes">
-<span class="sig-name descname"><span class="pre">stokes</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'a'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">dict</span></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.stokes"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.stokes" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">stokes</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'a'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">dict</span></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.stokes"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.stokes" title="Permalink to this definition">¶</a></dt>
 <dd><p>Generate stocks images from an image stack with polarized images.</p>
 <p>Currently, Degree of Linear Polarization (DoLP) and Angle of
 Polarization (AoP) will be calculated. Those irregular values
@@ -3572,15 +3610,15 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 DoPL correctly background subtraction must be applied beforehand because
 stokes parameter <code class="docutils literal notranslate"><span class="pre">s0</span></code> is affected by absolute intensities.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>along</strong> (<em>AxisLike</em><em>, </em><em>default is &quot;a&quot;</em>) – To define which axis is polarization angle axis. Along this axis
 the angle of polarizer must be in order of 0, 45, 90, 135 degree.</p>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Dictionaly with keys “dolp” and “aop”, which correspond to DoPL and
 AoP respectively.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>dict</p>
 </dd>
 </dl>
@@ -3604,10 +3642,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.stretch">
-<span class="sig-name descname"><span class="pre">stretch</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">nDFloat</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'center'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'center'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">PaddingMode</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.stretch"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.stretch" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">stretch</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'center'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'center'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.stretch"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.stretch" title="Permalink to this definition">¶</a></dt>
 <dd><p>2D stretching of an image from a point.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>scale</strong> (<em>array-like</em>) – Stretch factors.</p></li>
 <li><p><strong>center</strong> (<em>str</em><em> or </em><em>array-like</em><em>, </em><em>optional</em>) – Rotation center coordinate. By default the center of image will be the rotation center.</p></li>
@@ -3620,10 +3658,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Stretched image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3631,23 +3669,23 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.structure_tensor_eig">
-<span class="sig-name descname"><span class="pre">structure_tensor_eig</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.structure_tensor_eig"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.structure_tensor_eig" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">structure_tensor_eig</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.structure_tensor_eig"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.structure_tensor_eig" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate structure tensor’s eigenvalues and eigenvectors.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array of float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
 If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Arrays of eigenvalues and eigenvectors. The axis <code class="docutils literal notranslate"><span class="pre">&quot;l&quot;</span></code> denotes the index of
 eigenvalues. l=0 means the smallest eigenvalue. <code class="docutils literal notranslate"><span class="pre">&quot;r&quot;</span></code> denotes the index of
 spatial dimensions. For 3D image, r=0 means z-element of an eigenvector.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>ImgArray and ImgArray</p>
 </dd>
 </dl>
@@ -3655,22 +3693,22 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.structure_tensor_eigval">
-<span class="sig-name descname"><span class="pre">structure_tensor_eigval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.structure_tensor_eigval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.structure_tensor_eigval" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">structure_tensor_eigval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.structure_tensor_eigval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.structure_tensor_eigval" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate structure tensor’s eigenvalues and eigenvectors.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array of float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
 If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Array of eigenvalues. The axis <code class="docutils literal notranslate"><span class="pre">&quot;l&quot;</span></code> denotes the index of eigenvalues.
 l=0 means the smallest eigenvalue.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3683,7 +3721,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <p>The threshold value can be given with a float or a string that indicates what
 thresholding method will be used.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>thr</strong> (<em>float</em><em> or </em><em>str</em><em>, </em><em>optional</em>) – Threshold value, percentage or thresholding algorithm.</p></li>
 <li><p><strong>along</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Dimensions that will not share the same threshold. For instance, if
@@ -3692,10 +3730,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>**kwargs</strong> – Keyword arguments that will passed to function indicated in ‘method’.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Boolian array.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3709,38 +3747,27 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 </dd></dl>
 
+<dl class="py attribute">
+<dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.tiled">
+<span class="sig-name descname"><span class="pre">tiled</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.tiled.TiledAccessor" title="impy.arrays.tiled.TiledAccessor"><span class="pre">TiledAccessor</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.tiled" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.tiled_lowpass_filter">
-<span class="sig-name descname"><span class="pre">tiled_lowpass_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">overlap</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">16</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.tiled_lowpass_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.tiled_lowpass_filter" title="Permalink to this definition">¶</a></dt>
-<dd><p>Tile-by-tile Butterworth low-pass filter. This method is an approximation of the standard
-low-pass filter, which would be useful when the image is large.</p>
-<dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><ul class="simple">
-<li><p><strong>cutoff</strong> (<em>float</em><em> or </em><em>array-like</em><em>, </em><em>default is 0.2</em>) – Cutoff frequency.</p></li>
-<li><p><strong>chunks</strong> (<em>str</em><em> or </em><em>sequence of int</em>) – Chunk size of each lowpass filter task.</p></li>
-<li><p><strong>order</strong> (<em>float</em><em>, </em><em>default is 2</em>) – Steepness of cutoff.</p></li>
-<li><p><strong>overlap</strong> (<em>int</em><em>, </em><em>default is 16</em>) – Overlapping pixels at the edges of tiles.</p></li>
-<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
-For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
-<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
-</ul>
-</dd>
-<dt class="field-even">Returns</dt>
-<dd class="field-even"><p>Filtered image.</p>
-</dd>
-<dt class="field-odd">Return type</dt>
-<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
-</dd>
-</dl>
-</dd></dl>
+<span class="sig-name descname"><span class="pre">tiled_lowpass_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">overlap</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">16</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.tiled_lowpass_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.tiled_lowpass_filter" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.tiled_lucy">
+<span class="sig-name descname"><span class="pre">tiled_lucy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">niter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1e-05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">overlap</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.tiled_lucy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.tiled_lucy" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.tophat">
-<span class="sig-name descname"><span class="pre">tophat</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.tophat"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.tophat" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">tophat</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.tophat"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.tophat" title="Permalink to this definition">¶</a></dt>
 <dd><p>Tophat morphological image processing. This is useful for background subtraction.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -3767,10 +3794,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3782,17 +3809,17 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dd><p>Calculate yx-directional drift using the method equivalent to
 <code class="docutils literal notranslate"><span class="pre">skimage.registration.phase_cross_correlation</span></code>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>along</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Along which axis drift will be calculated.</p></li>
 <li><p><strong>show_drift</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, plot the result.</p></li>
 <li><p><strong>upsample_factor</strong> (<em>int</em><em>, </em><em>default is 10</em>) – Up-sampling factor when calculating phase cross correlation.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>DataFrame structure with x,y columns</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
 </dd>
 </dl>
@@ -3805,7 +3832,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 new template and is used for the next template. To avoid slight shifts accumulating to the
 template image, new template image will be fitteg to the old one by phase cross correlation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>template</strong> (<em>np.ndarray</em>) – Template image. Must be 2 or 3 dimensional.</p></li>
 <li><p><strong>bg</strong> (<em>float</em><em>, </em><em>optional</em>) – Background intensity. If not given, it will calculated as the minimum value of
@@ -3813,10 +3840,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>along</strong> (<em>str</em><em>, </em><em>default is &quot;t&quot;</em>) – Which axis will be the time axis.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Centers of matched templates.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
 </dd>
 </dl>
@@ -3824,7 +3851,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.unmix">
-<span class="sig-name descname"><span class="pre">unmix</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">matrix</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'c'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.unmix"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.unmix" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">unmix</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">matrix</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'c'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.unmix"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.unmix" title="Permalink to this definition">¶</a></dt>
 <dd><p>Unmix fluorescence leakage between channels in a linear way. For example, a blue/green image,
 fluorescent leakage can be written as following equation:</p>
 <blockquote>
@@ -3841,7 +3868,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <div><p><span class="math notranslate nohighlight">\(V_{real} = M^{-1} \cdot V_{obs}\)</span></p>
 </div></blockquote>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>matrix</strong> (<em>array-like</em>) – Leakage matrix. The (i, j) component of the matrix is the leakage from i-th channel to
 j-th channel.</p></li>
@@ -3851,10 +3878,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Unmixed image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3877,19 +3904,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <p>Image region labeled with $i$ means that all the points in the region are
 closer to the $i$-th point than any other points.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>coords</strong> (<a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><em>MarkerFrame</em></a><em> or </em><em>(</em><em>N</em><em>, </em><em>2</em><em>) </em><em>array-like</em>) – Coordinates of points.</p></li>
-<li><p><strong>inf</strong> (<em>int</em><em>, </em><em>array of int</em><em>, </em><em>optional</em>) – Distance to infinity points. If not provided, infinity points are
+<li><p><strong>inf</strong> (<em>int</em><em>, </em><em>array</em><em> of </em><em>int</em><em>, </em><em>optional</em>) – Distance to infinity points. If not provided, infinity points are
 placed at 100 times further positions relative to the image shape.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Segmentation labels of image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label">Label</a></p>
 </dd>
 </dl>
@@ -3900,7 +3927,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">watershed</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coords</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><span class="pre">MarkerFrame</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'self'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'distance'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'distance'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_distance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.watershed"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.watershed" title="Permalink to this definition">¶</a></dt>
 <dd><p>Label segmentation using watershed algorithm.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>coords</strong> (<a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><em>MarkerFrame</em></a><em>, </em><em>optional</em>) – Returned by such as <cite>peak_local_max()</cite>. Array of coordinates of peaks.</p></li>
 <li><p><strong>{connectivity}</strong> – </p></li>
@@ -3913,10 +3940,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>{dims}</strong> – </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Updated labels.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label">Label</a></p>
 </dd>
 </dl>
@@ -3924,11 +3951,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.wavelet_denoising">
-<span class="sig-name descname"><span class="pre">wavelet_denoising</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">noise_sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wavelet</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'db1'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'soft'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'hard'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'soft'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wavelet_levels</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'BayesShrink'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'VisuShrink'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'BayesShrink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift_steps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.wavelet_denoising"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.wavelet_denoising" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">wavelet_denoising</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">noise_sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wavelet</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'db1'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'soft'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'hard'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'soft'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wavelet_levels</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'BayesShrink'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'VisuShrink'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'BayesShrink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift_steps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.wavelet_denoising"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.wavelet_denoising" title="Permalink to this definition">¶</a></dt>
 <dd><p>Wavelet denoising. Because it is not shift invariant, <code class="docutils literal notranslate"><span class="pre">cycle_spin</span></code> is called inside the
 function.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>noise_sigma</strong> (<em>float</em><em>, </em><em>optional</em>) – Standard deviation of noise, if known.</p></li>
 <li><p><strong>wavelet</strong> (<em>str</em><em>, </em><em>default is &quot;db1&quot;</em>) – Any options of <cite>pywt.wavelist</cite>.</p></li>
@@ -3941,10 +3968,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Denoised image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3952,7 +3979,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.ImgArray.wiener">
-<span class="sig-name descname"><span class="pre">wiener</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">numpy.ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.wiener"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.wiener" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">wiener</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.wiener"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.ImgArray.wiener" title="Permalink to this definition">¶</a></dt>
 <dd><p>Classical wiener deconvolution. This algorithm has the serious ringing problem
 if parameters are set to wrong values.</p>
 <p><span class="math notranslate nohighlight">\(F[Y_{res}] = \frac{F[Y_{obs}] \cdot \bar{H}}{|H|^2 + \lambda}\)</span></p>
@@ -3960,19 +3987,20 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="math notranslate nohighlight">\(Y_{res}\)</span>: restored image;
 <span class="math notranslate nohighlight">\(H\)</span> : FFT of point spread function (PSF);</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>psf</strong> (<em>np.ndarray</em>) – Point spread function.</p></li>
+<li><p><strong>psf</strong> (<em>ndarray</em><em> or </em><em>callable</em>) – Point spread function. If a function is given, <cite>psf(shape)</cite> will be
+called to generate the PSF.</p></li>
 <li><p><strong>lmd</strong> (<em>float</em><em>, </em><em>default is 0.1</em>) – Constant value used in the deconvolution. See Formulation below.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Deconvolved image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -3991,11 +4019,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.arrays.imgarray.wave_num">
-<span class="sig-prename descclassname"><span class="pre">impy.arrays.imgarray.</span></span><span class="sig-name descname"><span class="pre">wave_num</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sl</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">slice</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">s</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">uf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">numpy.ndarray</span></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#wave_num"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.wave_num" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.arrays.imgarray.</span></span><span class="sig-name descname"><span class="pre">wave_num</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sl</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">slice</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">s</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">uf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#wave_num"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.imgarray.wave_num" title="Permalink to this definition">¶</a></dt>
 <dd><p>A function that makes wave number vertical vector. Returned vector will
 be [k/s, (k + 1/uf)/s, (k + 2/uf)/s, …] (where k = sl.start)</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>sl</strong> (<em>slice</em>) – Slice that specify which part of the image will be transformed.</p></li>
 <li><p><strong>s</strong> (<em>int</em>) – Size along certain dimension.</p></li>
@@ -4007,11 +4035,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.arrays.label">
-<span id="impy-arrays-label-module"></span><h2>impy.arrays.label module<a class="headerlink" href="#module-impy.arrays.label" title="Permalink to this headline">¶</a></h2>
+<span id="impy-arrays-label-module"></span><h2>impy.arrays.label module<a class="headerlink" href="#module-impy.arrays.label" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.arrays.label.Label">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.label.</span></span><span class="sig-name descname"><span class="pre">Label</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">obj</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">source</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metadata</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.label.Label" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.arrays.bases.metaarray.MetaArray</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">MetaArray</span></code></a></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.label.Label.add_label">
 <span class="sig-name descname"><span class="pre">add_label</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">label_image</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.add_label"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.label.Label.add_label" title="Permalink to this definition">¶</a></dt>
@@ -4029,19 +4057,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.label.Label.expand_labels">
-<span class="sig-name descname"><span class="pre">expand_labels</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">distance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">impy.arrays.label.Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.expand_labels"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.label.Label.expand_labels" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">expand_labels</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">distance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.expand_labels"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.label.Label.expand_labels" title="Permalink to this definition">¶</a></dt>
 <dd><p>Expand areas of labels.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>distance</strong> (<em>int</em><em>, </em><em>optional</em>) – The distance to expand, by default 1</p></li>
 <li><p><strong>{dims}</strong> – </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Same array but labels are updated.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label">Label</a></p>
 </dd>
 </dl>
@@ -4054,20 +4082,20 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.label.Label.increment">
-<span class="sig-name descname"><span class="pre">increment</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">impy.arrays.label.Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.increment"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.label.Label.increment" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">increment</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.increment"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.label.Label.increment" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.label.Label.increment_iter">
-<span class="sig-name descname"><span class="pre">increment_iter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">impy.arrays.label.Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.increment_iter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.label.Label.increment_iter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">increment_iter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.increment_iter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.label.Label.increment_iter" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.label.Label.opening">
-<span class="sig-name descname"><span class="pre">opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">impy.arrays.label.Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.opening"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.label.Label.opening" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.opening"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.label.Label.opening" title="Permalink to this definition">¶</a></dt>
 <dd><p>Morphological opening.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -4092,10 +4120,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Opened labels</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label">Label</a></p>
 </dd>
 </dl>
@@ -4103,26 +4131,26 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.label.Label.optimize">
-<span class="sig-name descname"><span class="pre">optimize</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">impy.arrays.label.Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.optimize"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.label.Label.optimize" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">optimize</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.optimize"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.label.Label.optimize" title="Permalink to this definition">¶</a></dt>
 <dd><p>Optimize labeling.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.label.Label.proj">
-<span class="sig-name descname"><span class="pre">proj</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forbid_overlap</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">impy.arrays.label.Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.proj"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.label.Label.proj" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">proj</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forbid_overlap</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.proj"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.label.Label.proj" title="Permalink to this definition">¶</a></dt>
 <dd><p>Label projection. This function is useful when zyx-labels are drawn but you want to reduce the
 dimension.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>axis</strong> (<em>str</em><em>, </em><em>optional</em>) – Along which axis projection will be calculated. If None, most plausible one will be chosen.</p></li>
 <li><p><strong>forbid_overlap</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True and there were any label overlap, this function will raise ValueError.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Projected labels.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label">Label</a></p>
 </dd>
 </dl>
@@ -4130,7 +4158,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.label.Label.relabel">
-<span class="sig-name descname"><span class="pre">relabel</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">impy.arrays.label.Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.relabel"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.label.Label.relabel" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">relabel</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.relabel"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.label.Label.relabel" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
@@ -4142,11 +4170,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.arrays.labeledarray">
-<span id="impy-arrays-labeledarray-module"></span><h2>impy.arrays.labeledarray module<a class="headerlink" href="#module-impy.arrays.labeledarray" title="Permalink to this headline">¶</a></h2>
+<span id="impy-arrays-labeledarray-module"></span><h2>impy.arrays.labeledarray module<a class="headerlink" href="#module-impy.arrays.labeledarray" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.arrays.labeledarray.ArrayCovariates">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.labeledarray.</span></span><span class="sig-name descname"><span class="pre">ArrayCovariates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.labeledarray.SupportAxesSlicing" title="impy.arrays.labeledarray.SupportAxesSlicing"><span class="pre">impy.arrays.labeledarray.SupportAxesSlicing</span></a><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">parent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">impy.arrays.bases.metaarray.MetaArray</span></a></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#ArrayCovariates"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.ArrayCovariates" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">MutableMapping</span></code>[<code class="xref py py-class docutils literal notranslate"><span class="pre">str</span></code>, <a class="reference internal" href="#impy.arrays.labeledarray.SupportAxesSlicing" title="impy.arrays.labeledarray.SupportAxesSlicing"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.arrays.labeledarray.SupportAxesSlicing</span></code></a>]</p>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.labeledarray.</span></span><span class="sig-name descname"><span class="pre">ArrayCovariates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.labeledarray.SupportAxesSlicing" title="impy.arrays.labeledarray.SupportAxesSlicing"><span class="pre">impy.arrays.labeledarray.SupportAxesSlicing</span></a><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">parent</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#ArrayCovariates"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.ArrayCovariates" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">MutableMapping</span></code>[<code class="xref py py-class docutils literal notranslate"><span class="pre">str</span></code>, <a class="reference internal" href="#impy.arrays.labeledarray.SupportAxesSlicing" title="impy.arrays.labeledarray.SupportAxesSlicing"><code class="xref py py-class docutils literal notranslate"><span class="pre">SupportAxesSlicing</span></code></a>]</p>
 <p>A dictionary of covariate objects for a MetaArray.</p>
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.labeledarray.ArrayCovariates.construct_by_copying">
@@ -4169,22 +4197,22 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.arrays.labeledarray.LabeledArray">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.labeledarray.</span></span><span class="sig-name descname"><span class="pre">LabeledArray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">obj</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">source</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Path</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metadata</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.arrays.bases.metaarray.MetaArray</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">MetaArray</span></code></a></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.labeledarray.LabeledArray.append_label">
-<span class="sig-name descname"><span class="pre">append_label</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">label_image</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">numpy.ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">new</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">impy.arrays.label.Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.append_label"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.append_label" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">append_label</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">label_image</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">new</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.append_label"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.append_label" title="Permalink to this definition">¶</a></dt>
 <dd><p>Append new labels from an array. This function works for boolean or signed int arrays.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>label_image</strong> (<em>np.ndarray</em>) – Labeled image.</p></li>
 <li><p><strong>new</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, existing labels will be removed anyway.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>New labels.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label">Label</a></p>
 </dd>
 </dl>
@@ -4223,13 +4251,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.arrays.labeledarray.LabeledArray.axes">
-<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">axes</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">impy.axes._axes.Axes</span></em><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.axes" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">axes</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">Axes</span></em><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.axes" title="Permalink to this definition">¶</a></dt>
 <dd><p>Axes of the array.</p>
 </dd></dl>
 
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.arrays.labeledarray.LabeledArray.covariates">
-<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">covariates</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.labeledarray.ArrayCovariates" title="impy.arrays.labeledarray.ArrayCovariates"><span class="pre">impy.arrays.labeledarray.ArrayCovariates</span></a></em><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.covariates" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">covariates</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.labeledarray.ArrayCovariates" title="impy.arrays.labeledarray.ArrayCovariates"><span class="pre">ArrayCovariates</span></a></em><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.covariates" title="Permalink to this definition">¶</a></dt>
 <dd><p>Get all the covariates.</p>
 </dd></dl>
 
@@ -4238,7 +4266,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">crop_center</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">nDFloat</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.crop_center"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.crop_center" title="Permalink to this definition">¶</a></dt>
 <dd><p>Crop out the center of an image.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>scale</strong> (<em>float</em><em> or </em><em>array-like</em><em>, </em><em>default is 0.5</em>) – Scale of the cropped image. If an array is given, each axis will be cropped in different scales,
 using each value respectively.</p></li>
@@ -4246,10 +4274,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>CroppedImage</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Self</p>
 </dd>
 </dl>
@@ -4274,13 +4302,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dd><p>Make a kernel from an image by cropping out the center region.
 This function is useful especially in <cite>ImgArray.defocus()</cite>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><p><strong>radius</strong> (<em>int</em><em> or </em><em>array-like of int</em><em>, </em><em>default is 2</em>) – Radius of the kernel.</p>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>radius</strong> (<em>int</em><em> or </em><em>array-like</em><em> of </em><em>int</em><em>, </em><em>default is 2</em>) – Radius of the kernel.</p>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Kernel</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.labeledarray.LabeledArray" title="impy.arrays.labeledarray.LabeledArray">LabeledArray</a></p>
 </dd>
 </dl>
@@ -4300,18 +4328,18 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">extract</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">label_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filt</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.html#impy.collections.DataList" title="impy.collections.DataList"><span class="pre">DataList</span></a><span class="p"><span class="pre">[</span></span><span class="pre">Self</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.extract"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.extract" title="Permalink to this definition">¶</a></dt>
 <dd><p>Extract certain regions of the image and substitute others to <cite>cval</cite>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>label_ids</strong> (<em>int</em><em> or </em><em>iterable of int</em><em>, </em><em>by default all the label IDs.</em>) – Which label regions are extracted.</p></li>
+<li><p><strong>label_ids</strong> (<em>int</em><em> or </em><em>iterable</em><em> of </em><em>int</em><em>, </em><em>by default all the label IDs.</em>) – Which label regions are extracted.</p></li>
 <li><p><strong>filt</strong> (<em>callable</em><em>, </em><em>optional</em>) – If given, only regions <cite>X</cite> that satisfy filt(self, X) will extracted.</p></li>
 <li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.</em>) – Constant value to fill regions outside the extracted labeled regions.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Extracted image(s)</p>
 </dd>
-<dt class="field-odd">Return type</dt>
-<dd class="field-odd"><p>DataList of LabeledArray</p>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.html#impy.collections.DataList" title="impy.collections.DataList">DataList</a> of <a class="reference internal" href="#impy.arrays.labeledarray.LabeledArray" title="impy.arrays.labeledarray.LabeledArray">LabeledArray</a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -4322,16 +4350,16 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dd><p>Apply same function with different parameters for each channel. This function will be useful
 when the parameters are dependent on channels, like wave length.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>func</strong> (<em>str</em>) – Function name to apply over channel axis.</p></li>
 <li><p><strong>along</strong> (<em>str</em><em>, </em><em>default is &quot;c&quot;</em>) – Along which axis function will be applied to.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>output image stack</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.labeledarray.LabeledArray" title="impy.arrays.labeledarray.LabeledArray">LabeledArray</a></p>
 </dd>
 </dl>
@@ -4343,7 +4371,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dd><p>Apply same function with different parameters with same input. This function will be useful
 when you want to try different conditions to the same image.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>func</strong> (<em>callable</em><em> or </em><em>str</em>) – Function to apply repetitively. If str, then member method will be called.</p></li>
 <li><p><strong>var</strong> (<em>dict</em><em>[</em><em>str</em><em>, </em><em>Iterable</em><em>]</em><em>, </em><em>optional</em>) – Name of variable and the values to try. If you want to try sigma=1,2,3 then you should
@@ -4352,10 +4380,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 is provided in <cite>kwargs</cite>, then kwargs will be <cite>var</cite>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>List of outputs.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.html#impy.collections.DataList" title="impy.collections.DataList">DataList</a></p>
 </dd>
 </dl>
@@ -4387,7 +4415,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 then it will converted automatically if possible. For mrc file format, only zyx and yx is
 allowed. zyx-scale is also saved.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>save_path</strong> (<em>str</em>) – File name.</p></li>
 <li><p><strong>dtype</strong> (<em>dtype-like</em><em>, </em><em>optional</em>) – In what data type img will be saved.</p></li>
@@ -4404,7 +4432,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.labeledarray.LabeledArray.label">
-<span class="sig-name descname"><span class="pre">label</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ref_image</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">np.ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">bool</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.label"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.label" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">label</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ref_image</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">bool</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.label"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.label" title="Permalink to this definition">¶</a></dt>
 <dd><p>Label image using skimage’s label().</p>
 <p>Label image using <cite>ref_image</cite> as reference image, or image itself. If
 <code class="docutils literal notranslate"><span class="pre">filt</span></code> is given, image will be labeled only if certain condition
@@ -4417,7 +4445,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </div>
 </div></blockquote>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>ref_image</strong> (<em>array</em><em>, </em><em>optional</em>) – Image to make label, by default self is used.</p></li>
 <li><p><strong>filt</strong> (<em>callable</em><em>, </em><em>positional argument but not optional</em>) – Filter function. The first argument is intensity image sliced from
@@ -4431,10 +4459,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>connectivity</strong> (<em>int</em><em>, </em><em>optional</em>) – Connectivity of pixels. See <code class="docutils literal notranslate"><span class="pre">skimage.measure.label</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Newly created label.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label">Label</a></p>
 </dd>
 </dl>
@@ -4482,7 +4510,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.labeledarray.LabeledArray.label_if">
-<span class="sig-name descname"><span class="pre">label_if</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ref_image</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">np.ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">bool</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.label_if"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.label_if" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">label_if</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ref_image</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">bool</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.label_if"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.label_if" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py property">
@@ -4493,10 +4521,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.labeledarray.LabeledArray.map_coordinates">
-<span class="sig-name descname"><span class="pre">map_coordinates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coordinates</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">PaddingMode</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefilter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.map_coordinates"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.map_coordinates" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">map_coordinates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coordinates</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">PaddingMode</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefilter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">has_nan</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.map_coordinates"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.map_coordinates" title="Permalink to this definition">¶</a></dt>
 <dd><p>Coordinate mapping in the image. See <code class="docutils literal notranslate"><span class="pre">scipy.ndimage.map_coordinates</span></code>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>coordinates</strong> (<em>ArrayLike</em>) – Interpolation coordinates. Must be (D, N) or (D, X_1, …, X_D) shape.</p></li>
 <li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
@@ -4506,14 +4534,15 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </p></li>
 <li><p><strong>prefilter</strong> (<em>bool</em><em>, </em><em>optional</em>) – Spline prefilter applied to the array. By default set to True if <code class="docutils literal notranslate"><span class="pre">order</span></code> is larger
 than 1.</p></li>
+<li><p><strong>has_nan</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If true, nan values will be masked out.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Transformed image. Axes will be correctly filled if possible.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.labeledarray.LabeledArray" title="impy.arrays.labeledarray.LabeledArray">LabeledArray</a></p>
 </dd>
 </dl>
@@ -4524,7 +4553,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">pathprops</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">paths</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.frame.html#impy.frame.frames.PathFrame" title="impy.frame.frames.PathFrame"><span class="pre">PathFrame</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">ArrayLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">ArrayLike</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">properties</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.html#impy.collections.DataDict" title="impy.collections.DataDict"><span class="pre">DataDict</span></a><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.pathprops"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.pathprops" title="Permalink to this definition">¶</a></dt>
 <dd><p>Measure line property using func(line_scan) for each functions in properties.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>paths</strong> (<a class="reference internal" href="impy.frame.html#impy.frame.frames.PathFrame" title="impy.frame.frames.PathFrame"><em>PathFrame</em></a>) – Paths to measure properties.</p></li>
 <li><p><strong>properties</strong> (<em>str</em><em> or </em><em>callable</em><em>, or </em><em>their iterable</em>) – Properties to be analyzed.</p></li>
@@ -4533,11 +4562,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Line properties. Keys are property names and values are the corresponding PropArrays.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
-<dd class="field-odd"><p>DataDict of PropArray</p>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.html#impy.collections.DataDict" title="impy.collections.DataDict">DataDict</a> of <a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray">PropArray</a></p>
 </dd>
 </dl>
 <p class="rubric">Examples</p>
@@ -4559,7 +4588,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <p>This method is essentially identical to <a class="reference internal" href="#impy.arrays.labeledarray.LabeledArray.map_coordinates" title="impy.arrays.labeledarray.LabeledArray.map_coordinates"><code class="xref py py-func docutils literal notranslate"><span class="pre">map_coordinates()</span></code></a> but is
 more straightforward for measuring intensities at points.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>coords</strong> (<em>DataFrame</em><em> or </em><em>array-like</em>) – Coordinates of point to be measured.</p></li>
 <li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
@@ -4568,10 +4597,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>squeeze</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True and only one point is measured, the redundant dimension ID_AXIS will be deleted.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Intensities at points.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray">PropArray</a> or float</p>
 </dd>
 </dl>
@@ -4587,20 +4616,20 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.labeledarray.LabeledArray.proj_labels">
-<span class="sig-name descname"><span class="pre">proj_labels</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forbid_overlap</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">impy.arrays.label.Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.proj_labels"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.proj_labels" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">proj_labels</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forbid_overlap</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.proj_labels"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.proj_labels" title="Permalink to this definition">¶</a></dt>
 <dd><p>Label projection. This function is useful when zyx-labels are drawn but you want to reduce the
 dimension.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>axis</strong> (<em>str</em><em>, </em><em>optional</em>) – Along which axis projection will be calculated. If None, most plausible one will be chosen.</p></li>
 <li><p><strong>forbid_overlap</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True and there were any label overlap, this function will raise ValueError.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Projected labels.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label">Label</a></p>
 </dd>
 </dl>
@@ -4617,7 +4646,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">remove_edges</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pixel</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">nDInt</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.remove_edges"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.remove_edges" title="Permalink to this definition">¶</a></dt>
 <dd><p>Remove pixels from the edges.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>pixel</strong> (<em>int</em><em> or </em><em>array-like</em><em>, </em><em>default is 1</em>) – Number of pixels to remove. If an array is given, each axis will be cropped with different pixels,
 using each value respectively.</p></li>
@@ -4625,10 +4654,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Cropped image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.labeledarray.LabeledArray" title="impy.arrays.labeledarray.LabeledArray">LabeledArray</a></p>
 </dd>
 </dl>
@@ -4642,7 +4671,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 3D-images. The argument <cite>linewidth</cite> is not implemented here because it is
 useless.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>a</strong> (<em>array-like</em>) – Path or source coordinate. If the former, it must be like:
 <cite>a = [[y0, x0], [y1, x1], …, [yn, xn]]</cite></p></li>
@@ -4652,10 +4681,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Line scans.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray">PropArray</a></p>
 </dd>
 </dl>
@@ -4692,7 +4721,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 origin be the origin of a xy-plane, the rotation direction from dst1 to dst2 must be counter-
 clockwise, or the cropped image will be reversed.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>origin</strong> (<em>(</em><em>float</em><em>, </em><em>float</em><em>)</em>) – </p></li>
 <li><p><strong>dst1</strong> (<em>(</em><em>float</em><em>, </em><em>float</em><em>)</em>) – </p></li>
@@ -4701,10 +4730,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Cropped array.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.labeledarray.LabeledArray" title="impy.arrays.labeledarray.LabeledArray">LabeledArray</a></p>
 </dd>
 </dl>
@@ -4712,10 +4741,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.labeledarray.LabeledArray.set_scale">
-<span class="sig-name descname"><span class="pre">set_scale</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">other</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.set_scale"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.set_scale" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">set_scale</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">other</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.set_scale"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.set_scale" title="Permalink to this definition">¶</a></dt>
 <dd><p>Set scales of each axis.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>other</strong> (<em>dict</em><em> or </em><em>object with axes</em>) – New scales. If dict, it should be like {“x”: 0.1, “y”: 0.1}. If MetaArray, only
 scales of common axes are copied.</p></li>
@@ -4731,7 +4760,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">specify</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Coords</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Coords</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">labeltype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'square'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.specify"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.specify" title="Permalink to this definition">¶</a></dt>
 <dd><p>Make rectangle or ellipse labels from points.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>center</strong> (<em>array like</em><em> or </em><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><em>MarkerFrame</em></a>) – Coordinates of centers. For MarkerFrame, it must have the same axes order.</p></li>
 <li><p><strong>radius</strong> (<em>float</em><em> or </em><em>array-like</em>) – Radius of labels.</p></li>
@@ -4740,10 +4769,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>labeltype</strong> (<em>str</em><em>, </em><em>default is &quot;square&quot;</em>) – The shape of labels.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Labeled regions.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label">Label</a></p>
 </dd>
 </dl>
@@ -4761,10 +4790,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.labeledarray.LabeledArray.spline_filter">
-<span class="sig-name descname"><span class="pre">spline_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mirror'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.spline_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.spline_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">spline_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mirror'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.spline_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.spline_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Run spline filter.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
 For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
@@ -4775,10 +4804,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.labeledarray.LabeledArray" title="impy.arrays.labeledarray.LabeledArray">LabeledArray</a></p>
 </dd>
 </dl>
@@ -4790,13 +4819,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dd><p>Split n-dimensional image into (n-1)-dimensional images. This function is different from
 <cite>np.split</cite>, which split an array into smaller pieces (n-D to n-D).</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>axis</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Along which axis the original image will be split, by default “c”</p>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Separate images</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>list of arrays</p>
 </dd>
 </dl>
@@ -4807,7 +4836,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">tile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.tile"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.LabeledArray.tile" title="Permalink to this definition">¶</a></dt>
 <dd><p>Tile images in a certain order.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>shape</strong> (<em>tuple</em><em>[</em><em>int</em><em>, </em><em>int</em><em>]</em><em>, </em><em>optional</em>) – Grid shape. This parameter must be specified unless the length of <cite>along</cite> is 2.</p></li>
 <li><p><strong>along</strong> (<em>str</em><em>, </em><em>optional</em>) – Axis (Axes) over which will be iterated.</p></li>
@@ -4827,10 +4856,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Tiled array</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Labeled</p>
 </dd>
 </dl>
@@ -4840,11 +4869,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.arrays.labeledarray.SegmentedLine">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.labeledarray.</span></span><span class="sig-name descname"><span class="pre">SegmentedLine</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">nodes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">numpy.ndarray</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#SegmentedLine"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.SegmentedLine" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.labeledarray.</span></span><span class="sig-name descname"><span class="pre">SegmentedLine</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">nodes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#SegmentedLine"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.SegmentedLine" title="Permalink to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.labeledarray.SegmentedLine.sample_points">
-<span class="sig-name descname"><span class="pre">sample_points</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">numpy.ndarray</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#SegmentedLine.sample_points"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.SegmentedLine.sample_points" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">sample_points</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#SegmentedLine.sample_points"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.labeledarray.SegmentedLine.sample_points" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
@@ -4856,7 +4885,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <p>A protocol that covariate objects must follow.</p>
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.arrays.labeledarray.SupportAxesSlicing.axes">
-<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">axes</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">impy.axes._axes.Axes</span></em><a class="headerlink" href="#impy.arrays.labeledarray.SupportAxesSlicing.axes" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">axes</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">Axes</span></em><a class="headerlink" href="#impy.arrays.labeledarray.SupportAxesSlicing.axes" title="Permalink to this definition">¶</a></dt>
 <dd><p>Axes object bound to the object.</p>
 </dd></dl>
 
@@ -4870,11 +4899,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.arrays.lazy">
-<span id="impy-arrays-lazy-module"></span><h2>impy.arrays.lazy module<a class="headerlink" href="#module-impy.arrays.lazy" title="Permalink to this headline">¶</a></h2>
+<span id="impy-arrays-lazy-module"></span><h2>impy.arrays.lazy module<a class="headerlink" href="#module-impy.arrays.lazy" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.lazy.</span></span><span class="sig-name descname"><span class="pre">LazyImgArray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">obj</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DaskArray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">source</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metadata</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="#impy.arrays.axesmixin.AxesMixin" title="impy.arrays.axesmixin.AxesMixin"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.arrays.axesmixin.AxesMixin</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="#impy.arrays.axesmixin.AxesMixin" title="impy.arrays.axesmixin.AxesMixin"><code class="xref py py-class docutils literal notranslate"><span class="pre">AxesMixin</span></code></a></p>
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.GB">
 <em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">GB</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">float</span></em><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.GB" title="Permalink to this definition">¶</a></dt>
@@ -4888,7 +4917,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.affine">
-<span class="sig-name descname"><span class="pre">affine</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">matrix</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rotation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shear</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">translation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.affine"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.affine" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">affine</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">matrix</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rotation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shear</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">translation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.affine"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.affine" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.affine. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Convert image by Affine transformation. 2D Affine transformation is written as:</p>
 <div class="math notranslate nohighlight">
@@ -4899,7 +4928,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
                 \begin{bmatrix} y \\x\\ 1 \end{bmatrix}\end{split}\]</div>
 <p>and similarly, n-D Affine transformation can be described as (n+1)-D matrix.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>matrix</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
 <li><p><strong>scale</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
@@ -4911,16 +4940,16 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </p></li>
 <li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
 <li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
-<li><p><strong>output_shape</strong> (<em>tuple of int</em><em>, </em><em>optional</em>) – Shape of output array.</p></li>
+<li><p><strong>output_shape</strong> (<em>tuple</em><em> of </em><em>int</em><em>, </em><em>optional</em>) – Shape of output array.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Transformed image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -4928,20 +4957,20 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.apply_dask_func">
-<span class="sig-name descname"><span class="pre">apply_dask_func</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">funcname</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.apply_dask_func"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.apply_dask_func" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">apply_dask_func</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">funcname</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.apply_dask_func"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.apply_dask_func" title="Permalink to this definition">¶</a></dt>
 <dd><p>Apply dask array function to the connected dask array.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>funcname</strong> (<em>str</em>) – Name of function to apply.</p></li>
 <li><p><strong>args</strong> – Parameters that will be passed to <cite>funcname</cite>.</p></li>
 <li><p><strong>kwargs</strong> – Parameters that will be passed to <cite>funcname</cite>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Updated one</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -4949,33 +4978,33 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.as_float">
-<span class="sig-name descname"><span class="pre">as_float</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.as_float"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.as_float" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">as_float</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.as_float"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.as_float" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.as_img_type">
-<span class="sig-name descname"><span class="pre">as_img_type</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dtype=&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.as_img_type"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.as_img_type" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">as_img_type</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dtype=&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.as_img_type"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.as_img_type" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.as_uint16">
-<span class="sig-name descname"><span class="pre">as_uint16</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.as_uint16"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.as_uint16" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">as_uint16</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.as_uint16"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.as_uint16" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.as_uint8">
-<span class="sig-name descname"><span class="pre">as_uint8</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.as_uint8"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.as_uint8" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">as_uint8</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.as_uint8"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.as_uint8" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.binning">
-<span class="sig-name descname"><span class="pre">binning</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">binsize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_edges</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.binning"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.binning" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">binning</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">binsize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_edges</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.binning"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.binning" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.binning. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Binning of images. This function is similar to <code class="docutils literal notranslate"><span class="pre">rescale</span></code> but is strictly
 binned by <span class="math notranslate nohighlight">\(N \times N\)</span> blocks. Also, any numpy functions that accept
 “axis” argument are supported for reduce functions.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>binsize</strong> (<em>int</em><em>, </em><em>default is 2</em>) – Bin size, such as 2x2.</p></li>
 <li><p><strong>method</strong> (<em>str</em><em> or </em><em>callable</em><em>, </em><em>default is numpy.mean</em>) – Reduce function applied to each bin.</p></li>
@@ -4985,10 +5014,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Binned image</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5001,7 +5030,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.chunksize">
-<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">chunksize</span></span><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.chunksize" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">chunksize</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">AxesTuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.chunksize" title="Permalink to this definition">¶</a></dt>
 <dd><p>Chunk size of the array.</p>
 </dd></dl>
 
@@ -5019,13 +5048,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.closing">
-<span class="sig-name descname"><span class="pre">closing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.closing"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.closing" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">closing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.closing"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.closing" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.closing. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Morphological closing.</p>
 <p>If input is binary image, the running function will automatically switched to
 <code class="docutils literal notranslate"><span class="pre">binary_closing</span></code> to speed up calculation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -5052,10 +5081,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5063,18 +5092,18 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.compute">
-<span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ignore_limit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.compute" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ignore_limit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.compute" title="Permalink to this definition">¶</a></dt>
 <dd><p>Compute all the task and convert the result into ImgArray. If image size overwhelms MAX_GB
 then MemoryError is raised.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.convolve">
-<span class="sig-name descname"><span class="pre">convolve</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kernel</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.convolve"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.convolve" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">convolve</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kernel</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.convolve"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.convolve" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.convolve. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>General linear convolution by running kernel filtering.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>kernel</strong> (<em>array-like</em>) – Convolution kernel.</p></li>
 <li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
@@ -5084,10 +5113,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Convolved image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5095,11 +5124,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.crop_center">
-<span class="sig-name descname"><span class="pre">crop_center</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.crop_center"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.crop_center" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">crop_center</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.crop_center"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.crop_center" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of LabeledArray.crop_center. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Crop out the center of an image.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>scale</strong> (<em>float</em><em> or </em><em>array-like</em><em>, </em><em>default is 0.5</em>) – Scale of the cropped image. If an array is given, each axis will be cropped in different scales,
 using each value respectively.</p></li>
@@ -5107,10 +5136,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>CroppedImage</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Self</p>
 </dd>
 </dl>
@@ -5131,12 +5160,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.dilation">
-<span class="sig-name descname"><span class="pre">dilation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.dilation"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.dilation" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">dilation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.dilation"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.dilation" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.dilation. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Morphological dilation. If input is binary image, the running function will automatically switched to
 <code class="docutils literal notranslate"><span class="pre">binary_dilation</span></code> to speed up calculation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -5163,10 +5192,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5179,7 +5208,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <p>Drift correction using iterative Affine translation. If translation vectors <code class="docutils literal notranslate"><span class="pre">shift</span></code>
 is not given, then it will be determined using <code class="docutils literal notranslate"><span class="pre">track_drift</span></code> method of ImgArray.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>shift</strong> (<em>DataFrame</em><em> or </em><em>(</em><em>N</em><em>, </em><em>D</em><em>) </em><em>array</em><em>, </em><em>optional</em>) – Translation vectors. If DataFrame, it must have columns named with all the symbols
 contained in <code class="docutils literal notranslate"><span class="pre">dims</span></code>.</p></li>
@@ -5192,10 +5221,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>affine_kwargs</strong> – Keyword arguments that will be passed to <code class="docutils literal notranslate"><span class="pre">warp</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Corrected image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5216,11 +5245,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.edge_filter">
-<span class="sig-name descname"><span class="pre">edge_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'sobel'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.edge_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.edge_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">edge_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'sobel'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.edge_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.edge_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.edge_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Sobel filter. This filter is useful for edge detection.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>method</strong> (<em>str</em><em>, </em><em>{&quot;sobel&quot;</em><em>, </em><em>&quot;farid&quot;</em><em>, </em><em>&quot;scharr&quot;</em><em>, </em><em>&quot;prewitt&quot;}</em><em>, </em><em>default is &quot;sobel&quot;</em>) – Edge operator name.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
@@ -5228,10 +5257,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5239,13 +5268,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.erosion">
-<span class="sig-name descname"><span class="pre">erosion</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.erosion"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.erosion" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">erosion</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.erosion"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.erosion" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.erosion. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Morphological erosion.</p>
 <p>If input is binary image, the running function will automatically switched to
 <code class="docutils literal notranslate"><span class="pre">binary_erosion</span></code> to speed up calculation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -5272,10 +5301,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5283,14 +5312,14 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.fft">
-<span class="sig-name descname"><span class="pre">fft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'same'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.fft"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.fft" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'same'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.fft"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.fft" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.fft. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Fast Fourier transformation. This function returns complex array, which is
 inconpatible with some ImgArray functions.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable of int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
+<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable</em><em> of </em><em>int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
 - integers: padded or cropped to the specified shape.
 - “square”: padded to smallest 2^N-long square.
 - “same” (default): no padding or cropping.</p></li>
@@ -5300,10 +5329,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>FFT image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5315,23 +5344,25 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.gaussian_filter">
-<span class="sig-name descname"><span class="pre">gaussian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.gaussian_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.gaussian_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">gaussian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.gaussian_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.gaussian_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.gaussian_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Run Gaussian filter (Gaussian blur).</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array of float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
 If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
+<li><p><strong>fourier</strong> (<em>bool</em><em>, </em><em>default is False</em>) – Whether to run the convolution in Fourier space. This option is useful when the kernel or the image is large.
+Note that discrete Fourier transform assumes that the image is periodic, so that if intensities of the input image are not consecutive at img[0] and img[-1], you may get some artifacts at the boundary.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5345,11 +5376,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.ifft">
-<span class="sig-name descname"><span class="pre">ifft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">real</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.ifft"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.ifft" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">ifft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">real</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.ifft"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.ifft" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.ifft. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Fast Inverse Fourier transformation. Complementary function with <cite>fft()</cite>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>real</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, only the real part is returned.</p></li>
 <li><p><strong>shift</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, call <code class="docutils literal notranslate"><span class="pre">np.fft.ifftshift</span></code> at the first.</p></li>
@@ -5358,10 +5389,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>IFFT image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5376,7 +5407,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 then it will converted automatically if possible. For mrc file format, only zyx and yx is
 allowed. zyx-scale is also saved.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>save_path</strong> (<em>str</em>) – File name.</p></li>
 <li><p><strong>dtype</strong> (<em>dtype-like</em><em>, </em><em>optional</em>) – In what data type img will be saved.</p></li>
@@ -5388,15 +5419,15 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.iradon">
-<span class="sig-name descname"><span class="pre">iradon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degrees</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">central_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxisLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'y'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">degree_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxisLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">height_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxisLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">height</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'hamming'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.iradon"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.iradon" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">iradon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degrees</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">central_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'y'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">degree_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">height_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">height</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'hamming'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.iradon"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.iradon" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.iradon. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Inverse Radon transformation (weighted back projection) of a tile series.</p>
 <p>Input array must be a tilt series of 1D or 2D images. They are back-
 projected into a 2D or 3D image with arbitrary height.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>degrees</strong> (<em>sequence of float</em>) – Projection angles in degree. Length must match the length of the degree
+<li><p><strong>degrees</strong> (<em>sequence</em><em> of </em><em>float</em>) – Projection angles in degree. Length must match the length of the degree
 axis of the input image.</p></li>
 <li><p><strong>central_axis</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Axis parallel to the rotation axis.</p></li>
 <li><p><strong>degree_axis</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Axis of rotation degree. By default, the first axis will be used.</p></li>
@@ -5414,10 +5445,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Reconstruction.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5435,12 +5466,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.kalman_filter">
-<span class="sig-name descname"><span class="pre">kalman_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">gain</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">noise_var</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'t'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.kalman_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.kalman_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">kalman_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">gain</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">noise_var</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'t'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.kalman_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.kalman_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.kalman_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Kalman filter for image smoothing. This function is same as “Kalman Stack Filter” in ImageJ but support
 batch processing. This filter is useful for preprocessing of particle tracking.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>gain</strong> (<em>float</em><em>, </em><em>default is 0.8</em>) – Filter gain.</p></li>
 <li><p><strong>noise_var</strong> (<em>float</em><em>, </em><em>default is 0.05</em>) – Initial estimate of noise variance.</p></li>
@@ -5450,10 +5481,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5461,11 +5492,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.laplacian_filter">
-<span class="sig-name descname"><span class="pre">laplacian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.laplacian_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.laplacian_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">laplacian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.laplacian_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.laplacian_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.laplacian_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Edge detection using Laplacian filter. Kernel is made by <cite>skimage</cite>’s function.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>int</em><em>, </em><em>default is 1</em>) – Radius of kernel. Shape of kernel will be (2*radius+1, 2*radius+1).</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
@@ -5473,10 +5504,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5484,26 +5515,27 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.lucy">
-<span class="sig-name descname"><span class="pre">lucy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">numpy.ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">niter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1e-05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.lucy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.lucy" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">lucy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">niter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1e-05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.lucy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.lucy" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.lucy. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Deconvolution of N-dimensional image, using Richardson-Lucy’s algorithm.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>psf</strong> (<em>np.ndarray</em>) – Point spread function.</p></li>
+<li><p><strong>psf</strong> (<em>ndarray</em><em> or </em><em>callable</em>) – Point spread function. If a function is given, <cite>psf(shape)</cite> will be
+called to generate the PSF.</p></li>
 <li><p><strong>niter</strong> (<em>int</em><em>, </em><em>default is 50.</em>) – Number of iterations.</p></li>
-<li><p><strong>eps</strong> (<em>float</em><em>, </em><em>default is 1e-5</em>) – During deconvolution, division by small values in the convolve image of estimation and
-PSF may cause divergence. Therefore, division by values under <cite>eps</cite> is substituted
-to zero.</p></li>
+<li><p><strong>eps</strong> (<em>float</em><em>, </em><em>default is 1e-5</em>) – During deconvolution, division by small values in the convolve image
+of estimation and PSF may cause divergence. Therefore, division by
+values under <cite>eps</cite> is substituted to zero.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Deconvolved image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5529,11 +5561,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.mean_filter">
-<span class="sig-name descname"><span class="pre">mean_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.mean_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.mean_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">mean_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.mean_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.mean_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.mean_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Mean filter. Kernel is filled with same values.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -5560,10 +5592,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5571,12 +5603,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.median_filter">
-<span class="sig-name descname"><span class="pre">median_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.median_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.median_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">median_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.median_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.median_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.median_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Running multi-dimensional median filter.</p>
 <p>This filter is useful for deleting outliers generated by noise.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -5603,10 +5635,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5639,12 +5671,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.opening">
-<span class="sig-name descname"><span class="pre">opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.opening"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.opening" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.opening"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.opening" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.opening. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Morphological opening. If input is binary image, the running function will automatically switched to
 <code class="docutils literal notranslate"><span class="pre">binary_opening</span></code> to speed up calculation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
 <blockquote>
@@ -5671,10 +5703,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5682,11 +5714,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.pad">
-<span class="sig-name descname"><span class="pre">pad</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pad_width</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.pad"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.pad" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">pad</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pad_width</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.pad"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.pad" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.pad. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Pad image only for spatial dimensions.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>pad_width</strong> – See documentation of np.pad().</p></li>
 <li><p><strong>mode</strong> – See documentation of np.pad().</p></li>
@@ -5694,10 +5726,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>dims</strong> (<em>int</em><em> or </em><em>str</em><em>, </em><em>optional</em>) – Which dimension to pad.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Padded image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5737,28 +5769,29 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.power_spectra">
-<span class="sig-name descname"><span class="pre">power_spectra</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'same'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">zero_norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.power_spectra"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.power_spectra" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">power_spectra</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'same'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">zero_norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.power_spectra"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.power_spectra" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.power_spectra. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Return n-D power spectra of images, which is defined as:</p>
 <div class="math notranslate nohighlight">
 \[P = Re(F[I_{img}])^2 + Im(F[I_{img}])^2\]</div>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable of int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
+<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable</em><em> of </em><em>int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
 - integers: padded or cropped to the specified shape.
 - “square”: padded to smallest 2^N-long square.
 - “same” (default): no padding or cropping.</p></li>
 <li><p><strong>norm</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, maximum value of power spectra is adjusted to 1.</p></li>
 <li><p><strong>double_precision</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, FFT will be calculated using 64-bit float and 128-bit complex.</p></li>
+<li><p><strong>shift</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, call <code class="docutils literal notranslate"><span class="pre">np.fft.fftshift</span></code> at the first.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Power spectra</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5770,11 +5803,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.proj">
-<span class="sig-name descname"><span class="pre">proj</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.proj"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.proj" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">proj</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.proj"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.proj" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.proj. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Projection along any axis.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>axis</strong> (<em>str</em><em>, </em><em>optional</em>) – Along which axis projection will be calculated. If None, most plausible one will be chosen.</p></li>
 <li><p><strong>method</strong> (<em>str</em><em> or </em><em>callable</em><em>, </em><em>default is mean-projection.</em>) – Projection method. If str is given, it will converted to numpy function.</p></li>
@@ -5783,10 +5816,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>**kwargs</strong> – Other keyword arguments that will passed to projection function.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Projected image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5794,16 +5827,16 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.radon">
-<span class="sig-name descname"><span class="pre">radon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degrees</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">central_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxisLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.radon"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.radon" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">radon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degrees</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">central_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.radon"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.radon" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.radon. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Discrete Radon transformation of 2D or 3D image.</p>
 <p>Radon transformation is a list of projection of a same image from different angles.
 It generates tomographic n-D image slices from (n+1)-D image.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>degrees</strong> (<em>float</em><em> or </em><em>iterable of float</em>) – Rotation angles around the central axis in degrees.</p></li>
-<li><p><strong>central_axis</strong> (<em>axis-like</em><em> or </em><em>sequence of float</em><em>, </em><em>optional</em>) – Vector that defines the central axis of rotation.</p></li>
+<li><p><strong>degrees</strong> (<em>float</em><em> or </em><em>iterable</em><em> of </em><em>float</em>) – Rotation angles around the central axis in degrees.</p></li>
+<li><p><strong>central_axis</strong> (<em>axis-like</em><em> or </em><em>sequence</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Vector that defines the central axis of rotation.</p></li>
 <li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
 For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
 </p></li>
@@ -5811,13 +5844,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Tomographic image slices. The first spatial axis (“z” for zyx-image) will be dropped.
 If sequence of float is given as <code class="docutils literal notranslate"><span class="pre">degrees</span></code>, “degree” axis will be newly added at
 the position 0. For instance, if a zyx-image and <code class="docutils literal notranslate"><span class="pre">degrees=np.linspace(0,</span> <span class="pre">180,</span> <span class="pre">100)</span></code>
 are given, returned image has axes [“degree”, “y”, “x”].</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5829,10 +5862,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.rechunk">
-<span class="sig-name descname"><span class="pre">rechunk</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">block_size_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">balance</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.rechunk"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.rechunk" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">rechunk</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">block_size_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">balance</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.rechunk"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.rechunk" title="Permalink to this definition">¶</a></dt>
 <dd><p>Rechunk the bound dask array.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>chunks</strong> – Passed directly to dask.array’s rechunk</p></li>
 <li><p><strong>threshold</strong> – Passed directly to dask.array’s rechunk</p></li>
@@ -5840,10 +5873,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>balance</strong> – Passed directly to dask.array’s rechunk</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Rechunked dask array is bound.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5851,14 +5884,14 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.release">
-<span class="sig-name descname"><span class="pre">release</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.release"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.release" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">release</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.release"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.release" title="Permalink to this definition">¶</a></dt>
 <dd><p>Compute all the tasks and store the data in memory map, and read it as a dask array
 again.</p>
 </dd></dl>
 
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.shape">
-<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">shape</span></span><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.shape" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">shape</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">AxesTuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.shape" title="Permalink to this definition">¶</a></dt>
 <dd><p>Shape of the array.</p>
 </dd></dl>
 
@@ -5874,10 +5907,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dd><p>Copy of MetaArray.sort_axes. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Sort image dimensions to ptzcyx-order</p>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Sorted image</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5891,11 +5924,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.spline_filter">
-<span class="sig-name descname"><span class="pre">spline_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mirror'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.spline_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.spline_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">spline_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mirror'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.spline_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.spline_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of LabeledArray.spline_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Run spline filter.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
 For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
@@ -5906,10 +5939,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5931,13 +5964,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.threshold">
-<span class="sig-name descname"><span class="pre">threshold</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">thr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxisLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.threshold"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.threshold" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">threshold</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">thr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.threshold"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.threshold" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.threshold. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Apply thresholding to the image and create a binary image.</p>
 <p>The threshold value can be given with a float or a string that indicates what
 thresholding method will be used.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>thr</strong> (<em>float</em><em> or </em><em>str</em><em>, </em><em>optional</em>) – Threshold value, percentage or thresholding algorithm.</p></li>
 <li><p><strong>along</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Dimensions that will not share the same threshold. For instance, if
@@ -5946,10 +5979,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>**kwargs</strong> – Keyword arguments that will passed to function indicated in ‘method’.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Boolian array.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -5963,32 +5996,15 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dl>
 </dd></dl>
 
+<dl class="py attribute">
+<dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.tiled">
+<span class="sig-name descname"><span class="pre">tiled</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.tiled.TiledAccessor" title="impy.arrays.tiled.TiledAccessor"><span class="pre">TiledAccessor</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.tiled" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.tiled_lowpass_filter">
-<span class="sig-name descname"><span class="pre">tiled_lowpass_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">overlap</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">16</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.tiled_lowpass_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.tiled_lowpass_filter" title="Permalink to this definition">¶</a></dt>
-<dd><p>Copy of ImgArray.tiled_lowpass_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
-<p>Tile-by-tile Butterworth low-pass filter. This method is an approximation of the standard
-low-pass filter, which would be useful when the image is large.</p>
-<dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><ul class="simple">
-<li><p><strong>cutoff</strong> (<em>float</em><em> or </em><em>array-like</em><em>, </em><em>default is 0.2</em>) – Cutoff frequency.</p></li>
-<li><p><strong>chunks</strong> (<em>str</em><em> or </em><em>sequence of int</em>) – Chunk size of each lowpass filter task.</p></li>
-<li><p><strong>order</strong> (<em>float</em><em>, </em><em>default is 2</em>) – Steepness of cutoff.</p></li>
-<li><p><strong>overlap</strong> (<em>int</em><em>, </em><em>default is 16</em>) – Overlapping pixels at the edges of tiles.</p></li>
-<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
-For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
-<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
-</ul>
-</dd>
-<dt class="field-even">Returns</dt>
-<dd class="field-even"><p>Filtered image.</p>
-</dd>
-<dt class="field-odd">Return type</dt>
-<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
-</dd>
-</dl>
-</dd></dl>
+<span class="sig-name descname"><span class="pre">tiled_lowpass_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">overlap</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">16</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.tiled_lowpass_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.tiled_lowpass_filter" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.track_drift">
@@ -5997,17 +6013,17 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <p>Calculate yx-directional drift using the method equivalent to
 <code class="docutils literal notranslate"><span class="pre">skimage.registration.phase_cross_correlation</span></code>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>along</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Along which axis drift will be calculated.</p></li>
 <li><p><strong>show_drift</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, plot the result.</p></li>
 <li><p><strong>upsample_factor</strong> (<em>int</em><em>, </em><em>default is 10</em>) – Up-sampling factor when calculating phase cross correlation.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>DataFrame structure with x,y columns</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
 </dd>
 </dl>
@@ -6021,14 +6037,9 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 ‘axes’ will also be arranged.</p>
 </dd></dl>
 
-<dl class="py attribute">
-<dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.value">
-<span class="sig-name descname"><span class="pre">value</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">Any</span></em><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.value" title="Permalink to this definition">¶</a></dt>
-<dd></dd></dl>
-
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.lazy.LazyImgArray.wiener">
-<span class="sig-name descname"><span class="pre">wiener</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">numpy.ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.wiener"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.wiener" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">wiener</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.wiener"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.lazy.LazyImgArray.wiener" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of ImgArray.wiener. This function returns the same result but the value is evaluated lazily as an dask array.</p>
 <p>Classical wiener deconvolution. This algorithm has the serious ringing problem
 if parameters are set to wrong values.</p>
@@ -6037,19 +6048,20 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="math notranslate nohighlight">\(Y_{res}\)</span>: restored image;
 <span class="math notranslate nohighlight">\(H\)</span> : FFT of point spread function (PSF);</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>psf</strong> (<em>np.ndarray</em>) – Point spread function.</p></li>
+<li><p><strong>psf</strong> (<em>ndarray</em><em> or </em><em>callable</em>) – Point spread function. If a function is given, <cite>psf(shape)</cite> will be
+called to generate the PSF.</p></li>
 <li><p><strong>lmd</strong> (<em>float</em><em>, </em><em>default is 0.1</em>) – Constant value used in the deconvolution. See Formulation below.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Deconvolved image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
 </dd>
 </dl>
@@ -6068,11 +6080,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.arrays.phasearray">
-<span id="impy-arrays-phasearray-module"></span><h2>impy.arrays.phasearray module<a class="headerlink" href="#module-impy.arrays.phasearray" title="Permalink to this headline">¶</a></h2>
+<span id="impy-arrays-phasearray-module"></span><h2>impy.arrays.phasearray module<a class="headerlink" href="#module-impy.arrays.phasearray" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.arrays.phasearray.PhaseArray">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.phasearray.</span></span><span class="sig-name descname"><span class="pre">PhaseArray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">obj</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">source</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metadata</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'rad'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">border</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.phasearray.PhaseArray" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="#impy.arrays.labeledarray.LabeledArray" title="impy.arrays.labeledarray.LabeledArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.arrays.labeledarray.LabeledArray</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="#impy.arrays.labeledarray.LabeledArray" title="impy.arrays.labeledarray.LabeledArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">LabeledArray</span></code></a></p>
 <dl class="py attribute">
 <dt class="sig sig-object py" id="impy.arrays.phasearray.PhaseArray.additional_props">
 <span class="sig-name descname"><span class="pre">additional_props</span></span><em class="property"><span class="w"> </span><span class="p"><span class="pre">=</span></span><span class="w"> </span><span class="pre">['_source',</span> <span class="pre">'_metadata',</span> <span class="pre">'_name',</span> <span class="pre">'unit',</span> <span class="pre">'border']</span></em><a class="headerlink" href="#impy.arrays.phasearray.PhaseArray.additional_props" title="Permalink to this definition">¶</a></dt>
@@ -6085,7 +6097,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.phasearray.PhaseArray.binning">
-<span class="sig-name descname"><span class="pre">binning</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">binsize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_edges</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.binning"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.phasearray.PhaseArray.binning" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">binning</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">binsize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_edges</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.binning"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.phasearray.PhaseArray.binning" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py attribute">
@@ -6095,7 +6107,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.phasearray.PhaseArray.deg2rad">
-<span class="sig-name descname"><span class="pre">deg2rad</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">impy.arrays.phasearray.PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.deg2rad"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.phasearray.PhaseArray.deg2rad" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">deg2rad</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.deg2rad"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.phasearray.PhaseArray.deg2rad" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
@@ -6105,13 +6117,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.phasearray.PhaseArray.map_coordinates">
-<span class="sig-name descname"><span class="pre">map_coordinates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coordinates</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">PaddingMode</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefilter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.map_coordinates"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.phasearray.PhaseArray.map_coordinates" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">map_coordinates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coordinates</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefilter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.map_coordinates"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.phasearray.PhaseArray.map_coordinates" title="Permalink to this definition">¶</a></dt>
 <dd><p>Coordinate mapping in the image. See <code class="docutils literal notranslate"><span class="pre">scipy.ndimage.map_coordinates</span></code>.</p>
 <p>For a <code class="docutils literal notranslate"><span class="pre">PhaseArray</span></code>, standard interpolation does not work because of its specific
 addition rule. Phase image is first converted into a complex array by <span class="math notranslate nohighlight">\(e^{-i \psi}\)</span>
 and the phase is restored by logarithm after interpolation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>coordinates</strong> (<em>ArrayLike</em>) – Interpolation coordinates. Must be (D, N) or (D, X_1, …, X_D) shape.</p></li>
 <li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
@@ -6125,10 +6137,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Transformed image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray">PhaseArray</a></p>
 </dd>
 </dl>
@@ -6136,21 +6148,21 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.phasearray.PhaseArray.mean_filter">
-<span class="sig-name descname"><span class="pre">mean_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">impy.arrays.phasearray.PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.mean_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.phasearray.PhaseArray.mean_filter" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">mean_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.mean_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.phasearray.PhaseArray.mean_filter" title="Permalink to this definition">¶</a></dt>
 <dd><p>Mean filter using phase averaging method:</p>
 <p><span class="math notranslate nohighlight">\(\arg{\sum_{k}{e^{i X_k}}}\)</span></p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em>, </em><em>default is 1</em>) – Radius of kernel.</p></li>
 <li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions.</p></li>
 <li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If update self to filtered image.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Filtered image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray">PhaseArray</a></p>
 </dd>
 </dl>
@@ -6164,7 +6176,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.phasearray.PhaseArray.rad2deg">
-<span class="sig-name descname"><span class="pre">rad2deg</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">impy.arrays.phasearray.PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.rad2deg"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.phasearray.PhaseArray.rad2deg" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">rad2deg</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.rad2deg"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.phasearray.PhaseArray.rad2deg" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
@@ -6178,14 +6190,14 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 In PhaseArray, instead of mean_intensity you should use “phase_mean”. The
 phase_mean function is included so that it can be passed in <code class="docutils literal notranslate"><span class="pre">properties</span></code> argument.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>properties</strong> (<em>iterable</em><em>, </em><em>optional</em>) – properties to analyze, see skimage.measure.regionprops.</p></li>
-<li><p><strong>extra_properties</strong> (<em>iterable of callable</em><em>, </em><em>optional</em>) – extra properties to analyze, see skimage.measure.regionprops.</p></li>
+<li><p><strong>extra_properties</strong> (<em>iterable</em><em> of </em><em>callable</em><em>, </em><em>optional</em>) – extra properties to analyze, see skimage.measure.regionprops.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Return type</dt>
-<dd class="field-even"><p>DataDict of PropArray</p>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
+<dd class="field-even"><p><a class="reference internal" href="impy.html#impy.collections.DataDict" title="impy.collections.DataDict">DataDict</a> of <a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray">PropArray</a></p>
 </dd>
 </dl>
 <p class="rubric">Example</p>
@@ -6201,12 +6213,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.phasearray.PhaseArray.reslice">
-<span class="sig-name descname"><span class="pre">reslice</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">src</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dst</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">impy.arrays.specials.PropArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.reslice"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.phasearray.PhaseArray.reslice" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">reslice</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">src</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dst</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.reslice"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.phasearray.PhaseArray.reslice" title="Permalink to this definition">¶</a></dt>
 <dd><p>Measure line profile iteratively for every slice of image.</p>
 <p>Because input is phase, we can not apply standard interpolation to calculate
 intensities on float-coordinates.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>src</strong> (<em>array-like</em>) – Source coordinate.</p></li>
 <li><p><strong>dst</strong> (<em>array-like</em>) – Destination coordinate.</p></li>
@@ -6214,10 +6226,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>dims</strong> (<em>int</em><em> or </em><em>str</em><em>, </em><em>optional</em>) – Spatial dimensions.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Line scans.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray">PropArray</a></p>
 </dd>
 </dl>
@@ -6228,7 +6240,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">set_border</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">a</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">b</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.set_border"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.phasearray.PhaseArray.set_border" title="Permalink to this definition">¶</a></dt>
 <dd><p>Set new border safely.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>a</strong> (<em>float</em>) – New lower border.</p></li>
 <li><p><strong>b</strong> (<em>float</em>) – New higher border.</p></li>
@@ -6246,11 +6258,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.arrays.specials">
-<span id="impy-arrays-specials-module"></span><h2>impy.arrays.specials module<a class="headerlink" href="#module-impy.arrays.specials" title="Permalink to this headline">¶</a></h2>
+<span id="impy-arrays-specials-module"></span><h2>impy.arrays.specials module<a class="headerlink" href="#module-impy.arrays.specials" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.arrays.specials.PropArray">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.specials.</span></span><span class="sig-name descname"><span class="pre">PropArray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">obj</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">source</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metadata</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">propname</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/specials.html#PropArray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.specials.PropArray" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.arrays.bases.metaarray.MetaArray</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">MetaArray</span></code></a></p>
 <dl class="py attribute">
 <dt class="sig sig-object py" id="impy.arrays.specials.PropArray.additional_props">
 <span class="sig-name descname"><span class="pre">additional_props</span></span><em class="property"><span class="w"> </span><span class="p"><span class="pre">=</span></span><span class="w"> </span><span class="pre">['_source',</span> <span class="pre">'_metadata',</span> <span class="pre">'_name',</span> <span class="pre">'propname']</span></em><a class="headerlink" href="#impy.arrays.specials.PropArray.additional_props" title="Permalink to this definition">¶</a></dt>
@@ -6261,13 +6273,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">as_frame</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">colname</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'f'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.frame.html#impy.frame.frames.AxesFrame" title="impy.frame.frames.AxesFrame"><span class="pre">AxesFrame</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/specials.html#PropArray.as_frame"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.specials.PropArray.as_frame" title="Permalink to this definition">¶</a></dt>
 <dd><p>N-dimensional data to DataFrame. The intensity data is stored in the <cite>colname</cite> column.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>colname</strong> (<em>str</em><em>, </em><em>default is &quot;f&quot;</em>) – The name of new column.</p>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>DataFrame with PropArray data.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.AxesFrame" title="impy.frame.frames.AxesFrame">AxesFrame</a></p>
 </dd>
 </dl>
@@ -6275,10 +6287,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.specials.PropArray.curve_fit">
-<span class="sig-name descname"><span class="pre">curve_fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">f</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p0</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'t'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_fit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.html#impy.collections.DataDict" title="impy.collections.DataDict"><span class="pre">impy.collections.DataDict</span></a><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">impy.arrays.specials.PropArray</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/specials.html#PropArray.curve_fit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.specials.PropArray.curve_fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">curve_fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">f</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p0</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'t'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_fit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.html#impy.collections.DataDict" title="impy.collections.DataDict"><span class="pre">DataDict</span></a><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/specials.html#PropArray.curve_fit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.specials.PropArray.curve_fit" title="Permalink to this definition">¶</a></dt>
 <dd><p>Run scipy.optimize.curve_fit for each dimesion.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>f</strong> (<em>callable</em>) – Model function.</p></li>
 <li><p><strong>p0</strong> (<em>array</em><em> or </em><em>callable</em><em>, </em><em>optional</em>) – Initial parameter. Callable object that estimate initial paramter can also
@@ -6288,12 +6300,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 save much memory.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>params : Fitting parameters
 covs : Covariances
 fit : fitting trajectories (if return_fit==True)</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.html#impy.collections.DataDict" title="impy.collections.DataDict">DataDict</a></p>
 </dd>
 </dl>
@@ -6301,10 +6313,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.arrays.specials.PropArray.hist">
-<span class="sig-name descname"><span class="pre">hist</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'N'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bins</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cmap</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'jet'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cmap_range</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">(0.0,</span> <span class="pre">1.0)</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">impy.arrays.specials.PropArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/specials.html#PropArray.hist"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.specials.PropArray.hist" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">hist</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'N'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bins</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cmap</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'jet'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cmap_range</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">(0.0,</span> <span class="pre">1.0)</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/specials.html#PropArray.hist"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.specials.PropArray.hist" title="Permalink to this definition">¶</a></dt>
 <dd><p>Plot histogram.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>along</strong> (<em>str</em><em>, </em><em>optional</em>) – Which axis will be the x-axis of plot, by default None</p></li>
 <li><p><strong>bins</strong> (<em>int</em><em>, </em><em>optional</em>) – Bin number of histogram.</p></li>
@@ -6312,7 +6324,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>cmap_range</strong> (<em>tuple</em><em>, </em><em>default is</em><em> (</em><em>0</em><em>, </em><em>1</em><em>)</em>) – Range of float for colormap iteration.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p>self</p>
 </dd>
 </dl>
@@ -6323,7 +6335,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cmap</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'jet'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cmap_range</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(0,</span> <span class="pre">1)</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/specials.html#PropArray.plot"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.specials.PropArray.plot" title="Permalink to this definition">¶</a></dt>
 <dd><p>Plot all the results with x-axis defined by <cite>along</cite>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>along</strong> (<em>str</em><em>, </em><em>optional</em>) – Which axis will be the x-axis of plot, by default None</p></li>
 <li><p><strong>cmap</strong> (<em>str</em><em>, </em><em>default is &quot;jet&quot;</em>) – Colormap of each graph.</p></li>
@@ -6340,9 +6352,6072 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </dd></dl>
 
+</section>
+<section id="module-impy.arrays.tiled">
+<span id="impy-arrays-tiled-module"></span><h2>impy.arrays.tiled module<a class="headerlink" href="#module-impy.arrays.tiled" title="Permalink to this heading">¶</a></h2>
+<dl class="py class">
+<dt class="sig sig-object py" id="impy.arrays.tiled.TiledAccessor">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.tiled.</span></span><span class="sig-name descname"><span class="pre">TiledAccessor</span></span><a class="reference internal" href="../_modules/impy/arrays/tiled.html#TiledAccessor"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.tiled.TiledAccessor" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">Generic</span></code>[<code class="xref py py-obj docutils literal notranslate"><span class="pre">_T</span></code>]</p>
+</dd></dl>
+
+<dl class="py class">
+<dt class="sig sig-object py" id="impy.arrays.tiled.TiledImage">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.tiled.</span></span><span class="sig-name descname"><span class="pre">TiledImage</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">_T</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'auto'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">boundary</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'periodic'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'none'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'periodic'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'none'</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/tiled.html#TiledImage"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.tiled.TiledImage" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">Generic</span></code>[<code class="xref py py-obj docutils literal notranslate"><span class="pre">_T</span></code>]</p>
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.tiled.TiledImage.boundary">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">boundary</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">str</span></em><a class="headerlink" href="#impy.arrays.tiled.TiledImage.boundary" title="Permalink to this definition">¶</a></dt>
+<dd><p>How to handle the boundary of the image.</p>
+</dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.tiled.TiledImage.chunks">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">chunks</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#impy.arrays.tiled.TiledImage.chunks" title="Permalink to this definition">¶</a></dt>
+<dd><p>Chunksize of the tiled image.</p>
+</dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.tiled.TiledImage.depth">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">depth</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#impy.arrays.tiled.TiledImage.depth" title="Permalink to this definition">¶</a></dt>
+<dd><p>Depth of overlaps</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.tiled.TiledImage.dog_filter">
+<span class="sig-name descname"><span class="pre">dog_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">low_sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">high_sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fourier</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">_T</span></span></span><a class="reference internal" href="../_modules/impy/arrays/tiled.html#TiledImage.dog_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.tiled.TiledImage.dog_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Run Difference of Gaussian filter. This function does not support <cite>update</cite>
+argument because intensity can be negative.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>low_sigma</strong> (<em>scalar</em><em> or </em><em>array</em><em> of </em><em>scalars</em><em>, </em><em>default is 1.</em>) – lower standard deviation(s) of Gaussian.</p></li>
+<li><p><strong>high_sigma</strong> (<em>scalar</em><em> or </em><em>array</em><em> of </em><em>scalars</em><em>, </em><em>default is x1.6</em><em> of </em><em>low_sigma.</em>) – higher standard deviation(s) of Gaussian.</p></li>
+<li><p><strong>{fourier}</strong> – </p></li>
+</ul>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.tiled.TiledImage.gaussian_filter">
+<span class="sig-name descname"><span class="pre">gaussian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fourier</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">_T</span></span></span><a class="reference internal" href="../_modules/impy/arrays/tiled.html#TiledImage.gaussian_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.tiled.TiledImage.gaussian_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Run Gaussian filter (Gaussian blur).</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>{sigma}{fourier}</strong> – </p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.tiled.TiledImage.log_filter">
+<span class="sig-name descname"><span class="pre">log_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">_T</span></span></span><a class="reference internal" href="../_modules/impy/arrays/tiled.html#TiledImage.log_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.tiled.TiledImage.log_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Laplacian of Gaussian filter.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>{sigma}</strong> – </p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.tiled.TiledImage.lowpass_filter">
+<span class="sig-name descname"><span class="pre">lowpass_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">_T</span></span></span><a class="reference internal" href="../_modules/impy/arrays/tiled.html#TiledImage.lowpass_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.tiled.TiledImage.lowpass_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Tile-wise butterworth lowpass filter.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>cutoff</strong> (<em>float</em><em> or </em><em>array-like</em><em>, </em><em>default is 0.2</em>) – Cutoff frequency.</p></li>
+<li><p><strong>order</strong> (<em>float</em><em>, </em><em>default is 2</em>) – Steepness of cutoff.</p></li>
+</ul>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.tiled.TiledImage.lucy">
+<span class="sig-name descname"><span class="pre">lucy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">niter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1e-05</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">_T</span></span></span><a class="reference internal" href="../_modules/impy/arrays/tiled.html#TiledImage.lucy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.tiled.TiledImage.lucy" title="Permalink to this definition">¶</a></dt>
+<dd><p>Deconvolution of N-dimensional image, using Richardson-Lucy’s algorithm.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>psf</strong> (<em>ndarray</em><em> or </em><em>callable</em>) – Point spread function. If a function is given, <cite>psf(shape)</cite> will be
+called to generate the PSF.</p></li>
+<li><p><strong>niter</strong> (<em>int</em><em>, </em><em>default is 50.</em>) – Number of iterations.</p></li>
+<li><p><strong>eps</strong> (<em>float</em><em>, </em><em>default is 1e-5</em>) – During deconvolution, division by small values in the convolve image
+of estimation and PSF may cause divergence. Therefore, division by
+values under <cite>eps</cite> is substituted to zero.</p></li>
+</ul>
+</dd>
+</dl>
+</dd></dl>
+
+</dd></dl>
+
 </section>
 <section id="module-impy.arrays">
-<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-impy.arrays" title="Permalink to this headline">¶</a></h2>
+<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-impy.arrays" title="Permalink to this heading">¶</a></h2>
+<dl class="py class">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.</span></span><span class="sig-name descname"><span class="pre">BigImgArray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">obj</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DaskArray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">source</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metadata</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/big.html#BigImgArray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.BigImgArray" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">LazyImgArray</span></code></a></p>
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.affine">
+<span class="sig-name descname"><span class="pre">affine</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">matrix</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rotation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shear</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">translation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.affine" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.affine. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Convert image by Affine transformation. 2D Affine transformation is written as:</p>
+<div class="math notranslate nohighlight">
+\[\begin{split}\begin{bmatrix} y'\\ x' \\1 \end{bmatrix} =
+\begin{bmatrix} A_{00} &amp; A_{01} &amp; A_{02} \\
+                A_{10} &amp; A_{11} &amp; A_{12} \\
+                    0 &amp;      0 &amp;      1  \end{bmatrix}
+                \begin{bmatrix} y \\x\\ 1 \end{bmatrix}\end{split}\]</div>
+<p>and similarly, n-D Affine transformation can be described as (n+1)-D matrix.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>matrix</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
+<li><p><strong>scale</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
+<li><p><strong>rotation</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
+<li><p><strong>shear</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
+<li><p><strong>translation</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>output_shape</strong> (<em>tuple</em><em> of </em><em>int</em><em>, </em><em>optional</em>) – Shape of output array.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Transformed image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.as_float">
+<span class="sig-name descname"><span class="pre">as_float</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.as_float" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.as_img_type">
+<span class="sig-name descname"><span class="pre">as_img_type</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dtype=&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.as_img_type" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.as_uint16">
+<span class="sig-name descname"><span class="pre">as_uint16</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.as_uint16" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.as_uint8">
+<span class="sig-name descname"><span class="pre">as_uint8</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.as_uint8" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.binning">
+<span class="sig-name descname"><span class="pre">binning</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">binsize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_edges</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.binning" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.binning. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Binning of images. This function is similar to <code class="docutils literal notranslate"><span class="pre">rescale</span></code> but is strictly
+binned by <span class="math notranslate nohighlight">\(N \times N\)</span> blocks. Also, any numpy functions that accept
+“axis” argument are supported for reduce functions.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>binsize</strong> (<em>int</em><em>, </em><em>default is 2</em>) – Bin size, such as 2x2.</p></li>
+<li><p><strong>method</strong> (<em>str</em><em> or </em><em>callable</em><em>, </em><em>default is numpy.mean</em>) – Reduce function applied to each bin.</p></li>
+<li><p><strong>check_edges</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, only divisible <code class="docutils literal notranslate"><span class="pre">binsize</span></code> is accepted. If False, image is
+cropped at the end to match <cite>binsize</cite>.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Binned image</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.closing">
+<span class="sig-name descname"><span class="pre">closing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.closing" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.closing. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Morphological closing.</p>
+<p>If input is binary image, the running function will automatically switched to
+<code class="docutils literal notranslate"><span class="pre">binary_closing</span></code> to speed up calculation.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.convolve">
+<span class="sig-name descname"><span class="pre">convolve</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kernel</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.convolve" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.convolve. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>General linear convolution by running kernel filtering.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>kernel</strong> (<em>array-like</em>) – Convolution kernel.</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Convolved image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.dilation">
+<span class="sig-name descname"><span class="pre">dilation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.dilation" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.dilation. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Morphological dilation. If input is binary image, the running function will automatically switched to
+<code class="docutils literal notranslate"><span class="pre">binary_dilation</span></code> to speed up calculation.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.drift_correction">
+<span class="sig-name descname"><span class="pre">drift_correction</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Coords</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ref</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray"><span class="pre">ImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">zero_ave</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">affine_kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.drift_correction" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.drift_correction. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Drift correction using iterative Affine translation. If translation vectors <code class="docutils literal notranslate"><span class="pre">shift</span></code>
+is not given, then it will be determined using <code class="docutils literal notranslate"><span class="pre">track_drift</span></code> method of ImgArray.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>shift</strong> (<em>DataFrame</em><em> or </em><em>(</em><em>N</em><em>, </em><em>D</em><em>) </em><em>array</em><em>, </em><em>optional</em>) – Translation vectors. If DataFrame, it must have columns named with all the symbols
+contained in <code class="docutils literal notranslate"><span class="pre">dims</span></code>.</p></li>
+<li><p><strong>ref</strong> (<a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray"><em>ImgArray</em></a><em>, </em><em>optional</em>) – The reference n-D image to determine drift, if <code class="docutils literal notranslate"><span class="pre">shift</span></code> was not given.</p></li>
+<li><p><strong>zero_ave</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, average shift will be zero.</p></li>
+<li><p><strong>along</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Along which axis drift will be corrected.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+<li><p><strong>affine_kwargs</strong> – Keyword arguments that will be passed to <code class="docutils literal notranslate"><span class="pre">warp</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Corrected image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<dl>
+<dt>Drift correction of multichannel image using the first channel as the reference.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">drift_correction</span><span class="p">(</span><span class="n">ref</span><span class="o">=</span><span class="n">img</span><span class="p">[</span><span class="s2">&quot;c=0&quot;</span><span class="p">])</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.edge_filter">
+<span class="sig-name descname"><span class="pre">edge_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'sobel'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.edge_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.edge_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Sobel filter. This filter is useful for edge detection.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>method</strong> (<em>str</em><em>, </em><em>{&quot;sobel&quot;</em><em>, </em><em>&quot;farid&quot;</em><em>, </em><em>&quot;scharr&quot;</em><em>, </em><em>&quot;prewitt&quot;}</em><em>, </em><em>default is &quot;sobel&quot;</em>) – Edge operator name.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.erosion">
+<span class="sig-name descname"><span class="pre">erosion</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.erosion" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.erosion. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Morphological erosion.</p>
+<p>If input is binary image, the running function will automatically switched to
+<code class="docutils literal notranslate"><span class="pre">binary_erosion</span></code> to speed up calculation.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.fft">
+<span class="sig-name descname"><span class="pre">fft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'same'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.fft" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.fft. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Fast Fourier transformation. This function returns complex array, which is
+inconpatible with some ImgArray functions.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable</em><em> of </em><em>int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
+- integers: padded or cropped to the specified shape.
+- “square”: padded to smallest 2^N-long square.
+- “same” (default): no padding or cropping.</p></li>
+<li><p><strong>shift</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, call <code class="docutils literal notranslate"><span class="pre">np.fft.fftshift</span></code> in the end.</p></li>
+<li><p><strong>double_precision</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, FFT will be calculated using 64-bit float and 128-bit complex.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>FFT image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><code class="xref py py-obj docutils literal notranslate"><span class="pre">local_dft</span></code></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.gaussian_filter">
+<span class="sig-name descname"><span class="pre">gaussian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.gaussian_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.gaussian_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Run Gaussian filter (Gaussian blur).</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
+<li><p><strong>fourier</strong> (<em>bool</em><em>, </em><em>default is False</em>) – Whether to run the convolution in Fourier space. This option is useful when the kernel or the image is large.
+Note that discrete Fourier transform assumes that the image is periodic, so that if intensities of the input image are not consecutive at img[0] and img[-1], you may get some artifacts at the boundary.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.ifft">
+<span class="sig-name descname"><span class="pre">ifft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">real</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.ifft" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.ifft. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Fast Inverse Fourier transformation. Complementary function with <cite>fft()</cite>.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>real</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, only the real part is returned.</p></li>
+<li><p><strong>shift</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, call <code class="docutils literal notranslate"><span class="pre">np.fft.ifftshift</span></code> at the first.</p></li>
+<li><p><strong>double_precision</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, FFT will be calculated using 64-bit float and 128-bit complex.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>IFFT image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.kalman_filter">
+<span class="sig-name descname"><span class="pre">kalman_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">gain</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">noise_var</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'t'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.kalman_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.kalman_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Kalman filter for image smoothing. This function is same as “Kalman Stack Filter” in ImageJ but support
+batch processing. This filter is useful for preprocessing of particle tracking.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>gain</strong> (<em>float</em><em>, </em><em>default is 0.8</em>) – Filter gain.</p></li>
+<li><p><strong>noise_var</strong> (<em>float</em><em>, </em><em>default is 0.05</em>) – Initial estimate of noise variance.</p></li>
+<li><p><strong>along</strong> (<em>str</em><em>, </em><em>default is &quot;t&quot;</em>) – Which axis will be the time axis.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.laplacian_filter">
+<span class="sig-name descname"><span class="pre">laplacian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.laplacian_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.laplacian_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Edge detection using Laplacian filter. Kernel is made by <cite>skimage</cite>’s function.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>int</em><em>, </em><em>default is 1</em>) – Radius of kernel. Shape of kernel will be (2*radius+1, 2*radius+1).</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.lucy">
+<span class="sig-name descname"><span class="pre">lucy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">niter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1e-05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.lucy" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.lucy. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Deconvolution of N-dimensional image, using Richardson-Lucy’s algorithm.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>psf</strong> (<em>ndarray</em><em> or </em><em>callable</em>) – Point spread function. If a function is given, <cite>psf(shape)</cite> will be
+called to generate the PSF.</p></li>
+<li><p><strong>niter</strong> (<em>int</em><em>, </em><em>default is 50.</em>) – Number of iterations.</p></li>
+<li><p><strong>eps</strong> (<em>float</em><em>, </em><em>default is 1e-5</em>) – During deconvolution, division by small values in the convolve image
+of estimation and PSF may cause divergence. Therefore, division by
+values under <cite>eps</cite> is substituted to zero.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Deconvolved image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><code class="xref py py-obj docutils literal notranslate"><span class="pre">lucy_tv</span></code>, <a class="reference internal" href="#impy.arrays.BigImgArray.wiener" title="impy.arrays.BigImgArray.wiener"><code class="xref py py-obj docutils literal notranslate"><span class="pre">wiener</span></code></a></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.mean_filter">
+<span class="sig-name descname"><span class="pre">mean_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.mean_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.mean_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Mean filter. Kernel is filled with same values.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.median_filter">
+<span class="sig-name descname"><span class="pre">median_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.median_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.median_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Running multi-dimensional median filter.</p>
+<p>This filter is useful for deleting outliers generated by noise.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.opening">
+<span class="sig-name descname"><span class="pre">opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.opening" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.opening. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Morphological opening. If input is binary image, the running function will automatically switched to
+<code class="docutils literal notranslate"><span class="pre">binary_opening</span></code> to speed up calculation.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.power_spectra">
+<span class="sig-name descname"><span class="pre">power_spectra</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'same'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">zero_norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.power_spectra" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.power_spectra. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Return n-D power spectra of images, which is defined as:</p>
+<div class="math notranslate nohighlight">
+\[P = Re(F[I_{img}])^2 + Im(F[I_{img}])^2\]</div>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable</em><em> of </em><em>int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
+- integers: padded or cropped to the specified shape.
+- “square”: padded to smallest 2^N-long square.
+- “same” (default): no padding or cropping.</p></li>
+<li><p><strong>norm</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, maximum value of power spectra is adjusted to 1.</p></li>
+<li><p><strong>double_precision</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, FFT will be calculated using 64-bit float and 128-bit complex.</p></li>
+<li><p><strong>shift</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, call <code class="docutils literal notranslate"><span class="pre">np.fft.fftshift</span></code> at the first.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Power spectra</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><code class="xref py py-obj docutils literal notranslate"><span class="pre">local_power_spectra</span></code></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.proj">
+<span class="sig-name descname"><span class="pre">proj</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.proj" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.proj. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Projection along any axis.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>axis</strong> (<em>str</em><em>, </em><em>optional</em>) – Along which axis projection will be calculated. If None, most plausible one will be chosen.</p></li>
+<li><p><strong>method</strong> (<em>str</em><em> or </em><em>callable</em><em>, </em><em>default is mean-projection.</em>) – Projection method. If str is given, it will converted to numpy function.</p></li>
+<li><p><strong>mask</strong> (<em>array-like</em><em>, </em><em>optional</em>) – If provided, input image will be converted to np.ma.array and <code class="docutils literal notranslate"><span class="pre">method</span></code> will also be interpreted
+as an masked functio if possible.</p></li>
+<li><p><strong>**kwargs</strong> – Other keyword arguments that will passed to projection function.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Projected image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.radon">
+<span class="sig-name descname"><span class="pre">radon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degrees</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">central_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.radon" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.radon. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Discrete Radon transformation of 2D or 3D image.</p>
+<p>Radon transformation is a list of projection of a same image from different angles.
+It generates tomographic n-D image slices from (n+1)-D image.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>degrees</strong> (<em>float</em><em> or </em><em>iterable</em><em> of </em><em>float</em>) – Rotation angles around the central axis in degrees.</p></li>
+<li><p><strong>central_axis</strong> (<em>axis-like</em><em> or </em><em>sequence</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Vector that defines the central axis of rotation.</p></li>
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Tomographic image slices. The first spatial axis (“z” for zyx-image) will be dropped.
+If sequence of float is given as <code class="docutils literal notranslate"><span class="pre">degrees</span></code>, “degree” axis will be newly added at
+the position 0. For instance, if a zyx-image and <code class="docutils literal notranslate"><span class="pre">degrees=np.linspace(0,</span> <span class="pre">180,</span> <span class="pre">100)</span></code>
+are given, returned image has axes [“degree”, “y”, “x”].</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><code class="xref py py-obj docutils literal notranslate"><span class="pre">iradon</span></code></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.spline_filter">
+<span class="sig-name descname"><span class="pre">spline_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mirror'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.spline_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of LabeledArray.spline_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Run spline filter.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.tiled_lowpass_filter">
+<span class="sig-name descname"><span class="pre">tiled_lowpass_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">overlap</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">16</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.tiled_lowpass_filter" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.track_drift">
+<span class="sig-name descname"><span class="pre">track_drift</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">DaskArray</span></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.track_drift" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.track_drift. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Calculate yx-directional drift using the method equivalent to
+<code class="docutils literal notranslate"><span class="pre">skimage.registration.phase_cross_correlation</span></code>.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>along</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Along which axis drift will be calculated.</p></li>
+<li><p><strong>show_drift</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, plot the result.</p></li>
+<li><p><strong>upsample_factor</strong> (<em>int</em><em>, </em><em>default is 10</em>) – Up-sampling factor when calculating phase cross correlation.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>DataFrame structure with x,y columns</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.BigImgArray.wiener">
+<span class="sig-name descname"><span class="pre">wiener</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.BigImgArray.wiener" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.wiener. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Classical wiener deconvolution. This algorithm has the serious ringing problem
+if parameters are set to wrong values.</p>
+<p><span class="math notranslate nohighlight">\(F[Y_{res}] = \frac{F[Y_{obs}] \cdot \bar{H}}{|H|^2 + \lambda}\)</span></p>
+<p><span class="math notranslate nohighlight">\(Y_{obs}\)</span>: observed image;
+<span class="math notranslate nohighlight">\(Y_{res}\)</span>: restored image;
+<span class="math notranslate nohighlight">\(H\)</span> : FFT of point spread function (PSF);</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>psf</strong> (<em>ndarray</em><em> or </em><em>callable</em>) – Point spread function. If a function is given, <cite>psf(shape)</cite> will be
+called to generate the PSF.</p></li>
+<li><p><strong>lmd</strong> (<em>float</em><em>, </em><em>default is 0.1</em>) – Constant value used in the deconvolution. See Formulation below.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Deconvolved image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.BigImgArray.lucy" title="impy.arrays.BigImgArray.lucy"><code class="xref py py-obj docutils literal notranslate"><span class="pre">lucy</span></code></a>, <code class="xref py py-obj docutils literal notranslate"><span class="pre">lucy_tv</span></code></p>
+</div>
+</dd></dl>
+
+</dd></dl>
+
+<dl class="py class">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.</span></span><span class="sig-name descname"><span class="pre">ImgArray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">obj</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">source</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Path</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metadata</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <a class="reference internal" href="#impy.arrays.labeledarray.LabeledArray" title="impy.arrays.labeledarray.LabeledArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">LabeledArray</span></code></a></p>
+<p>An n-D array for image analysis.</p>
+<dl class="py attribute">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.axes">
+<span class="sig-name descname"><span class="pre">axes</span></span><a class="headerlink" href="#impy.arrays.ImgArray.axes" title="Permalink to this definition">¶</a></dt>
+<dd><p>Image axes, such as “zyx” or “tcyx”.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>str</p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py attribute">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.scale">
+<span class="sig-name descname"><span class="pre">scale</span></span><a class="headerlink" href="#impy.arrays.ImgArray.scale" title="Permalink to this definition">¶</a></dt>
+<dd><p>Physical scale along each axis. For instance, scale of x-axis can be referred
+to by <code class="docutils literal notranslate"><span class="pre">img.scale[&quot;x&quot;]</span></code> or <a href="#id30"><span class="problematic" id="id31">``</span></a>img.scale.x</p>
+<dl class="field-list simple">
+<dt class="field-odd">Type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>ScaleDict</p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py attribute">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.metadata">
+<span class="sig-name descname"><span class="pre">metadata</span></span><a class="headerlink" href="#impy.arrays.ImgArray.metadata" title="Permalink to this definition">¶</a></dt>
+<dd><p>Metadata tagged to the image.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>dict</p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py attribute">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.source">
+<span class="sig-name descname"><span class="pre">source</span></span><a class="headerlink" href="#impy.arrays.ImgArray.source" title="Permalink to this definition">¶</a></dt>
+<dd><p>Source file of the image.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>Path</p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.affine">
+<span class="sig-name descname"><span class="pre">affine</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">matrix</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rotation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shear</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">translation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefilter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.affine"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.affine" title="Permalink to this definition">¶</a></dt>
+<dd><p>Convert image by Affine transformation. 2D Affine transformation is written as:</p>
+<div class="math notranslate nohighlight">
+\[\begin{split}\begin{bmatrix} y'\\ x' \\1 \end{bmatrix} =
+\begin{bmatrix} A_{00} &amp; A_{01} &amp; A_{02} \\
+                A_{10} &amp; A_{11} &amp; A_{12} \\
+                    0 &amp;      0 &amp;      1  \end{bmatrix}
+                \begin{bmatrix} y \\x\\ 1 \end{bmatrix}\end{split}\]</div>
+<p>and similarly, n-D Affine transformation can be described as (n+1)-D matrix.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>matrix</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
+<li><p><strong>scale</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
+<li><p><strong>rotation</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
+<li><p><strong>shear</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
+<li><p><strong>translation</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>output_shape</strong> (<em>tuple</em><em> of </em><em>int</em><em>, </em><em>optional</em>) – Shape of output array.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Transformed image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.area_closing">
+<span class="sig-name descname"><span class="pre">area_closing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">area</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">64</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.area_closing"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.area_closing" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.area_opening">
+<span class="sig-name descname"><span class="pre">area_opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">area</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">64</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.area_opening"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.area_opening" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.binning">
+<span class="sig-name descname"><span class="pre">binning</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">binsize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_edges</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.binning"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.binning" title="Permalink to this definition">¶</a></dt>
+<dd><p>Binning of images. This function is similar to <code class="docutils literal notranslate"><span class="pre">rescale</span></code> but is strictly
+binned by <span class="math notranslate nohighlight">\(N \times N\)</span> blocks. Also, any numpy functions that accept
+“axis” argument are supported for reduce functions.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>binsize</strong> (<em>int</em><em>, </em><em>default is 2</em>) – Bin size, such as 2x2.</p></li>
+<li><p><strong>method</strong> (<em>str</em><em> or </em><em>callable</em><em>, </em><em>default is numpy.mean</em>) – Reduce function applied to each bin.</p></li>
+<li><p><strong>check_edges</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, only divisible <code class="docutils literal notranslate"><span class="pre">binsize</span></code> is accepted. If False, image is
+cropped at the end to match <cite>binsize</cite>.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Binned image</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.center_of_mass">
+<span class="sig-name descname"><span class="pre">center_of_mass</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.center_of_mass"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.center_of_mass" title="Permalink to this definition">¶</a></dt>
+<dd><p>Calculate the center of mass of the image.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Center of mass. Axes will be the input axes minus <code class="docutils literal notranslate"><span class="pre">dims</span></code>, plus a new axis
+<code class="docutils literal notranslate"><span class="pre">dim</span></code> at the first position, which represents the dimensions of the
+results.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.PropArray" title="impy.arrays.PropArray">PropArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.centroid_sm">
+<span class="sig-name descname"><span class="pre">centroid_sm</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coords</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Coords</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">nDInt</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray"><span class="pre">ImgArray</span></a><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">bool</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">find_sm_kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><span class="pre">MarkerFrame</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.centroid_sm"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.centroid_sm" title="Permalink to this definition">¶</a></dt>
+<dd><p>Calculate positions of particles in subpixel precision using centroid.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>coords</strong> (<a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><em>MarkerFrame</em></a><em> or </em><em>(</em><em>N</em><em>, </em><em>2</em><em>) </em><em>array</em><em>, </em><em>optional</em>) – Coordinates of peaks. If None, this will be determined by find_sm.</p></li>
+<li><p><strong>radius</strong> (<em>int</em><em>, </em><em>default is 4.</em>) – Range to calculate centroids. Rectangular image with size 2r+1 x 2r+1 will be send
+to calculate moments.</p></li>
+<li><p><strong>filt</strong> (<em>callable</em><em>, </em><em>optional</em>) – For every slice <code class="docutils literal notranslate"><span class="pre">sl</span></code>, label is added only when filt(<cite>input</cite>) == True is satisfied.</p></li>
+<li><p><strong>find_sm_kwargs</strong> (<em>keyword arguments</em>) – Parameters passed to <a class="reference internal" href="#impy.arrays.ImgArray.find_sm" title="impy.arrays.ImgArray.find_sm"><code class="xref py py-func docutils literal notranslate"><span class="pre">find_sm()</span></code></a>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Coordinates of peaks.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.ImgArray.find_sm" title="impy.arrays.ImgArray.find_sm"><code class="xref py py-obj docutils literal notranslate"><span class="pre">find_sm</span></code></a>, <code class="xref py py-obj docutils literal notranslate"><span class="pre">refine_sm</span></code></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.clip">
+<span class="sig-name descname"><span class="pre">clip</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">in_range</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">('0%',</span> <span class="pre">'100%')</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.clip"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.clip" title="Permalink to this definition">¶</a></dt>
+<dd><p>Saturate low/high intensity using np.clip().</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>in_range</strong> (<em>two scalar values</em><em>, </em><em>optional</em>) – range of lower/upper limits, by default (0%, 100%).</p>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Clipped image with temporal attribute</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.closing">
+<span class="sig-name descname"><span class="pre">closing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.closing"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.closing" title="Permalink to this definition">¶</a></dt>
+<dd><p>Morphological closing.</p>
+<p>If input is binary image, the running function will automatically switched to
+<code class="docutils literal notranslate"><span class="pre">binary_closing</span></code> to speed up calculation.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.coef_filter">
+<span class="sig-name descname"><span class="pre">coef_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.coef_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.coef_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Coefficient of variance filter.</p>
+<p>For kernel area X, <span class="math notranslate nohighlight">\(\frac{\sqrt{V[X]}}{E[X]}\)</span> is calculated. This filter
+is useful for feature extraction from images with uneven background intensity.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.convex_hull">
+<span class="sig-name descname"><span class="pre">convex_hull</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.convex_hull"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.convex_hull" title="Permalink to this definition">¶</a></dt>
+<dd><p>Compute convex hull image.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Convex hull image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.convolve">
+<span class="sig-name descname"><span class="pre">convolve</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kernel</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.convolve"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.convolve" title="Permalink to this definition">¶</a></dt>
+<dd><p>General linear convolution by running kernel filtering.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>kernel</strong> (<em>array-like</em>) – Convolution kernel.</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Convolved image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.corner_harris">
+<span class="sig-name descname"><span class="pre">corner_harris</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.corner_harris"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.corner_harris" title="Permalink to this definition">¶</a></dt>
+<dd><p>Calculate Harris response image.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
+<li><p><strong>k</strong> (<em>float</em><em>, </em><em>optional</em>) – Sensitivity factor to separate corners from edges, typically in range [0, 0.2].
+Small values of k result in detection of sharp corners.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Harris response</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.corner_peaks">
+<span class="sig-name descname"><span class="pre">corner_peaks</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_distance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">percentile</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">topn</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">inf</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">topn_per_label</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">inf</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exclude_border</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_labels</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><span class="pre">MarkerFrame</span></a></span></span><a class="headerlink" href="#impy.arrays.ImgArray.corner_peaks" title="Permalink to this definition">¶</a></dt>
+<dd><p>Find local corner maxima. Slightly different from peak_local_max.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>min_distance</strong> (<em>int</em><em>, </em><em>default is 1</em>) – Minimum distance allowed for each two peaks. This parameter is slightly
+different from that in <code class="docutils literal notranslate"><span class="pre">skimage.feature.peak_local_max</span></code> because here float
+input is allowed and every time footprint is calculated.</p></li>
+<li><p><strong>percentile</strong> (<em>float</em><em>, </em><em>optional</em>) – Percentile to compute absolute threshold.</p></li>
+<li><p><strong>topn</strong> (<em>int</em><em>, </em><em>optional</em>) – Maximum number of peaks <strong>for each iteration</strong>.</p></li>
+<li><p><strong>topn_per_label</strong> (<em>int</em><em>, </em><em>default is np.inf</em>) – Maximum number of peaks per label.</p></li>
+<li><p><strong>use_labels</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If use self.labels when it exists.</p></li>
+<li><p><strong>{dims}</strong> – </p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>DataFrame with columns same as axes of self. For example, if self.axes is “tcyx” then
+return value has “t”, “c”, “y” and “x” columns, and sub-frame at t=0, c=0 contains all
+the coordinates of corners in the slice at t=0, c=0.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.count_neighbors">
+<span class="sig-name descname"><span class="pre">count_neighbors</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.count_neighbors"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.count_neighbors" title="Permalink to this definition">¶</a></dt>
+<dd><p>Count the number or neighbors of binary images. This function can be used for cross section
+or branch detection. Only works for binary images.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>connectivity</strong> (<em>int</em><em>, </em><em>optional</em>) – Connectivity of pixels. See <code class="docutils literal notranslate"><span class="pre">skimage.measure.label</span></code>.</p></li>
+<li><p><strong>mask</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, only neighbors of pixels that satisfy self==True is returned.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>uint8 array of the number of neighbors.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">skl</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">threshold</span><span class="p">()</span><span class="o">.</span><span class="n">skeletonize</span><span class="p">()</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">edge</span> <span class="o">=</span> <span class="n">skl</span><span class="o">.</span><span class="n">count_neighbors</span><span class="p">()</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">edge</span> <span class="o">==</span> <span class="mi">1</span><span class="p">)</span> <span class="c1"># get coordinates of filament edges.</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">edge</span> <span class="o">&gt;=</span> <span class="mi">3</span><span class="p">)</span> <span class="c1"># get coordinates of filament cross sections.</span>
+</pre></div>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.diameter_closing">
+<span class="sig-name descname"><span class="pre">diameter_closing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">diameter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">8</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.diameter_closing"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.diameter_closing" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.diameter_opening">
+<span class="sig-name descname"><span class="pre">diameter_opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">diameter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">8</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.diameter_opening"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.diameter_opening" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.dilation">
+<span class="sig-name descname"><span class="pre">dilation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.dilation"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.dilation" title="Permalink to this definition">¶</a></dt>
+<dd><p>Morphological dilation. If input is binary image, the running function will automatically switched to
+<code class="docutils literal notranslate"><span class="pre">binary_dilation</span></code> to speed up calculation.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.distance_map">
+<span class="sig-name descname"><span class="pre">distance_map</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.distance_map"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.distance_map" title="Permalink to this definition">¶</a></dt>
+<dd><p>Calculate distance map from binary images.
+For instance, <code class="docutils literal notranslate"><span class="pre">[1,</span> <span class="pre">1,</span> <span class="pre">1,</span> <span class="pre">0,</span> <span class="pre">0,</span> <span class="pre">0,</span> <span class="pre">1,</span> <span class="pre">1,</span> <span class="pre">1]</span></code> will be converted to
+<code class="docutils literal notranslate"><span class="pre">[3,</span> <span class="pre">2,</span> <span class="pre">1,</span> <span class="pre">0,</span> <span class="pre">0,</span> <span class="pre">0,</span> <span class="pre">1,</span> <span class="pre">2,</span> <span class="pre">3]</span></code>. Note that returned array will be float in n-D
+images.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Distance map, the further the brighter</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.dog_filter">
+<span class="sig-name descname"><span class="pre">dog_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">low_sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">high_sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fourier</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.dog_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.dog_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Run Difference of Gaussian filter. This function does not support <cite>update</cite>
+argument because intensity can be negative.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>low_sigma</strong> (<em>scalar</em><em> or </em><em>array</em><em> of </em><em>scalars</em><em>, </em><em>default is 1.</em>) – lower standard deviation(s) of Gaussian.</p></li>
+<li><p><strong>high_sigma</strong> (<em>scalar</em><em> or </em><em>array</em><em> of </em><em>scalars</em><em>, </em><em>default is x1.6</em><em> of </em><em>low_sigma.</em>) – higher standard deviation(s) of Gaussian.</p></li>
+<li><p><strong>fourier</strong> (<em>bool</em><em>, </em><em>default is False</em>) – Whether to run the convolution in Fourier space. This option is useful when the kernel or the image is large.
+Note that discrete Fourier transform assumes that the image is periodic, so that if intensities of the input image are not consecutive at img[0] and img[-1], you may get some artifacts at the boundary.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.doh_filter">
+<span class="sig-name descname"><span class="pre">doh_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.doh_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.doh_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Determinant of Hessian filter. This function does not support <cite>update</cite>
+argument because output has total different scale of intensity.</p>
+<blockquote>
+<div><div class="admonition warning">
+<p class="admonition-title">Warning</p>
+<p>Because in most cases we want to find only bright dots, eigenvalues larger
+than 0 is ignored before computing determinant.</p>
+</div>
+</div></blockquote>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.drift_correction">
+<span class="sig-name descname"><span class="pre">drift_correction</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Coords</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ref</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray"><span class="pre">ImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">zero_ave</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxisLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.drift_correction"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.drift_correction" title="Permalink to this definition">¶</a></dt>
+<dd><p>Drift correction using iterative Affine translation. If translation vectors <code class="docutils literal notranslate"><span class="pre">shift</span></code>
+is not given, then it will be determined using <code class="docutils literal notranslate"><span class="pre">track_drift</span></code> method of ImgArray.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>shift</strong> (<em>DataFrame</em><em> or </em><em>(</em><em>N</em><em>, </em><em>D</em><em>) </em><em>array</em><em>, </em><em>optional</em>) – Translation vectors. If DataFrame, it must have columns named with all the symbols
+contained in <code class="docutils literal notranslate"><span class="pre">dims</span></code>.</p></li>
+<li><p><strong>ref</strong> (<a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray"><em>ImgArray</em></a><em>, </em><em>optional</em>) – The reference n-D image to determine drift, if <code class="docutils literal notranslate"><span class="pre">shift</span></code> was not given.</p></li>
+<li><p><strong>zero_ave</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, average shift will be zero.</p></li>
+<li><p><strong>along</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Along which axis drift will be corrected.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+<li><p><strong>affine_kwargs</strong> – Keyword arguments that will be passed to <code class="docutils literal notranslate"><span class="pre">warp</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Corrected image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<dl>
+<dt>Drift correction of multichannel image using the first channel as the reference.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">drift_correction</span><span class="p">(</span><span class="n">ref</span><span class="o">=</span><span class="n">img</span><span class="p">[</span><span class="s2">&quot;c=0&quot;</span><span class="p">])</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.edge_filter">
+<span class="sig-name descname"><span class="pre">edge_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'sobel'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.edge_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.edge_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Sobel filter. This filter is useful for edge detection.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>method</strong> (<em>str</em><em>, </em><em>{&quot;sobel&quot;</em><em>, </em><em>&quot;farid&quot;</em><em>, </em><em>&quot;scharr&quot;</em><em>, </em><em>&quot;prewitt&quot;}</em><em>, </em><em>default is &quot;sobel&quot;</em>) – Edge operator name.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.edge_grad">
+<span class="sig-name descname"><span class="pre">edge_grad</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'sobel'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">deg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.edge_grad"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.edge_grad" title="Permalink to this definition">¶</a></dt>
+<dd><p>Calculate gradient direction using horizontal and vertical edge operation. Gradient direction
+is the direction with maximum gradient, i.e., intensity increase is largest.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
+<li><p><strong>method</strong> (<em>str</em><em>, </em><em>{&quot;sobel&quot;</em><em>, </em><em>&quot;farid&quot;</em><em>, </em><em>&quot;scharr&quot;</em><em>, </em><em>&quot;prewitt&quot;}</em><em>, </em><em>default is &quot;sobel&quot;</em>) – Edge operator name.</p></li>
+<li><p><strong>deg</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, degree rather than radian is returned.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Phase image with range [-180, 180) if deg==True, otherwise [-pi, pi).</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.PhaseArray" title="impy.arrays.PhaseArray">PhaseArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<ol class="arabic">
+<li><dl>
+<dt>Profile filament orientation distribution using histogram of edge gradient.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">grad</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">edge_grad</span><span class="p">(</span><span class="n">deg</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">plt</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">grad</span><span class="o">.</span><span class="n">ravel</span><span class="p">(),</span> <span class="n">bins</span><span class="o">=</span><span class="mi">100</span><span class="p">)</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</li>
+</ol>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.enhance_contrast">
+<span class="sig-name descname"><span class="pre">enhance_contrast</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.enhance_contrast"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.enhance_contrast" title="Permalink to this definition">¶</a></dt>
+<dd><p>Enhance contrast filter.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Contrast enhanced image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.entropy_filter">
+<span class="sig-name descname"><span class="pre">entropy_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.entropy_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.entropy_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Running entropy filter. This filter is useful for detecting change in background distribution.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.erosion">
+<span class="sig-name descname"><span class="pre">erosion</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.erosion"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.erosion" title="Permalink to this definition">¶</a></dt>
+<dd><p>Morphological erosion.</p>
+<p>If input is binary image, the running function will automatically switched to
+<code class="docutils literal notranslate"><span class="pre">binary_erosion</span></code> to speed up calculation.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.estimate_sigma">
+<span class="sig-name descname"><span class="pre">estimate_sigma</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.estimate_sigma"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.estimate_sigma" title="Permalink to this definition">¶</a></dt>
+<dd><p>Wavelet-based estimation of Gaussian noise.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>squeeze</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True and output can be converted to a scalar, then convert it.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Estimated standard deviation. sigma[“t=0;c=1”] means the estimated value of
+image slice at t=0 and c=1.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.PropArray" title="impy.arrays.PropArray">PropArray</a> or float</p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.fft">
+<span class="sig-name descname"><span class="pre">fft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">FftShape</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'same'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">double_precision</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.fft"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.fft" title="Permalink to this definition">¶</a></dt>
+<dd><p>Fast Fourier transformation. This function returns complex array, which is
+inconpatible with some ImgArray functions.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable</em><em> of </em><em>int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
+- integers: padded or cropped to the specified shape.
+- “square”: padded to smallest 2^N-long square.
+- “same” (default): no padding or cropping.</p></li>
+<li><p><strong>shift</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, call <code class="docutils literal notranslate"><span class="pre">np.fft.fftshift</span></code> in the end.</p></li>
+<li><p><strong>double_precision</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, FFT will be calculated using 64-bit float and 128-bit complex.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>FFT image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.ImgArray.local_dft" title="impy.arrays.ImgArray.local_dft"><code class="xref py py-obj docutils literal notranslate"><span class="pre">local_dft</span></code></a></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.fill_hole">
+<span class="sig-name descname"><span class="pre">fill_hole</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">thr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'otsu'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.fill_hole"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.fill_hole" title="Permalink to this definition">¶</a></dt>
+<dd><p>Filling holes. See skimage’s documents
+<a class="reference external" href="https://scikit-image.org/docs/stable/auto_examples/features_detection/plot_holes_and_peaks.html">here</a>.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>thr</strong> (<em>scalar</em><em> or </em><em>str</em><em>, </em><em>optional</em>) – Threshold (value or method) to apply if image is not binary.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Hole-filled image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.find_corners">
+<span class="sig-name descname"><span class="pre">find_corners</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">nDFloat</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="headerlink" href="#impy.arrays.ImgArray.find_corners" title="Permalink to this definition">¶</a></dt>
+<dd><p>Corner detection using Harris response.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p>
+</dd>
+</dl>
+<dl>
+<dt>k<span class="classifier">float, optional</span></dt><dd><p>Sensitivity factor to separate corners from edges, typically in range [0, 0.2].
+Small values of k result in detection of sharp corners.</p>
+<dl class="simple">
+<dt>dims<span class="classifier">str or int, optional</span></dt><dd><p>Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p>
+</dd>
+</dl>
+</dd>
+</dl>
+<dl class="field-list simple">
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
+<dd class="field-odd"><p>Coordinates of corners. For details see <code class="docutils literal notranslate"><span class="pre">corner_peaks</span></code> method.</p>
+</dd>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
+<dd class="field-even"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.find_sm">
+<span class="sig-name descname"><span class="pre">find_sm</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">nDFloat</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.5</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'dog'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">percentile</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">95</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">topn</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">inf</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exclude_border</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><span class="pre">MarkerFrame</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.find_sm"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.find_sm" title="Permalink to this definition">¶</a></dt>
+<dd><p>Single molecule detection using difference of Gaussian, determinant of Hessian, Laplacian of
+Gaussian or normalized cross correlation method.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>sigma</strong> (<em>float</em><em>, </em><em>optional</em>) – Standard deviation of puncta.</p></li>
+<li><p><strong>method</strong> (<em>str {&quot;dog&quot;</em><em>, </em><em>&quot;doh&quot;</em><em>, </em><em>&quot;log&quot;</em><em>, </em><em>&quot;gaussian&quot;</em><em>, </em><em>&quot;ncc&quot;}</em><em>, </em><em>default is &quot;dog&quot;</em>) – Which filter is used prior to finding local maxima. If “ncc”, a Gaussian particle is used as
+the template image.</p></li>
+<li><p><strong>cutoff</strong> (<em>float</em><em>, </em><em>optional</em>) – Cutoff value of filtered image generated by <cite>method</cite>.</p></li>
+<li><p><strong>percentile</strong> – Passed to <code class="docutils literal notranslate"><span class="pre">peak_local_max()</span></code></p></li>
+<li><p><strong>topn</strong> – Passed to <code class="docutils literal notranslate"><span class="pre">peak_local_max()</span></code></p></li>
+<li><p><strong>exclude_border</strong> – Passed to <code class="docutils literal notranslate"><span class="pre">peak_local_max()</span></code></p></li>
+<li><p><strong>dims</strong> – Passed to <code class="docutils literal notranslate"><span class="pre">peak_local_max()</span></code></p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Peaks in uint16 type.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<p>Track single molecules and view the tracks with napari.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">coords</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">find_sm</span><span class="p">()</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">lnk</span> <span class="o">=</span> <span class="n">coords</span><span class="o">.</span><span class="n">link</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="n">min_dwell</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">ip</span><span class="o">.</span><span class="n">gui</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">ip</span><span class="o">.</span><span class="n">gui</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">lnk</span><span class="p">)</span>
+</pre></div>
+</div>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.ImgArray.centroid_sm" title="impy.arrays.ImgArray.centroid_sm"><code class="xref py py-obj docutils literal notranslate"><span class="pre">centroid_sm</span></code></a>, <code class="xref py py-obj docutils literal notranslate"><span class="pre">refine_sm</span></code></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.flood">
+<span class="sig-name descname"><span class="pre">flood</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">seeds</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Coords</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tolerance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.flood"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.flood" title="Permalink to this definition">¶</a></dt>
+<dd><p>Flood filling with a list of seed points. By repeating skimage’s <code class="docutils literal notranslate"><span class="pre">flood</span></code> function,
+this method can perform segmentation of an image.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>seeds</strong> (<a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><em>MarkerFrame</em></a><em> or </em><em>(</em><em>N</em><em>, </em><em>D</em><em>) </em><em>array-like</em>) – Seed points to start flood filling.</p></li>
+<li><p><strong>connectivity</strong> (<em>int</em><em>, </em><em>optional</em>) – Connectivity of pixels. See <code class="docutils literal notranslate"><span class="pre">skimage.measure.label</span></code>.</p></li>
+<li><p><strong>tolerance</strong> (<em>float</em><em>, </em><em>optional</em>) – Intensity deviation within this value will be filled.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Labeled image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.focus_map">
+<span class="sig-name descname"><span class="pre">focus_map</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.focus_map"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.focus_map" title="Permalink to this definition">¶</a></dt>
+<dd><p>Compute focus map using variance of Laplacian method. yx-plane with higher variance is likely a
+focal plane because sharper image causes higher value of Laplacian on the edges.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>int</em><em>, </em><em>default is 1</em>) – Radius of Laplacian filter’s kernel.</p></li>
+<li><p><strong>{dims}</strong> – </p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Array of variance of Laplacian</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.PropArray" title="impy.arrays.PropArray">PropArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<dl>
+<dt>Get the focus plane from a 3D image.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">score</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">focus_map</span><span class="p">()</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">score</span><span class="o">.</span><span class="n">plot</span><span class="p">()</span>               <span class="c1"># plot the variation of laplacian focus</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">z_focus</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">argmax</span><span class="p">(</span><span class="n">score</span><span class="p">)</span> <span class="c1"># determine the focus plane</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="p">[</span><span class="n">z_focus</span><span class="p">]</span>               <span class="c1"># get the focus plane</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.gabor_angle">
+<span class="sig-name descname"><span class="pre">gabor_angle</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n_sample</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">180</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gamma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">phi</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">deg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.gabor_angle"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.gabor_angle" title="Permalink to this definition">¶</a></dt>
+<dd><p>Calculate filament angles using Gabor filter. For all the candidates of angles, Gabor response is
+calculated, and the strongest response is returned as output array.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>n_sample</strong> (<em>int</em><em>, </em><em>default is 180</em>) – Number of <a href="#id34"><span class="problematic" id="id35">`</span></a>theta`s to calculate. By default, -90, -89, …, 89 degree are calculated.</p></li>
+<li><p><strong>lmd</strong> (<em>float</em><em>, </em><em>default is 5</em>) – Wave length of Gabor kernel. Make sure that the diameter of the objects you want to detect is
+around <cite>lmd/2</cite>.</p></li>
+<li><p><strong>sigma</strong> (<em>float</em><em>, </em><em>default is 2.5</em>) – Standard deviation of Gaussian factor of Gabor kernel.</p></li>
+<li><p><strong>gamma</strong> (<em>float</em><em>, </em><em>default is 1</em>) – Anisotropy of Gabor kernel, i.e. the standard deviation orthogonal to theta will be sigma/gamma.</p></li>
+<li><p><strong>phi</strong> (<em>float</em><em>, </em><em>default is 0</em>) – Phase offset of harmonic factor of Gabor kernel.</p></li>
+<li><p><strong>deg</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, degree rather than radian is returned.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Phase image with range [-90, 90) if deg==True, otherwise [-pi/2, pi/2).</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.ImgArray.hessian_angle" title="impy.arrays.ImgArray.hessian_angle"><code class="xref py py-obj docutils literal notranslate"><span class="pre">hessian_angle</span></code></a></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.gabor_filter">
+<span class="sig-name descname"><span class="pre">gabor_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">gamma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">phi</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_imag</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.gabor_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.gabor_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Make a Gabor kernel and convolve it.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>lmd</strong> (<em>float</em><em>, </em><em>default is 5</em>) – Wave length of Gabor kernel. Make sure that the diameter of the objects you want to detect is
+around <cite>lmd/2</cite>.</p></li>
+<li><p><strong>theta</strong> (<em>float</em><em>, </em><em>default is 0</em>) – Orientation of harmonic factor of Gabor kernel in radian (x-directional if <cite>theta==0</cite>).</p></li>
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
+<li><p><strong>gamma</strong> (<em>float</em><em>, </em><em>default is 1</em>) – Anisotropy of Gabor kernel, i.e. the standard deviation orthogonal to theta will be sigma/gamma.</p></li>
+<li><p><strong>phi</strong> (<em>float</em><em>, </em><em>default is 0</em>) – Phase offset of harmonic factor of Gabor kernel.</p></li>
+<li><p><strong>return_imag</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, a complex image that contains both real and imaginary part of Gabor response is returned.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a> (dtype is float32 or complex64)</p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<dl>
+<dt>Edge Detection using multi-angle Gabor filtering.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">thetas</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">deg2rad</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">45</span><span class="p">,</span> <span class="mi">90</span><span class="p">,</span> <span class="mi">135</span><span class="p">])</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">out</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="mi">4</span><span class="p">,)</span><span class="o">+</span><span class="n">img</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">theta</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">thetas</span><span class="p">):</span>
+<span class="gp">&gt;&gt;&gt; </span>    <span class="n">out</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">gabor_filter</span><span class="p">(</span><span class="n">theta</span><span class="o">=</span><span class="n">theta</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">out</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.gauss_correction">
+<span class="sig-name descname"><span class="pre">gauss_correction</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ref</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0625</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">median_radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">15</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.gauss_correction"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.gauss_correction" title="Permalink to this definition">¶</a></dt>
+<dd><p>Correct unevenly distributed excitation light using Gaussian fitting. This method subtracts
+background intensity at the same time. If input image is uint, then output value under 0 will
+replaced with 0. If you want to quantify background, it is necessary to first convert input
+image to float image.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>ref</strong> (ImgArray, default is <cite>self</cite>.) – Reference image to estimate background.</p></li>
+<li><p><strong>scale</strong> (<em>float</em><em>, </em><em>default is 1/16.</em>) – Scale of rough image (to speed up fitting).</p></li>
+<li><p><strong>median_radius</strong> (<em>float</em><em>, </em><em>default is 15.</em>) – Radius of median prefilter’s kernel. If smaller than 1, prefiltering will be skipped.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Corrected and background subtracted image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<p>1. When input image has “ptcyx”-axes, and you want to estimate the background intensity
+for each channel by averaging all the positions and times.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img_cor</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">gauss_correction</span><span class="p">(</span><span class="n">ref</span><span class="o">=</span><span class="n">img</span><span class="o">.</span><span class="n">proj</span><span class="p">(</span><span class="s2">&quot;pt&quot;</span><span class="p">))</span>
+</pre></div>
+</div>
+<p>2. When input image has “ptcyx”-axes, and you want to estimate the background intensity
+for each channel and time point by averaging all the positions.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img_cor</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">gauss_correction</span><span class="p">(</span><span class="n">ref</span><span class="o">=</span><span class="n">img</span><span class="o">.</span><span class="n">proj</span><span class="p">(</span><span class="s2">&quot;p&quot;</span><span class="p">))</span>
+</pre></div>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.gauss_sm">
+<span class="sig-name descname"><span class="pre">gauss_sm</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coords</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.5</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filt</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">percentile</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">95</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_all</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#impy.arrays.ImgArray.gauss_sm" title="Permalink to this definition">¶</a></dt>
+<dd><p>Calculate positions of particles in subpixel precision using Gaussian fitting.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>coords</strong> (<a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><em>MarkerFrame</em></a><em> or </em><em>(</em><em>N</em><em>, </em><em>2</em><em>) </em><em>array</em><em>, </em><em>optional</em>) – Coordinates of peaks. If None, this will be determined by find_sm.</p></li>
+<li><p><strong>radius</strong> (<em>int</em><em>, </em><em>default is 4.</em>) – Fitting range. Rectangular image with size 2r+1 x 2r+1 will be send to Gaussian
+fitting function.</p></li>
+<li><p><strong>sigma</strong> (<em>float</em><em>, </em><em>default is 1.5</em>) – Expected standard deviation of particles.</p></li>
+<li><p><strong>filt</strong> (<em>callable</em><em>, </em><em>optional</em>) – For every slice <cite>sl</cite>, label is added only when filt(<cite>input</cite>) == True is satisfied.
+This discrimination is conducted before Gaussian fitting so that stringent filter
+will save time.</p></li>
+<li><p><strong>percentile</strong> – Passed to peak_local_max()</p></li>
+<li><p><strong>dims</strong> – Passed to peak_local_max()</p></li>
+<li><p><strong>return_all</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, fitting results are all returned as Frame Dict.</p></li>
+<li><p><strong>{dims}</strong> – </p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p><ul class="simple">
+<li><p><em>MarkerFrame, if return_all == False</em> – Gaussian centers.</p></li>
+<li><p><em>DataDict with keys {means, sigmas, errors}, if return_all == True</em> – Dictionary that contains means, standard deviations and fitting errors.</p></li>
+</ul>
+</p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.gaussfit">
+<span class="sig-name descname"><span class="pre">gaussfit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0625</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Powell'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'yx'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.gaussfit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.gaussfit" title="Permalink to this definition">¶</a></dt>
+<dd><p>Fit the image to 2-D Gaussian background.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>scale</strong> (<em>float</em><em>, </em><em>default is 1/16.</em>) – Scale of rough image (to speed up fitting).</p></li>
+<li><p><strong>p0</strong> (<em>sequence</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Initial parameters.</p></li>
+<li><p><strong>method</strong> (<em>str</em><em>, </em><em>optional</em>) – Fitting method. See <cite>scipy.optimize.minimize</cite>.</p></li>
+<li><p><strong>mask</strong> (<em>np.ndarray</em><em>, </em><em>optional</em><em>,</em>) – If given, ignore the True region from fitting.</p></li>
+<li><p><strong>{dims}</strong> – </p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Fit image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.gaussian_filter">
+<span class="sig-name descname"><span class="pre">gaussian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fourier</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.gaussian_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.gaussian_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Run Gaussian filter (Gaussian blur).</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
+<li><p><strong>fourier</strong> (<em>bool</em><em>, </em><em>default is False</em>) – Whether to run the convolution in Fourier space. This option is useful when the kernel or the image is large.
+Note that discrete Fourier transform assumes that the image is periodic, so that if intensities of the input image are not consecutive at img[0] and img[-1], you may get some artifacts at the boundary.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.glcm_props">
+<span class="sig-name descname"><span class="pre">glcm_props</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">distances</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">angles</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">properties</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bins</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rescale_max</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.glcm_props"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.glcm_props" title="Permalink to this definition">¶</a></dt>
+<dd><p>Compute properties of “Gray Level Coocurrence Matrix”. This will take long time
+because of pure Python for-loop.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>distances</strong> (<em>array_like</em>) – List of pixel pair distance offsets.</p></li>
+<li><p><strong>angles</strong> (<em>array_like</em>) – List of pixel pair angles in radians.</p></li>
+<li><p><strong>radius</strong> (<em>int</em>) – Window radius.</p></li>
+<li><p><strong>properties</strong> (<em>tuple</em><em> of </em><em>str</em>) – contrast, dissimilarity, homogeneity, energy, mean, std, asm, max, entropy</p></li>
+<li><p><strong>bins</strong> (<em>int</em><em>, </em><em>optional</em>) – Number of bins.</p></li>
+<li><p><strong>rescale_max</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, the contrast of the input image is maximized by multiplying an integer.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>GLCM with additional axes “da”, where “d” means distance and “a” means angle.
+If input image has “tzyx” axes then output will have “tzd&lt;yx” axes.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.html#impy.collections.DataDict" title="impy.collections.DataDict">DataDict</a> of <a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<dl>
+<dt>Plot GLCM’s IDM and ASM images</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">out</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">glcm_props</span><span class="p">([</span><span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="mi">3</span><span class="p">,</span> <span class="n">properties</span><span class="o">=</span><span class="p">(</span><span class="s2">&quot;idm&quot;</span><span class="p">,</span><span class="s2">&quot;asm&quot;</span><span class="p">))</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">out</span><span class="o">.</span><span class="n">idm</span><span class="p">[</span><span class="s2">&quot;d=0;&lt;=0&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">imshow</span><span class="p">()</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">out</span><span class="o">.</span><span class="n">asm</span><span class="p">[</span><span class="s2">&quot;d=0;&lt;=0&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">imshow</span><span class="p">()</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.hessian_angle">
+<span class="sig-name descname"><span class="pre">hessian_angle</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">deg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.hessian_angle"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.hessian_angle" title="Permalink to this definition">¶</a></dt>
+<dd><p>Calculate filament angles using Hessian’s eigenvectors.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
+<li><p><strong>deg</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, returned array will be in degree. Otherwise, radian will be the unit
+of angle.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Phase image with range [-90, 90] if <code class="docutils literal notranslate"><span class="pre">deg==True</span></code>, otherwise [-pi/2, pi/2].</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.ImgArray.gabor_angle" title="impy.arrays.ImgArray.gabor_angle"><code class="xref py py-obj docutils literal notranslate"><span class="pre">gabor_angle</span></code></a></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.hessian_eig">
+<span class="sig-name descname"><span class="pre">hessian_eig</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.hessian_eig"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.hessian_eig" title="Permalink to this definition">¶</a></dt>
+<dd><p>Calculate Hessian’s eigenvalues and eigenvectors.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Arrays of eigenvalues and eigenvectors. The axis <code class="docutils literal notranslate"><span class="pre">&quot;base&quot;</span></code> denotes the index of
+eigenvalues. l=0 means the smallest eigenvalue. <code class="docutils literal notranslate"><span class="pre">&quot;dim&quot;</span></code> denotes the index of
+spatial dimensions. For 3D image, dim=0 means z-element of an eigenvector.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>ImgArray and ImgArray</p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.hessian_eigval">
+<span class="sig-name descname"><span class="pre">hessian_eigval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.hessian_eigval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.hessian_eigval" title="Permalink to this definition">¶</a></dt>
+<dd><p>Calculate Hessian’s eigenvalues for each image.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Array of eigenvalues. The axis <code class="docutils literal notranslate"><span class="pre">&quot;base&quot;</span></code> denotes the index of eigenvalues.
+l=0 means the smallest eigenvalue.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<dl>
+<dt>Extract filament</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">eig</span> <span class="o">=</span> <span class="o">-</span><span class="n">img</span><span class="o">.</span><span class="n">hessian_eigval</span><span class="p">()[</span><span class="n">ip</span><span class="o">.</span><span class="n">slicer</span><span class="o">.</span><span class="n">base</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">eig</span><span class="p">[</span><span class="n">eig</span><span class="o">&lt;</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.highpass_filter">
+<span class="sig-name descname"><span class="pre">highpass_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.highpass_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.highpass_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Butterworth high-pass filter.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>cutoff</strong> (<em>float</em><em> or </em><em>array-like</em><em>, </em><em>default is 0.2</em>) – Cutoff frequency.</p></li>
+<li><p><strong>order</strong> (<em>float</em><em>, </em><em>default is 2</em>) – Steepness of cutoff.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.ifft">
+<span class="sig-name descname"><span class="pre">ifft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">real</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">double_precision</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.ifft"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.ifft" title="Permalink to this definition">¶</a></dt>
+<dd><p>Fast Inverse Fourier transformation. Complementary function with <cite>fft()</cite>.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>real</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, only the real part is returned.</p></li>
+<li><p><strong>shift</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, call <code class="docutils literal notranslate"><span class="pre">np.fft.ifftshift</span></code> at the first.</p></li>
+<li><p><strong>double_precision</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, FFT will be calculated using 64-bit float and 128-bit complex.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>IFFT image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.inpaint">
+<span class="sig-name descname"><span class="pre">inpaint</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mean'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'biharmonic'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'biharmonic'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.inpaint"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.inpaint" title="Permalink to this definition">¶</a></dt>
+<dd><p>Image inpainting.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>mask</strong> (<em>np.ndarray</em>) – Mask image. The True region will be inpainted.</p></li>
+<li><p><strong>method</strong> (<em>&quot;mean&quot;</em><em> or </em><em>&quot;biharmonic&quot;</em><em>, </em><em>default is &quot;biharmonic&quot;</em>) – Inpainting method.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Inpainted image of same data type.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.iradon">
+<span class="sig-name descname"><span class="pre">iradon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degrees</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">central_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'y'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">degree_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">height_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">height</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'hamming'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.iradon"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.iradon" title="Permalink to this definition">¶</a></dt>
+<dd><p>Inverse Radon transformation (weighted back projection) of a tile series.</p>
+<p>Input array must be a tilt series of 1D or 2D images. They are back-
+projected into a 2D or 3D image with arbitrary height.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>degrees</strong> (<em>sequence</em><em> of </em><em>float</em>) – Projection angles in degree. Length must match the length of the degree
+axis of the input image.</p></li>
+<li><p><strong>central_axis</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Axis parallel to the rotation axis.</p></li>
+<li><p><strong>degree_axis</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Axis of rotation degree. By default, the first axis will be used.</p></li>
+<li><p><strong>height_axis</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Axis that will be used to label the new axis after reconstruction. For
+instance, if input image has axes <code class="docutils literal notranslate"><span class="pre">[&quot;degree&quot;,</span> <span class="pre">&quot;y&quot;,</span> <span class="pre">&quot;x&quot;]</span></code> and
+<code class="docutils literal notranslate"><span class="pre">height_axis=&quot;z&quot;</span></code> then reconstructed image will have axes
+<code class="docutils literal notranslate"><span class="pre">[&quot;z&quot;,</span> <span class="pre">&quot;y&quot;,</span> <span class="pre">&quot;x&quot;]</span></code>. By default, “y” will be used for 2D input or “z” for
+3D input.</p></li>
+<li><p><strong>height</strong> (<em>int</em><em>, </em><em>optional</em>) – Height of reconstruction. By default, size equal to the axis perpendicular
+to the rotation axis will be used.</p></li>
+<li><p><strong>window</strong> (<em>str</em><em>, </em><em>default is &quot;hamming&quot;</em>) – Window function that will be applied to the Fourier domain along the axis
+perpendicular to the rotation axis.</p></li>
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Reconstruction.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.ImgArray.radon" title="impy.arrays.ImgArray.radon"><code class="xref py py-obj docutils literal notranslate"><span class="pre">radon</span></code></a></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.kalman_filter">
+<span class="sig-name descname"><span class="pre">kalman_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">gain</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">noise_var</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'t'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.kalman_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.kalman_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Kalman filter for image smoothing. This function is same as “Kalman Stack Filter” in ImageJ but support
+batch processing. This filter is useful for preprocessing of particle tracking.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>gain</strong> (<em>float</em><em>, </em><em>default is 0.8</em>) – Filter gain.</p></li>
+<li><p><strong>noise_var</strong> (<em>float</em><em>, </em><em>default is 0.05</em>) – Initial estimate of noise variance.</p></li>
+<li><p><strong>along</strong> (<em>str</em><em>, </em><em>default is &quot;t&quot;</em>) – Which axis will be the time axis.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.label_threshold">
+<span class="sig-name descname"><span class="pre">label_threshold</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">thr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">ThreasholdMethod</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'otsu'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">bool</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.Label" title="impy.arrays.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.label_threshold"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.label_threshold" title="Permalink to this definition">¶</a></dt>
+<dd><p>Make labels with threshold(). Be sure that keyword argument <code class="docutils literal notranslate"><span class="pre">dims</span></code> can be
+different (in most cases for &gt;4D images) between threshold() and label().
+In this function, both function will have the same <code class="docutils literal notranslate"><span class="pre">dims</span></code> for simplicity.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>thr</strong> (<em>float</em><em> or </em><em>str</em><em> or </em><em>None</em><em>, </em><em>optional</em>) – Threshold value, or thresholding algorithm.</p></li>
+<li><p><strong>{dims}</strong> – </p></li>
+<li><p><strong>**kwargs</strong> – Keyword arguments that will passed to function indicated in ‘method’.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Newly created label.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.Label" title="impy.arrays.Label">Label</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.laplacian_filter">
+<span class="sig-name descname"><span class="pre">laplacian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.laplacian_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.laplacian_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Edge detection using Laplacian filter. Kernel is made by <cite>skimage</cite>’s function.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>int</em><em>, </em><em>default is 1</em>) – Radius of kernel. Shape of kernel will be (2*radius+1, 2*radius+1).</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.lbp">
+<span class="sig-name descname"><span class="pre">lbp</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">12</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'default'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'ror'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'uniform'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'var'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'default'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.lbp"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.lbp" title="Permalink to this definition">¶</a></dt>
+<dd><p>Local binary pattern feature extraction.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>p</strong> (<em>int</em><em>, </em><em>default is 12</em>) – Number of circular neighbors</p></li>
+<li><p><strong>radius</strong> (<em>int</em><em>, </em><em>default is 1</em>) – Radius of neighbours.</p></li>
+<li><p><strong>method</strong> (<em>str</em><em>, </em><em>optional</em>) – Method to determined the pattern.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Local binary pattern image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.local_dft">
+<span class="sig-name descname"><span class="pre">local_dft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Slicer</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">double_precision</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.local_dft"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.local_dft" title="Permalink to this definition">¶</a></dt>
+<dd><p>Local discrete Fourier transformation (DFT). This function will be useful
+for Fourier transformation of small region of an image with a certain
+factor of up-sampling. In general FFT takes <span class="math notranslate nohighlight">\(O(N\log{N})\)</span> time, much
+faster compared to normal DFT (<span class="math notranslate nohighlight">\(O(N^2)\)</span>). However, If you are
+interested in certain region of Fourier space, you don’t have to calculate
+all the spectra. In this case DFT is faster and less memory comsuming.</p>
+<blockquote>
+<div><div class="admonition warning">
+<p class="admonition-title">Warning</p>
+<p>The result of <code class="docutils literal notranslate"><span class="pre">local_dft</span></code> will <strong>NOT</strong> be shifted with
+<code class="docutils literal notranslate"><span class="pre">np.fft.fftshift</span></code> because in general the center of arrays are
+unknown. Also, it is easier to understand <cite>x=0</cite> corresponds to the
+center.</p>
+</div>
+</div></blockquote>
+<p>Even whole spectrum is returned, <code class="docutils literal notranslate"><span class="pre">local_dft</span></code> may be faster than FFT with
+small and/or non-FFT-friendly shaped image.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>key</strong> (<em>str</em>) – Key string that specify region to DFT, such as “y=-50:10;x=:80”. With
+upsampled spectra, keys corresponds to the coordinate <strong>before</strong>
+up-sampling. If you want certain region, say “x=10:20”, this value
+will not change with different <code class="docutils literal notranslate"><span class="pre">upsample_factor</span></code>.</p></li>
+<li><p><strong>upsample_factor</strong> (<em>int</em><em> or </em><em>array</em><em> of </em><em>int</em><em>, </em><em>default is 1</em>) – Up-sampling factor. For instance, when <code class="docutils literal notranslate"><span class="pre">upsample_factor=10</span></code> a single
+pixel will be expanded to 10 pixels.</p></li>
+<li><p><strong>double_precision</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, FFT will be calculated using 64-bit float and 128-bit complex.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>DFT output.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.ImgArray.fft" title="impy.arrays.ImgArray.fft"><code class="xref py py-obj docutils literal notranslate"><span class="pre">fft</span></code></a></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.local_power_spectra">
+<span class="sig-name descname"><span class="pre">local_power_spectra</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Slicer</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">double_precision</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.local_power_spectra"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.local_power_spectra" title="Permalink to this definition">¶</a></dt>
+<dd><p>Return local n-D power spectra of images. See <code class="docutils literal notranslate"><span class="pre">local_dft</span></code>.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>key</strong> (<em>str</em>) – Key string that specify region to DFT, such as “y=-50:10;x=:80”. With Upsampled spectra, keys
+corresponds to the coordinate <strong>before</strong> up-sampling. If you want certain region, say “x=10:20”,
+this value will not change with different <code class="docutils literal notranslate"><span class="pre">upsample_factor</span></code>.</p></li>
+<li><p><strong>upsample_factor</strong> (<em>int</em><em> or </em><em>array</em><em> of </em><em>int</em><em>, </em><em>default is 1</em>) – Up-sampling factor. For instance, when <code class="docutils literal notranslate"><span class="pre">upsample_factor=10</span></code> a single pixel will be expanded to
+10 pixels.</p></li>
+<li><p><strong>norm</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, maximum value of power spectra is adjusted to 1.</p></li>
+<li><p><strong>double_precision</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, FFT will be calculated using 64-bit float and 128-bit complex.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Power spectra</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.ImgArray.power_spectra" title="impy.arrays.ImgArray.power_spectra"><code class="xref py py-obj docutils literal notranslate"><span class="pre">power_spectra</span></code></a></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.log_filter">
+<span class="sig-name descname"><span class="pre">log_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.log_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.log_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Laplacian of Gaussian filter.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.lowpass_conv_filter">
+<span class="sig-name descname"><span class="pre">lowpass_conv_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.lowpass_conv_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.lowpass_conv_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Butterworth low-pass filter in real space. Butterworth kernel is created first using inverse
+Fourier transform of weight function.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>cutoff</strong> (<em>float</em><em> or </em><em>array-like</em><em>, </em><em>default is 0.2</em>) – Cutoff frequency.</p></li>
+<li><p><strong>order</strong> (<em>float</em><em>, </em><em>default is 2</em>) – Steepness of cutoff.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.lowpass_filter">
+<span class="sig-name descname"><span class="pre">lowpass_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.lowpass_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.lowpass_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Butterworth low-pass filter.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>cutoff</strong> (<em>float</em><em> or </em><em>array-like</em><em>, </em><em>default is 0.2</em>) – Cutoff frequency.</p></li>
+<li><p><strong>order</strong> (<em>float</em><em>, </em><em>default is 2</em>) – Steepness of cutoff.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.lucy">
+<span class="sig-name descname"><span class="pre">lucy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">niter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1e-05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.lucy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.lucy" title="Permalink to this definition">¶</a></dt>
+<dd><p>Deconvolution of N-dimensional image, using Richardson-Lucy’s algorithm.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>psf</strong> (<em>ndarray</em><em> or </em><em>callable</em>) – Point spread function. If a function is given, <cite>psf(shape)</cite> will be
+called to generate the PSF.</p></li>
+<li><p><strong>niter</strong> (<em>int</em><em>, </em><em>default is 50.</em>) – Number of iterations.</p></li>
+<li><p><strong>eps</strong> (<em>float</em><em>, </em><em>default is 1e-5</em>) – During deconvolution, division by small values in the convolve image
+of estimation and PSF may cause divergence. Therefore, division by
+values under <cite>eps</cite> is substituted to zero.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Deconvolved image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.ImgArray.lucy_tv" title="impy.arrays.ImgArray.lucy_tv"><code class="xref py py-obj docutils literal notranslate"><span class="pre">lucy_tv</span></code></a>, <a class="reference internal" href="#impy.arrays.ImgArray.wiener" title="impy.arrays.ImgArray.wiener"><code class="xref py py-obj docutils literal notranslate"><span class="pre">wiener</span></code></a></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.lucy_tv">
+<span class="sig-name descname"><span class="pre">lucy_tv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_iter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tol</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1e-05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.lucy_tv"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.lucy_tv" title="Permalink to this definition">¶</a></dt>
+<dd><blockquote>
+<div><p>Deconvolution of N-dimensional image, using Richardson-Lucy’s algorithm with
+total variance regularization (so called RL-TV algorithm). The TV regularization
+factor at pixel position <span class="math notranslate nohighlight">\(x\)</span>, <span class="math notranslate nohighlight">\(F_{reg}(x)\)</span>, is calculated as:</p>
+<div class="math notranslate nohighlight">
+\[F_{reg}(x) = \frac{1}{1-\lambda \cdot div(\frac{grad(I(x)}{|grad(I(x))|})}\]</div>
+<p>(<span class="math notranslate nohighlight">\(I(x)\)</span>: image, <span class="math notranslate nohighlight">\(\lambda\)</span>: constant)</p>
+<p>and this factor is multiplied for every estimation made in each iteration.</p>
+<dl>
+<dt>psf<span class="classifier">ndarray or callable</span></dt><dd><p>Point spread function. If a function is given, <cite>psf(shape)</cite> will be
+called to generate the PSF.</p>
+</dd>
+<dt>max_iter<span class="classifier">int, default is 50.</span></dt><dd><p>Maximum number of iterations.</p>
+</dd>
+<dt>lmd<span class="classifier">float, default is 1e-3</span></dt><dd><p>The constant lambda of TV regularization factor.</p>
+</dd>
+<dt>tol<span class="classifier">float, default is 1e-3</span></dt><dd><p>Iteration stops if regularized absolute summation is lower than this
+value.</p>
+<p>:math:<a href="#id37"><span class="problematic" id="id38">`</span></a>frac{sum_{x}|I’(x) - I(x)|}</p>
+</dd>
+</dl>
+</div></blockquote>
+<p>{sum_{x}|I(x)|}`</p>
+<blockquote>
+<div><blockquote>
+<div><p>(<span class="math notranslate nohighlight">\(I'(x)\)</span>: estimation of <span class="math notranslate nohighlight">\(k+1\)</span>-th iteration, <span class="math notranslate nohighlight">\(I(x)\)</span>:
+estimation of <span class="math notranslate nohighlight">\(k\)</span>-th iteration)</p>
+</div></blockquote>
+<dl class="simple">
+<dt>eps<span class="classifier">float, default is 1e-5</span></dt><dd><p>During deconvolution, division by small values in the convolve image of
+estimation and PSF may cause divergence. Therefore, division by values
+under <code class="docutils literal notranslate"><span class="pre">eps</span></code> is substituted to zero.</p>
+</dd>
+<dt>dims<span class="classifier">str or int, optional</span></dt><dd><p>Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p>
+</dd>
+<dt>update<span class="classifier">bool, default is False</span></dt><dd><p>If True, input itself is updated to the output.</p>
+</dd>
+</dl>
+<dl class="simple">
+<dt>ImgArray</dt><dd><p>Deconvolved image.</p>
+</dd>
+</dl>
+<ul class="simple">
+<li><p>Dey, N., Blanc-Féraud, L., Zimmer, C., Roux, P., Kam, Z., Olivo-Marin, J. C.,
+&amp; Zerubia, J. (2004). 3D microscopy deconvolution using Richardson-Lucy algorithm
+with total variation regularization (Doctoral dissertation, INRIA).</p></li>
+</ul>
+<p>lucy
+wiener</p>
+</div></blockquote>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.mean_filter">
+<span class="sig-name descname"><span class="pre">mean_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.mean_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.mean_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Mean filter. Kernel is filled with same values.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.median_filter">
+<span class="sig-name descname"><span class="pre">median_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.median_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.median_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Running multi-dimensional median filter.</p>
+<p>This filter is useful for deleting outliers generated by noise.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.ncc_filter">
+<span class="sig-name descname"><span class="pre">ncc_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="pre">template:</span> <span class="pre">~numpy.ndarray,</span> <span class="pre">mode:</span> <span class="pre">str</span> <span class="pre">=</span> <span class="pre">'constant',</span> <span class="pre">cval:</span> <span class="pre">float</span> <span class="pre">|</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">~typing.Callable[[~numpy.ndarray],</span> <span class="pre">float]</span> <span class="pre">=</span> <span class="pre">&lt;function</span> <span class="pre">mean&gt;,</span> <span class="pre">*,</span> <span class="pre">dims:</span> <span class="pre">~typing.Sequence[str</span> <span class="pre">|</span> <span class="pre">~impy.axes._axis.Axis]</span> <span class="pre">|</span> <span class="pre">int</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.ncc_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.ncc_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Template matching using normalized cross correlation (NCC) method. This function is basically
+identical to that in <cite>skimage.feature</cite>, but is optimized for batch processing and improved
+readability.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>template</strong> (<em>np.ndarray</em>) – Template image. Must be 2 or 3 dimensional.</p></li>
+<li><p><strong>{mode}</strong> – </p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>optional</em>) – Background intensity. If not given, it will calculated as the mean value of
+the original image.</p></li>
+<li><p><strong>{dims}</strong> – </p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Response image with values between -1 and 1.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.opening">
+<span class="sig-name descname"><span class="pre">opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.opening"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.opening" title="Permalink to this definition">¶</a></dt>
+<dd><p>Morphological opening. If input is binary image, the running function will automatically switched to
+<code class="docutils literal notranslate"><span class="pre">binary_opening</span></code> to speed up calculation.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.pad">
+<span class="sig-name descname"><span class="pre">pad</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pad_width</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.pad"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.pad" title="Permalink to this definition">¶</a></dt>
+<dd><p>Pad image only for spatial dimensions.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>pad_width</strong> – See documentation of np.pad().</p></li>
+<li><p><strong>mode</strong> – See documentation of np.pad().</p></li>
+<li><p><strong>**kwargs</strong> – See documentation of np.pad().</p></li>
+<li><p><strong>dims</strong> (<em>int</em><em> or </em><em>str</em><em>, </em><em>optional</em>) – Which dimension to pad.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Padded image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<p>Suppose <code class="docutils literal notranslate"><span class="pre">img</span></code> has zyx-axes.</p>
+<ol class="arabic">
+<li><dl>
+<dt>Padding 5 pixels in zyx-direction:</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">pad</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</li>
+<li><dl>
+<dt>Padding 5 pixels in yx-direction:</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">pad</span><span class="p">(</span><span class="mi">5</span><span class="p">,</span> <span class="n">dims</span><span class="o">=</span><span class="s2">&quot;yx&quot;</span><span class="p">)</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</li>
+<li><dl>
+<dt>Padding 5 pixels in yx-direction and 2 pixels in z-direction:</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">pad</span><span class="p">([(</span><span class="mi">5</span><span class="p">,</span><span class="mi">5</span><span class="p">),</span> <span class="p">(</span><span class="mi">4</span><span class="p">,</span><span class="mi">4</span><span class="p">),</span> <span class="p">(</span><span class="mi">4</span><span class="p">,</span><span class="mi">4</span><span class="p">)])</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</li>
+<li><dl>
+<dt>Padding 10 pixels in z-(-)-direction and 5 pixels in z-(+)-direction.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">pad</span><span class="p">([(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">5</span><span class="p">)],</span> <span class="n">dims</span><span class="o">=</span><span class="s2">&quot;z&quot;</span><span class="p">)</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</li>
+</ol>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.pad_defocus">
+<span class="sig-name descname"><span class="pre">pad_defocus</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kernel</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">depth</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">width</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">6</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.pad_defocus"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.pad_defocus" title="Permalink to this definition">¶</a></dt>
+<dd><p>Make a z-directional padded image by defocusing the original image. This padding is
+useful when applying FFT to a 3D image.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>kernel</strong> (<em>0-</em><em>, </em><em>1-</em><em> or </em><em>3-dimensional array.</em>) – If 0- (scalar) or 1-dimensional array was given, this is interpreted as standard
+deviation of Gaussian kernel. If 3-dimensional array was given, this is directly
+used as convolution kernel. Other dimension will raise ValueError.</p></li>
+<li><p><strong>depth</strong> (<em>int</em><em>, </em><em>default is 3</em>) – Depth of defocusing. For an image with z-axis size L, then output image will have
+size L + 2*depth.</p></li>
+<li><p><strong>width</strong> (<em>int</em><em>, </em><em>default is 6</em>) – Width of defocusing. For an image with yx-shape (M, N), then output image will have
+shape (M * 2*width, N + 2*width).</p></li>
+<li><p><strong>bg</strong> (<em>float</em><em>, </em><em>optional</em>) – Background intensity. If not given, it will calculated as the minimum value of
+the original image.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Padded image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<p>depth = 2</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="o">----|</span>   <span class="o">|----|</span> <span class="n">o</span> <span class="o">|--</span>     <span class="n">o</span> <span class="o">...</span> <span class="n">center</span> <span class="n">of</span> <span class="n">kernel</span>
+<span class="o">----|</span> <span class="n">o</span> <span class="o">|----|</span>   <span class="o">|--</span>
+<span class="o">++++|</span>   <span class="o">|++++|</span><span class="n">___</span><span class="o">|++</span>  <span class="o">&lt;-</span> <span class="n">the</span> <span class="n">upper</span> <span class="n">edge</span> <span class="n">of</span> <span class="n">original</span> <span class="n">image</span>
+<span class="o">++++|</span><span class="n">___</span><span class="o">|+++++++++++</span>
+</pre></div>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.peak_local_max">
+<span class="sig-name descname"><span class="pre">peak_local_max</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_distance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">percentile</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">topn</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">inf</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">topn_per_label</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">inf</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">exclude_border</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_labels</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><span class="pre">MarkerFrame</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.peak_local_max"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.peak_local_max" title="Permalink to this definition">¶</a></dt>
+<dd><p>Find local maxima. This algorithm corresponds to ImageJ’s ‘Find Maxima’ but is more flexible.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>min_distance</strong> (<em>float</em><em>, </em><em>default is 1.0</em>) – Minimum distance allowed for each two peaks. This parameter is slightly
+different from that in <code class="docutils literal notranslate"><span class="pre">skimage.feature.peak_local_max</span></code> because here float
+input is allowed and every time footprint is calculated.</p></li>
+<li><p><strong>percentile</strong> (<em>float</em><em>, </em><em>optional</em>) – Percentile to compute absolute threshold.</p></li>
+<li><p><strong>topn</strong> (<em>int</em><em>, </em><em>optional</em>) – Maximum number of peaks <strong>for each iteration</strong>.</p></li>
+<li><p><strong>topn_per_label</strong> (<em>int</em><em>, </em><em>default is np.inf</em>) – Maximum number of peaks per label.</p></li>
+<li><p><strong>use_labels</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If use self.labels when it exists.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>DataFrame with columns same as axes of self. For example, if self.axes is “tcyx” then
+return value has “t”, “c”, “y” and “x” columns, and sub-frame at t=0, c=0 contains all
+the coordinates of peaks in the slice at t=0, c=0.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.power_spectra">
+<span class="sig-name descname"><span class="pre">power_spectra</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">FftShape</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'same'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">zero_norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">double_precision</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.power_spectra"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.power_spectra" title="Permalink to this definition">¶</a></dt>
+<dd><p>Return n-D power spectra of images, which is defined as:</p>
+<div class="math notranslate nohighlight">
+\[P = Re(F[I_{img}])^2 + Im(F[I_{img}])^2\]</div>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable</em><em> of </em><em>int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
+- integers: padded or cropped to the specified shape.
+- “square”: padded to smallest 2^N-long square.
+- “same” (default): no padding or cropping.</p></li>
+<li><p><strong>norm</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, maximum value of power spectra is adjusted to 1.</p></li>
+<li><p><strong>double_precision</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, FFT will be calculated using 64-bit float and 128-bit complex.</p></li>
+<li><p><strong>shift</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, call <code class="docutils literal notranslate"><span class="pre">np.fft.fftshift</span></code> at the first.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Power spectra</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.ImgArray.local_power_spectra" title="impy.arrays.ImgArray.local_power_spectra"><code class="xref py py-obj docutils literal notranslate"><span class="pre">local_power_spectra</span></code></a></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.proj">
+<span class="sig-name descname"><span class="pre">proj</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.proj"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.proj" title="Permalink to this definition">¶</a></dt>
+<dd><p>Projection along any axis.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>axis</strong> (<em>str</em><em>, </em><em>optional</em>) – Along which axis projection will be calculated. If None, most plausible one will be chosen.</p></li>
+<li><p><strong>method</strong> (<em>str</em><em> or </em><em>callable</em><em>, </em><em>default is mean-projection.</em>) – Projection method. If str is given, it will converted to numpy function.</p></li>
+<li><p><strong>mask</strong> (<em>array-like</em><em>, </em><em>optional</em>) – If provided, input image will be converted to np.ma.array and <code class="docutils literal notranslate"><span class="pre">method</span></code> will also be interpreted
+as an masked functio if possible.</p></li>
+<li><p><strong>**kwargs</strong> – Other keyword arguments that will passed to projection function.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Projected image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.radial_profile">
+<span class="sig-name descname"><span class="pre">radial_profile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">nbin</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">r_max</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.radial_profile"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.radial_profile" title="Permalink to this definition">¶</a></dt>
+<dd><p>Calculate radial profile of images. Scale along each axis will be considered,
+i.e., rather ellipsoidal profile will be calculated instead if scales are
+different between axes.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>nbin</strong> (<em>int</em><em>, </em><em>default is 32</em>) – Number of bins.</p></li>
+<li><p><strong>center</strong> (<em>iterable</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – The coordinate of center of radial profile. By default, the center of image
+is used.</p></li>
+<li><p><strong>r_max</strong> (<em>float</em><em>, </em><em>optional</em>) – Maximum radius to make profile. Region 0 &lt;= r &lt; r_max will be split into
+<code class="docutils literal notranslate"><span class="pre">nbin</span></code> rings (or shells). <strong>Scale must be considered</strong> because scales of
+each axis may vary.</p></li>
+<li><p><strong>method</strong> (<em>str</em><em>, </em><em>default is &quot;mean&quot;</em>) – Reduce function. Basic statistics functions are supported in <code class="docutils literal notranslate"><span class="pre">scipy.ndimage</span></code>
+but their names are not consistent with those in <cite>numpy</cite>. Use <cite>numpy</cite>’s names
+here.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Radial profile stored in x-axis by default. If input image has tzcyx-axes, then an array
+with tcx-axes will be returned.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.PropArray" title="impy.arrays.PropArray">PropArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.radon">
+<span class="sig-name descname"><span class="pre">radon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degrees</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">central_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.radon"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.radon" title="Permalink to this definition">¶</a></dt>
+<dd><p>Discrete Radon transformation of 2D or 3D image.</p>
+<p>Radon transformation is a list of projection of a same image from different angles.
+It generates tomographic n-D image slices from (n+1)-D image.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>degrees</strong> (<em>float</em><em> or </em><em>iterable</em><em> of </em><em>float</em>) – Rotation angles around the central axis in degrees.</p></li>
+<li><p><strong>central_axis</strong> (<em>axis-like</em><em> or </em><em>sequence</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Vector that defines the central axis of rotation.</p></li>
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Tomographic image slices. The first spatial axis (“z” for zyx-image) will be dropped.
+If sequence of float is given as <code class="docutils literal notranslate"><span class="pre">degrees</span></code>, “degree” axis will be newly added at
+the position 0. For instance, if a zyx-image and <code class="docutils literal notranslate"><span class="pre">degrees=np.linspace(0,</span> <span class="pre">180,</span> <span class="pre">100)</span></code>
+are given, returned image has axes [“degree”, “y”, “x”].</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.ImgArray.iradon" title="impy.arrays.ImgArray.iradon"><code class="xref py py-obj docutils literal notranslate"><span class="pre">iradon</span></code></a></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.random_walker">
+<span class="sig-name descname"><span class="pre">random_walker</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">beta</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">130</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'cg'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'cg_j'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'cg_mg'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'bf'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'cg_j'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tol</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.random_walker"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.random_walker" title="Permalink to this definition">¶</a></dt>
+<dd><p>Random walker segmentation. Only wrapped skimage segmentation.</p>
+<p><code class="docutils literal notranslate"><span class="pre">self.labels</span></code> will be segmented and updated inplace.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>beta</strong> – see skimage.segmentation.random_walker</p></li>
+<li><p><strong>mode</strong> – see skimage.segmentation.random_walker</p></li>
+<li><p><strong>tol</strong> – see skimage.segmentation.random_walker</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Relabeled image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.regionprops">
+<span class="sig-name descname"><span class="pre">regionprops</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">properties</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">('mean_intensity',)</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">extra_properties</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">Callable</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.html#impy.collections.DataDict" title="impy.collections.DataDict"><span class="pre">DataDict</span></a><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.regionprops"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.regionprops" title="Permalink to this definition">¶</a></dt>
+<dd><p>Multi-dimensional region property quantification.</p>
+<p>Run skimage’s regionprops() function and return the results as PropArray, so
+that you can access using flexible slicing. For example, if a tcyx-image is
+analyzed with <code class="docutils literal notranslate"><span class="pre">properties=(&quot;X&quot;,</span> <span class="pre">&quot;Y&quot;)</span></code>, then you can get X’s time-course profile
+of channel 1 at label 3 by <code class="docutils literal notranslate"><span class="pre">prop[&quot;X&quot;][&quot;p=5;c=1&quot;]</span></code> or <code class="docutils literal notranslate"><span class="pre">prop.X[&quot;p=5;c=1&quot;]</span></code>.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>properties</strong> (<em>iterable</em><em>, </em><em>optional</em>) – properties to analyze, see <code class="docutils literal notranslate"><span class="pre">skimage.measure.regionprops</span></code>.</p></li>
+<li><p><strong>extra_properties</strong> (<em>iterable</em><em> of </em><em>callable</em><em>, </em><em>optional</em>) – extra properties to analyze, see <code class="docutils literal notranslate"><span class="pre">skimage.measure.regionprops</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Dictionary has keys of properties that are specified by <cite>properties</cite>. Each value
+has the array of properties.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.html#impy.collections.DataDict" title="impy.collections.DataDict">DataDict</a> of <a class="reference internal" href="#impy.arrays.PropArray" title="impy.arrays.PropArray">PropArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<p>Measure region properties around single molecules.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">coords</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">centroid_sm</span><span class="p">()</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">specify</span><span class="p">(</span><span class="n">coords</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">labeltype</span><span class="o">=</span><span class="s2">&quot;circle&quot;</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">props</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">regionprops</span><span class="p">()</span>
+</pre></div>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.remove_fine_objects">
+<span class="sig-name descname"><span class="pre">remove_fine_objects</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">length</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.remove_fine_objects"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.remove_fine_objects" title="Permalink to this definition">¶</a></dt>
+<dd><p>Remove fine objects using diameter_opening.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>length</strong> (<em>float</em><em>, </em><em>default is 10</em>) – Objects longer than this will be removed.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Image with large objects removed.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.ImgArray.remove_large_objects" title="impy.arrays.ImgArray.remove_large_objects"><code class="xref py py-obj docutils literal notranslate"><span class="pre">remove_large_objects</span></code></a></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.remove_large_objects">
+<span class="sig-name descname"><span class="pre">remove_large_objects</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">5</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.remove_large_objects"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.remove_large_objects" title="Permalink to this definition">¶</a></dt>
+<dd><p>Remove large objects using opening. Those objects that were not removed by opening
+will be removed in output.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – Objects with radius larger than this value will be removed.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Image with large objects removed.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.ImgArray.remove_fine_objects" title="impy.arrays.ImgArray.remove_fine_objects"><code class="xref py py-obj docutils literal notranslate"><span class="pre">remove_fine_objects</span></code></a></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.remove_skeleton_structure">
+<span class="sig-name descname"><span class="pre">remove_skeleton_structure</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">structure</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'tip'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'branch'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'cross'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'tip'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.remove_skeleton_structure"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.remove_skeleton_structure" title="Permalink to this definition">¶</a></dt>
+<dd><p>Remove certain structure from skeletonized images.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>structure</strong> (<em>str</em><em>, </em><em>default is &quot;tip&quot;</em>) – What type of structure to remove.</p></li>
+<li><p><strong>connectivity</strong> (<em>int</em><em>, </em><em>optional</em>) – Connectivity of pixels. See <code class="docutils literal notranslate"><span class="pre">skimage.measure.label</span></code>.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Processed image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.rescale">
+<span class="sig-name descname"><span class="pre">rescale</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0625</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.rescale"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.rescale" title="Permalink to this definition">¶</a></dt>
+<dd><p>Rescale image by applying the diagonal component of Affine matrix.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>scale</strong> (<em>float</em><em>, </em><em>optional</em>) – Relative scale of the new image. scale 1/2 means that the shape of
+the output image will be (N/2, …).</p></li>
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Rescaled image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.rescale_intensity">
+<span class="sig-name descname"><span class="pre">rescale_intensity</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">in_range:</span> <span class="pre">tuple[int</span> <span class="pre">|</span> <span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">int</span> <span class="pre">|</span> <span class="pre">str]</span> <span class="pre">=</span> <span class="pre">('0%'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">'100%')</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype=&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.rescale_intensity"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.rescale_intensity" title="Permalink to this definition">¶</a></dt>
+<dd><p>Rescale the intensity of the image using skimage.exposure.rescale_intensity().</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>in_range</strong> (<em>two scalar values</em><em>, </em><em>default is</em><em> (</em><em>0%</em><em>, </em><em>100%</em><em>)</em>) – Range of lower/upper limit.</p></li>
+<li><p><strong>dtype</strong> (<em>numpy dtype</em><em>, </em><em>default is np.uint16</em>) – Output dtype.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Rescaled image with temporal attribute</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.rof_filter">
+<span class="sig-name descname"><span class="pre">rof_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tol</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_iter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.rof_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.rof_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Rudin-Osher-Fatemi’s total variation denoising.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>lmd</strong> (<em>float</em><em>, </em><em>default is 0.05</em>) – Constant value in total variation.</p></li>
+<li><p><strong>tol</strong> (<em>float</em><em>, </em><em>default is 1e-4</em>) – Iteration stops when gain is under this value.</p></li>
+<li><p><strong>max_iter</strong> (<em>int</em><em>, </em><em>default is 50</em>) – Maximum number of iterations.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.rolling_ball">
+<span class="sig-name descname"><span class="pre">rolling_ball</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefilter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mean'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'median'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'none'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_bg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.rolling_ball"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.rolling_ball" title="Permalink to this definition">¶</a></dt>
+<dd><p>Subtract Background using rolling-ball algorithm.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>prefilter</strong> (<em>&quot;mean&quot;</em><em>, </em><em>&quot;median&quot;</em><em> or </em><em>&quot;none&quot;</em>) – If apply 3x3 averaging before creating background.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Background subtracted image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.rotate">
+<span class="sig-name descname"><span class="pre">rotate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'center'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'center'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.rotate"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.rotate" title="Permalink to this definition">¶</a></dt>
+<dd><p>2D rotation of an image around a point. Outside will be padded with zero. For n-D images,
+this implementation is faster than <code class="docutils literal notranslate"><span class="pre">scipy.ndimage.rotate</span></code>.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>degree</strong> (<em>float</em>) – Clockwise degree of rotation. Not radian.</p></li>
+<li><p><strong>center</strong> (<em>str</em><em> or </em><em>array-like</em><em>, </em><em>optional</em>) – Rotation center coordinate. By default the center of image will be the rotation center.</p></li>
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Rotated image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.skeletonize">
+<span class="sig-name descname"><span class="pre">skeletonize</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.skeletonize"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.skeletonize" title="Permalink to this definition">¶</a></dt>
+<dd><p>Skeletonize images. Only works for binary images.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – Radius of skeleton. This is achieved simply by dilation of skeletonized results.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Skeletonized image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.smooth_mask">
+<span class="sig-name descname"><span class="pre">smooth_mask</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dilate_radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask_light</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.smooth_mask"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.smooth_mask" title="Permalink to this definition">¶</a></dt>
+<dd><p>Smoothen binary mask image at its edges. This is useful to make a “soft mask”.</p>
+<p>This method applies erosion/dilation to a binary image and then smooth its edges by Gaussian.
+The total value is always larger after Gaussian smoothing.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>sigma</strong> (<em>float</em><em>, </em><em>default is 2.0</em>) – Standard deviation of Gaussian blur.</p></li>
+<li><p><strong>dilate_radius</strong> (<em>float</em><em>, </em><em>default is 2.0</em>) – Radius in pixel that will be used to dilate mask before smoothing.</p></li>
+<li><p><strong>mask_light</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If true, mask array is considered to mask other image at its True values. Otherwise mask array
+plays more like a weight array, that is, False region will be zero.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Smoothened mask image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.split_pixel_unit">
+<span class="sig-name descname"><span class="pre">split_pixel_unit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">(0.5,</span> <span class="pre">0.5)</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">angle_order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">newaxis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'a'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.split_pixel_unit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.split_pixel_unit" title="Permalink to this definition">¶</a></dt>
+<dd><p>Split a (2N, 2M)-image into four (N, M)-images for each other pixels.</p>
+<p>Generally, image acquisition with a polarization camera will output
+<span class="math notranslate nohighlight">\((2N, 2M)\)</span>-image with <span class="math notranslate nohighlight">\(N \times M\)</span> pixel units:</p>
+<table class="docutils align-default">
+<tbody>
+<tr class="row-odd"><td><p>0</p></td>
+<td><p>1</p></td>
+<td><p>0</p></td>
+<td><p>1</p></td>
+<td><p>0</p></td>
+<td><p>1</p></td>
+</tr>
+<tr class="row-even"><td><p>3</p></td>
+<td><p>2</p></td>
+<td><p>3</p></td>
+<td><p>2</p></td>
+<td><p>3</p></td>
+<td><p>2</p></td>
+</tr>
+<tr class="row-odd"><td><p>0</p></td>
+<td><p>1</p></td>
+<td><p>0</p></td>
+<td><p>1</p></td>
+<td><p>0</p></td>
+<td><p>1</p></td>
+</tr>
+<tr class="row-even"><td><p>3</p></td>
+<td><p>2</p></td>
+<td><p>3</p></td>
+<td><p>2</p></td>
+<td><p>3</p></td>
+<td><p>2</p></td>
+</tr>
+</tbody>
+</table>
+<p>This function generates images only consist of positions of [0], [1],
+[2] or [3]. Strictly, each image is acquired from different position
+(the pixel (i, j) in [0]-image and the pixel (i, j) in [1]-image are
+acquired from different positions). This function also complements for
+this difference by interpolation.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>center</strong> (<em>tuple</em><em>, </em><em>default is</em><em> (</em><em>0</em><em>, </em><em>0</em><em>)</em>) – Coordinate that will be considered as the center of the returned
+image. Input (a, b) must satisfy 0 &lt; a &lt; 1 and 0 &lt; b &lt; 1. For example,
+center=(0, 0) means the most upper left pixel, and center=(0.5, 0.5)
+means the middle point of a pixel unit. <cite>[[0, 1], [3, 2]]</cite> becomes
+<cite>[[(0, 0), (0, 1)], [(1, 0), (1, 1)]]</cite>.</p>
+</dd>
+</dl>
+<dl>
+<dt>order<span class="classifier">int, default is 1</span></dt><dd><p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</dd>
+<dt>angle_order<span class="classifier">list of int, default is [2, 1, 0, 3]</span></dt><dd><p>Specify which pixels correspond to which polarization angles. 0, 1, 2
+and 3 corresponds to polarization of 0, 45, 90 and 135 degree
+respectively. This list will be directly passed to <code class="docutils literal notranslate"><span class="pre">np.ndarray</span></code> like
+<code class="docutils literal notranslate"><span class="pre">arr[angle_order]</span></code> to sort it. For example, if a pixel unit receives
+polarized light like below:</p>
+<blockquote>
+<div><div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="p">[</span><span class="mi">1</span><span class="p">]</span>    <span class="p">[</span> <span class="mi">90</span><span class="p">]</span> <span class="p">[</span> <span class="mi">45</span><span class="p">]</span>    <span class="p">[</span><span class="o">|</span><span class="p">]</span> <span class="p">[</span><span class="o">/</span><span class="p">]</span>
+<span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="p">[</span><span class="mi">3</span><span class="p">]</span> <span class="o">-&gt;</span> <span class="p">[</span><span class="mi">135</span><span class="p">]</span> <span class="p">[</span>  <span class="mi">0</span><span class="p">]</span> <span class="ow">or</span> <span class="p">[</span>\<span class="p">]</span> <span class="p">[</span><span class="o">-</span><span class="p">]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>then <code class="docutils literal notranslate"><span class="pre">angle_order</span></code> should be [2, 1, 0, 3].</p>
+</dd>
+</dl>
+<dl class="field-list simple">
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
+<dd class="field-odd"><p>Axis “a” is added in the first dimension. For example, If input is
+“tyx”-axes, then output will be “atyx”-axes.</p>
+</dd>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
+<dd class="field-even"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<p>Extract polarization in 0-, 45-, 90- and 135-degree directions from an
+image that is acquired from a polarization camera, and calculate total
+intensity of light by averaging.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img_pol</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">split_pixel_unit</span><span class="p">()</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">img_total</span> <span class="o">=</span> <span class="n">img_pol</span><span class="o">.</span><span class="n">proj</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="s2">&quot;a&quot;</span><span class="p">)</span>
+</pre></div>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.std_filter">
+<span class="sig-name descname"><span class="pre">std_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.std_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.std_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Standard deviation filter.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.stokes">
+<span class="sig-name descname"><span class="pre">stokes</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'a'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">dict</span></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.stokes"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.stokes" title="Permalink to this definition">¶</a></dt>
+<dd><p>Generate stocks images from an image stack with polarized images.</p>
+<p>Currently, Degree of Linear Polarization (DoLP) and Angle of
+Polarization (AoP) will be calculated. Those irregular values
+(np.nan, np.inf) will be replaced with 0. Be sure that to calculate
+DoPL correctly background subtraction must be applied beforehand because
+stokes parameter <code class="docutils literal notranslate"><span class="pre">s0</span></code> is affected by absolute intensities.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>along</strong> (<em>AxisLike</em><em>, </em><em>default is &quot;a&quot;</em>) – To define which axis is polarization angle axis. Along this axis
+the angle of polarizer must be in order of 0, 45, 90, 135 degree.</p>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Dictionaly with keys “dolp” and “aop”, which correspond to DoPL and
+AoP respectively.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>dict</p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<p>Calculate AoP image from the raw image and display them.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img_pol</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">split_polarization</span><span class="p">()</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">dpol</span> <span class="o">=</span> <span class="n">img_pol</span><span class="o">.</span><span class="n">stokes</span><span class="p">()</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">ip</span><span class="o">.</span><span class="n">gui</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">img_pol</span><span class="o">.</span><span class="n">proj</span><span class="p">())</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">ip</span><span class="o">.</span><span class="n">gui</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">dpol</span><span class="o">.</span><span class="n">aop</span><span class="o">.</span><span class="n">rad2deg</span><span class="p">())</span>
+</pre></div>
+</div>
+<p class="rubric">References</p>
+<ul class="simple">
+<li><p><a class="reference external" href="https://mavic.ne.jp/indutrialcamera-polarization-inline/">https://mavic.ne.jp/indutrialcamera-polarization-inline/</a></p></li>
+<li><p>Yang, J., Qiu, S., Jin, W., Wang, X., &amp; Xue, F. (2020). Polarization imaging model considering the
+non-ideality of polarizers. Applied optics, 59(2), 306-314.</p></li>
+<li><p>Feng, B., Guo, R., Zhang, F., Zhao, F., &amp; Dong, Y. (2021). Calculation and hue mapping of AoP in
+polarization imaging. May. <a class="reference external" href="https://doi.org/10.1117/12.2523643">https://doi.org/10.1117/12.2523643</a></p></li>
+</ul>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.stretch">
+<span class="sig-name descname"><span class="pre">stretch</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'center'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'center'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.stretch"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.stretch" title="Permalink to this definition">¶</a></dt>
+<dd><p>2D stretching of an image from a point.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>scale</strong> (<em>array-like</em>) – Stretch factors.</p></li>
+<li><p><strong>center</strong> (<em>str</em><em> or </em><em>array-like</em><em>, </em><em>optional</em>) – Rotation center coordinate. By default the center of image will be the rotation center.</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Stretched image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.structure_tensor_eig">
+<span class="sig-name descname"><span class="pre">structure_tensor_eig</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.structure_tensor_eig"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.structure_tensor_eig" title="Permalink to this definition">¶</a></dt>
+<dd><p>Calculate structure tensor’s eigenvalues and eigenvectors.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Arrays of eigenvalues and eigenvectors. The axis <code class="docutils literal notranslate"><span class="pre">&quot;l&quot;</span></code> denotes the index of
+eigenvalues. l=0 means the smallest eigenvalue. <code class="docutils literal notranslate"><span class="pre">&quot;r&quot;</span></code> denotes the index of
+spatial dimensions. For 3D image, r=0 means z-element of an eigenvector.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>ImgArray and ImgArray</p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.structure_tensor_eigval">
+<span class="sig-name descname"><span class="pre">structure_tensor_eigval</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.structure_tensor_eigval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.structure_tensor_eigval" title="Permalink to this definition">¶</a></dt>
+<dd><p>Calculate structure tensor’s eigenvalues and eigenvectors.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Array of eigenvalues. The axis <code class="docutils literal notranslate"><span class="pre">&quot;l&quot;</span></code> denotes the index of eigenvalues.
+l=0 means the smallest eigenvalue.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.threshold">
+<span class="sig-name descname"><span class="pre">threshold</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">thr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">ThreasholdMethod</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'otsu'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxisLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.threshold"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.threshold" title="Permalink to this definition">¶</a></dt>
+<dd><p>Apply thresholding to the image and create a binary image.</p>
+<p>The threshold value can be given with a float or a string that indicates what
+thresholding method will be used.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>thr</strong> (<em>float</em><em> or </em><em>str</em><em>, </em><em>optional</em>) – Threshold value, percentage or thresholding algorithm.</p></li>
+<li><p><strong>along</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Dimensions that will not share the same threshold. For instance, if
+<code class="docutils literal notranslate"><span class="pre">along=&quot;c&quot;</span></code> then threshold intensities are determined for every channel.
+If <code class="docutils literal notranslate"><span class="pre">thr</span></code> is float, <code class="docutils literal notranslate"><span class="pre">along</span></code> will be ignored.</p></li>
+<li><p><strong>**kwargs</strong> – Keyword arguments that will passed to function indicated in ‘method’.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Boolian array.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<dl>
+<dt>Substitute outliers to 0.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">thr</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">threshold</span><span class="p">(</span><span class="s2">&quot;99%&quot;</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="p">[</span><span class="n">thr</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py attribute">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.tiled">
+<span class="sig-name descname"><span class="pre">tiled</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.tiled.TiledAccessor" title="impy.arrays.tiled.TiledAccessor"><span class="pre">TiledAccessor</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray"><span class="pre">ImgArray</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#impy.arrays.ImgArray.tiled" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.tiled_lowpass_filter">
+<span class="sig-name descname"><span class="pre">tiled_lowpass_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">overlap</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">16</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.tiled_lowpass_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.tiled_lowpass_filter" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.tiled_lucy">
+<span class="sig-name descname"><span class="pre">tiled_lucy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">niter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1e-05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">overlap</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">32</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.tiled_lucy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.tiled_lucy" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.tophat">
+<span class="sig-name descname"><span class="pre">tophat</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.tophat"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.tophat" title="Permalink to this definition">¶</a></dt>
+<dd><p>Tophat morphological image processing. This is useful for background subtraction.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.track_drift">
+<span class="sig-name descname"><span class="pre">track_drift</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxisLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">show_drift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><span class="pre">MarkerFrame</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.track_drift"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.track_drift" title="Permalink to this definition">¶</a></dt>
+<dd><p>Calculate yx-directional drift using the method equivalent to
+<code class="docutils literal notranslate"><span class="pre">skimage.registration.phase_cross_correlation</span></code>.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>along</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Along which axis drift will be calculated.</p></li>
+<li><p><strong>show_drift</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, plot the result.</p></li>
+<li><p><strong>upsample_factor</strong> (<em>int</em><em>, </em><em>default is 10</em>) – Up-sampling factor when calculating phase cross correlation.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>DataFrame structure with x,y columns</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.track_template">
+<span class="sig-name descname"><span class="pre">track_template</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">template</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">np.ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxisLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'t'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><span class="pre">MarkerFrame</span></a></span></span><a class="headerlink" href="#impy.arrays.ImgArray.track_template" title="Permalink to this definition">¶</a></dt>
+<dd><p>Tracking using template matching. For every time frame, matched region is interpreted as a
+new template and is used for the next template. To avoid slight shifts accumulating to the
+template image, new template image will be fitteg to the old one by phase cross correlation.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>template</strong> (<em>np.ndarray</em>) – Template image. Must be 2 or 3 dimensional.</p></li>
+<li><p><strong>bg</strong> (<em>float</em><em>, </em><em>optional</em>) – Background intensity. If not given, it will calculated as the minimum value of
+the original image.</p></li>
+<li><p><strong>along</strong> (<em>str</em><em>, </em><em>default is &quot;t&quot;</em>) – Which axis will be the time axis.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Centers of matched templates.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.unmix">
+<span class="sig-name descname"><span class="pre">unmix</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">matrix</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'c'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.unmix"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.unmix" title="Permalink to this definition">¶</a></dt>
+<dd><p>Unmix fluorescence leakage between channels in a linear way. For example, a blue/green image,
+fluorescent leakage can be written as following equation:</p>
+<blockquote>
+<div><p><span class="math notranslate nohighlight">\(\left\{\begin{array}{ll} B_{obs} = B_{real} + a \cdot G_{real} &amp; \\G_{obs} = b \cdot B_{real} + G_{real} &amp; \end{array} \right.\)</span></p>
+</div></blockquote>
+<p>where “obs” means observed intensities, “real” means the real intensity. In this linear case,
+leakage matrix:</p>
+<blockquote>
+<div><p><span class="math notranslate nohighlight">\(M = \begin{bmatrix} 1 &amp; a \\b &amp; 1 \end{bmatrix} \\\)</span></p>
+<p><span class="math notranslate nohighlight">\(V_{obs} = M \cdot V_{real}\)</span></p>
+</div></blockquote>
+<p>must be predefined. If M is given, then real intensities can be restored by:</p>
+<blockquote>
+<div><p><span class="math notranslate nohighlight">\(V_{real} = M^{-1} \cdot V_{obs}\)</span></p>
+</div></blockquote>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>matrix</strong> (<em>array-like</em>) – Leakage matrix. The (i, j) component of the matrix is the leakage from i-th channel to
+j-th channel.</p></li>
+<li><p><strong>bg</strong> (<em>array-like</em><em>, </em><em>optional</em>) – Vector of background intensities for each channel. If not given, it is assumed to be the
+minimum value of each channel.</p></li>
+<li><p><strong>along</strong> (<em>str</em><em>, </em><em>default is &quot;c&quot;</em>) – The axis of channel.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Unmixed image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<dl>
+<dt>Complement the channel-0 to channel-1 leakage.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">mtx</span> <span class="o">=</span> <span class="p">[[</span><span class="mf">1.0</span><span class="p">,</span> <span class="mf">0.4</span><span class="p">],</span>
+<span class="gp">&gt;&gt;&gt; </span>       <span class="p">[</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">]]</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">bg</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1500</span><span class="p">,</span> <span class="mi">1200</span><span class="p">]</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">unmixed_img</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">unmix</span><span class="p">(</span><span class="n">mtx</span><span class="p">,</span> <span class="n">bg</span><span class="p">)</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.voronoi">
+<span class="sig-name descname"><span class="pre">voronoi</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coords</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Coords</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">nDInt</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.voronoi"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.voronoi" title="Permalink to this definition">¶</a></dt>
+<dd><p>Voronoi segmentation of an image.</p>
+<p>Image region labeled with $i$ means that all the points in the region are
+closer to the $i$-th point than any other points.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>coords</strong> (<a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><em>MarkerFrame</em></a><em> or </em><em>(</em><em>N</em><em>, </em><em>2</em><em>) </em><em>array-like</em>) – Coordinates of points.</p></li>
+<li><p><strong>inf</strong> (<em>int</em><em>, </em><em>array</em><em> of </em><em>int</em><em>, </em><em>optional</em>) – Distance to infinity points. If not provided, infinity points are
+placed at 100 times further positions relative to the image shape.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Segmentation labels of image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.Label" title="impy.arrays.Label">Label</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.watershed">
+<span class="sig-name descname"><span class="pre">watershed</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coords</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><span class="pre">MarkerFrame</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'self'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'distance'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'distance'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_distance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.Label" title="impy.arrays.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.watershed"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.watershed" title="Permalink to this definition">¶</a></dt>
+<dd><p>Label segmentation using watershed algorithm.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>coords</strong> (<a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><em>MarkerFrame</em></a><em>, </em><em>optional</em>) – Returned by such as <cite>peak_local_max()</cite>. Array of coordinates of peaks.</p></li>
+<li><p><strong>{connectivity}</strong> – </p></li>
+<li><p><strong>input</strong> (<em>str</em><em>, </em><em>optional</em>) – <p>What image will be the input of watershed algorithm.</p>
+<ul>
+<li><p>”self” … self is used.</p></li>
+<li><p>”distance” … distance map of self.labels is used.</p></li>
+</ul>
+</p></li>
+<li><p><strong>{dims}</strong> – </p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Updated labels.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.Label" title="impy.arrays.Label">Label</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.wavelet_denoising">
+<span class="sig-name descname"><span class="pre">wavelet_denoising</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">noise_sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wavelet</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'db1'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'soft'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'hard'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'soft'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wavelet_levels</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'BayesShrink'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'VisuShrink'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'BayesShrink'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift_steps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.wavelet_denoising"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.wavelet_denoising" title="Permalink to this definition">¶</a></dt>
+<dd><p>Wavelet denoising. Because it is not shift invariant, <code class="docutils literal notranslate"><span class="pre">cycle_spin</span></code> is called inside the
+function.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>noise_sigma</strong> (<em>float</em><em>, </em><em>optional</em>) – Standard deviation of noise, if known.</p></li>
+<li><p><strong>wavelet</strong> (<em>str</em><em>, </em><em>default is &quot;db1&quot;</em>) – Any options of <cite>pywt.wavelist</cite>.</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;soft&quot;</em><em>, </em><em>&quot;hard&quot;}</em><em>, </em><em>default is &quot;soft&quot;</em>) – Type of denoising.</p></li>
+<li><p><strong>wavelet_levels</strong> (<em>int</em><em>, </em><em>optional</em>) – The number of wavelet decomposition levels to use.</p></li>
+<li><p><strong>method</strong> (<em>{&quot;BayesShrink&quot;</em><em>, </em><em>&quot;VisuShrink&quot;}</em><em>, </em><em>default is &quot;BayesShrink&quot;</em>) – Thresholding method to be used</p></li>
+<li><p><strong>max_shifts</strong> (<em>int</em><em> or </em><em>tuple</em><em>, </em><em>default is 0</em>) – Shifts in range(0, max_shifts+1) will be used.</p></li>
+<li><p><strong>shift_steps</strong> (<em>int</em><em> or </em><em>tuple</em><em>, </em><em>default is 1</em>) – Step size of shifts.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Denoised image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.ImgArray.wiener">
+<span class="sig-name descname"><span class="pre">wiener</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/imgarray.html#ImgArray.wiener"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.ImgArray.wiener" title="Permalink to this definition">¶</a></dt>
+<dd><p>Classical wiener deconvolution. This algorithm has the serious ringing problem
+if parameters are set to wrong values.</p>
+<p><span class="math notranslate nohighlight">\(F[Y_{res}] = \frac{F[Y_{obs}] \cdot \bar{H}}{|H|^2 + \lambda}\)</span></p>
+<p><span class="math notranslate nohighlight">\(Y_{obs}\)</span>: observed image;
+<span class="math notranslate nohighlight">\(Y_{res}\)</span>: restored image;
+<span class="math notranslate nohighlight">\(H\)</span> : FFT of point spread function (PSF);</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>psf</strong> (<em>ndarray</em><em> or </em><em>callable</em>) – Point spread function. If a function is given, <cite>psf(shape)</cite> will be
+called to generate the PSF.</p></li>
+<li><p><strong>lmd</strong> (<em>float</em><em>, </em><em>default is 0.1</em>) – Constant value used in the deconvolution. See Formulation below.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Deconvolved image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.ImgArray.lucy" title="impy.arrays.ImgArray.lucy"><code class="xref py py-obj docutils literal notranslate"><span class="pre">lucy</span></code></a>, <a class="reference internal" href="#impy.arrays.ImgArray.lucy_tv" title="impy.arrays.ImgArray.lucy_tv"><code class="xref py py-obj docutils literal notranslate"><span class="pre">lucy_tv</span></code></a></p>
+</div>
+</dd></dl>
+
+</dd></dl>
+
+<dl class="py class">
+<dt class="sig sig-object py" id="impy.arrays.Label">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.</span></span><span class="sig-name descname"><span class="pre">Label</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">obj</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">source</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metadata</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.Label" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">MetaArray</span></code></a></p>
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.Label.add_label">
+<span class="sig-name descname"><span class="pre">add_label</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">label_image</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.add_label"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.Label.add_label" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.Label.as_larger_type">
+<span class="sig-name descname"><span class="pre">as_larger_type</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.as_larger_type"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.Label.as_larger_type" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.Label.delete_label">
+<span class="sig-name descname"><span class="pre">delete_label</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">label_ids</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.delete_label"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.Label.delete_label" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.Label.expand_labels">
+<span class="sig-name descname"><span class="pre">expand_labels</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">distance</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.expand_labels"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.Label.expand_labels" title="Permalink to this definition">¶</a></dt>
+<dd><p>Expand areas of labels.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>distance</strong> (<em>int</em><em>, </em><em>optional</em>) – The distance to expand, by default 1</p></li>
+<li><p><strong>{dims}</strong> – </p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Same array but labels are updated.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.Label" title="impy.arrays.Label">Label</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.Label.imshow">
+<span class="sig-name descname"><span class="pre">imshow</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.imshow"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.Label.imshow" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.Label.increment">
+<span class="sig-name descname"><span class="pre">increment</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">n</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.increment"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.Label.increment" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.Label.increment_iter">
+<span class="sig-name descname"><span class="pre">increment_iter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.increment_iter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.Label.increment_iter" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.Label.opening">
+<span class="sig-name descname"><span class="pre">opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.opening"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.Label.opening" title="Permalink to this definition">¶</a></dt>
+<dd><p>Morphological opening.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Opened labels</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.Label" title="impy.arrays.Label">Label</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.Label.optimize">
+<span class="sig-name descname"><span class="pre">optimize</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.optimize"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.Label.optimize" title="Permalink to this definition">¶</a></dt>
+<dd><p>Optimize labeling.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.Label.proj">
+<span class="sig-name descname"><span class="pre">proj</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forbid_overlap</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.proj"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.Label.proj" title="Permalink to this definition">¶</a></dt>
+<dd><p>Label projection. This function is useful when zyx-labels are drawn but you want to reduce the
+dimension.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>axis</strong> (<em>str</em><em>, </em><em>optional</em>) – Along which axis projection will be calculated. If None, most plausible one will be chosen.</p></li>
+<li><p><strong>forbid_overlap</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True and there were any label overlap, this function will raise ValueError.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Projected labels.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.Label" title="impy.arrays.Label">Label</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.Label.relabel">
+<span class="sig-name descname"><span class="pre">relabel</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/label.html#Label.relabel"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.Label.relabel" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+</dd></dl>
+
+<dl class="py class">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.</span></span><span class="sig-name descname"><span class="pre">LabeledArray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">obj</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">source</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Path</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metadata</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">MetaArray</span></code></a></p>
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.append_label">
+<span class="sig-name descname"><span class="pre">append_label</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">label_image</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">new</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.append_label"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.append_label" title="Permalink to this definition">¶</a></dt>
+<dd><p>Append new labels from an array. This function works for boolean or signed int arrays.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>label_image</strong> (<em>np.ndarray</em>) – Labeled image.</p></li>
+<li><p><strong>new</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, existing labels will be removed anyway.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>New labels.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.Label" title="impy.arrays.Label">Label</a></p>
+</dd>
+</dl>
+<p class="rubric">Example</p>
+<p>Make label from different channels.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">thr0</span> <span class="o">=</span> <span class="n">img</span><span class="p">[</span><span class="s2">&quot;c=0&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">threshold</span><span class="p">(</span><span class="s2">&quot;90%&quot;</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">thr0</span><span class="o">.</span><span class="n">label</span><span class="p">()</span> <span class="c1"># binary to label</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">thr1</span> <span class="o">=</span> <span class="n">img</span><span class="p">[</span><span class="s2">&quot;c=1&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">threshold</span><span class="p">(</span><span class="s2">&quot;90%&quot;</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">thr1</span><span class="o">.</span><span class="n">label</span><span class="p">()</span> <span class="c1"># binary to label</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">append_label</span><span class="p">(</span><span class="n">thr0</span><span class="o">.</span><span class="n">labels</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">append_label</span><span class="p">(</span><span class="n">thr1</span><span class="o">.</span><span class="n">labels</span><span class="p">)</span>
+</pre></div>
+</div>
+<p>If <cite>thr0</cite> has 100 labels and <cite>thr1</cite> has 150 labels then <cite>img</cite> will have <span class="math notranslate nohighlight">\(100+150=250\)</span> labels.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.as_float">
+<span class="sig-name descname"><span class="pre">as_float</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.as_float"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.as_float" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.as_img_type">
+<span class="sig-name descname"><span class="pre">as_img_type</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dtype=&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.as_img_type"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.as_img_type" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.as_uint16">
+<span class="sig-name descname"><span class="pre">as_uint16</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.as_uint16"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.as_uint16" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.as_uint8">
+<span class="sig-name descname"><span class="pre">as_uint8</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.as_uint8"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.as_uint8" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.axes">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">axes</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">Axes</span></em><a class="headerlink" href="#impy.arrays.LabeledArray.axes" title="Permalink to this definition">¶</a></dt>
+<dd><p>Axes of the array.</p>
+</dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.covariates">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">covariates</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.labeledarray.ArrayCovariates" title="impy.arrays.labeledarray.ArrayCovariates"><span class="pre">ArrayCovariates</span></a></em><a class="headerlink" href="#impy.arrays.LabeledArray.covariates" title="Permalink to this definition">¶</a></dt>
+<dd><p>Get all the covariates.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.crop_center">
+<span class="sig-name descname"><span class="pre">crop_center</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">nDFloat</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.crop_center"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.crop_center" title="Permalink to this definition">¶</a></dt>
+<dd><p>Crop out the center of an image.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>scale</strong> (<em>float</em><em> or </em><em>array-like</em><em>, </em><em>default is 0.5</em>) – Scale of the cropped image. If an array is given, each axis will be cropped in different scales,
+using each value respectively.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>CroppedImage</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>Self</p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<ol class="arabic">
+<li><p>Create a <span class="math notranslate nohighlight">\(512\times512\)</span> image from a <span class="math notranslate nohighlight">\(1024\times1024\)</span> image.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img_cropped</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">crop_center</span><span class="p">(</span><span class="n">scale</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
+</pre></div>
+</div>
+</li>
+<li><p>Create a <span class="math notranslate nohighlight">\(21\times256\times256\)</span> image from a <span class="math notranslate nohighlight">\(63\times1024\times1024\)</span> image.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img_cropped</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">crop_center</span><span class="p">(</span><span class="n">scale</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="o">/</span><span class="mi">3</span><span class="p">,</span> <span class="mi">1</span><span class="o">/</span><span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="o">/</span><span class="mi">2</span><span class="p">])</span>
+</pre></div>
+</div>
+</li>
+</ol>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.crop_kernel">
+<span class="sig-name descname"><span class="pre">crop_kernel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">nDInt</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.crop_kernel"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.crop_kernel" title="Permalink to this definition">¶</a></dt>
+<dd><p>Make a kernel from an image by cropping out the center region.
+This function is useful especially in <cite>ImgArray.defocus()</cite>.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>radius</strong> (<em>int</em><em> or </em><em>array-like</em><em> of </em><em>int</em><em>, </em><em>default is 2</em>) – Radius of the kernel.</p>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Kernel</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LabeledArray" title="impy.arrays.LabeledArray">LabeledArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<p>Make a <span class="math notranslate nohighlight">\(4\times4\times4\)</span> kernel from a point spread function image (suppose the
+image shapes are all even numbers).</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">psf</span> <span class="o">=</span> <span class="n">ip</span><span class="o">.</span><span class="n">imread</span><span class="p">(</span><span class="sa">r</span><span class="s2">&quot;.../PSF.tif&quot;</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">psfker</span> <span class="o">=</span> <span class="n">psf</span><span class="o">.</span><span class="n">crop_kernel</span><span class="p">()</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">psfer</span><span class="o">.</span><span class="n">shape</span>
+<span class="go">(4, 4, 4)</span>
+</pre></div>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.extract">
+<span class="sig-name descname"><span class="pre">extract</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">label_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filt</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.html#impy.collections.DataList" title="impy.collections.DataList"><span class="pre">DataList</span></a><span class="p"><span class="pre">[</span></span><span class="pre">Self</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.extract"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.extract" title="Permalink to this definition">¶</a></dt>
+<dd><p>Extract certain regions of the image and substitute others to <cite>cval</cite>.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>label_ids</strong> (<em>int</em><em> or </em><em>iterable</em><em> of </em><em>int</em><em>, </em><em>by default all the label IDs.</em>) – Which label regions are extracted.</p></li>
+<li><p><strong>filt</strong> (<em>callable</em><em>, </em><em>optional</em>) – If given, only regions <cite>X</cite> that satisfy filt(self, X) will extracted.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.</em>) – Constant value to fill regions outside the extracted labeled regions.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Extracted image(s)</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.html#impy.collections.DataList" title="impy.collections.DataList">DataList</a> of <a class="reference internal" href="#impy.arrays.LabeledArray" title="impy.arrays.LabeledArray">LabeledArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.for_each_channel">
+<span class="sig-name descname"><span class="pre">for_each_channel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'c'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.for_each_channel"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.for_each_channel" title="Permalink to this definition">¶</a></dt>
+<dd><p>Apply same function with different parameters for each channel. This function will be useful
+when the parameters are dependent on channels, like wave length.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>func</strong> (<em>str</em>) – Function name to apply over channel axis.</p></li>
+<li><p><strong>along</strong> (<em>str</em><em>, </em><em>default is &quot;c&quot;</em>) – Along which axis function will be applied to.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>output image stack</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LabeledArray" title="impy.arrays.LabeledArray">LabeledArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.for_params">
+<span class="sig-name descname"><span class="pre">for_params</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">var</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.html#impy.collections.DataList" title="impy.collections.DataList"><span class="pre">DataList</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.for_params"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.for_params" title="Permalink to this definition">¶</a></dt>
+<dd><p>Apply same function with different parameters with same input. This function will be useful
+when you want to try different conditions to the same image.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>func</strong> (<em>callable</em><em> or </em><em>str</em>) – Function to apply repetitively. If str, then member method will be called.</p></li>
+<li><p><strong>var</strong> (<em>dict</em><em>[</em><em>str</em><em>, </em><em>Iterable</em><em>]</em><em>, </em><em>optional</em>) – Name of variable and the values to try. If you want to try sigma=1,2,3 then you should
+give <cite>var={“sigma”: [1, 2, 3]}</cite>.</p></li>
+<li><p><strong>kwargs</strong> – Fixed paramters that will be passed to <cite>func</cite>. If <cite>var</cite> is not given and only one parameter
+is provided in <cite>kwargs</cite>, then kwargs will be <cite>var</cite>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>List of outputs.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.html#impy.collections.DataList" title="impy.collections.DataList">DataList</a></p>
+</dd>
+</dl>
+<p class="rubric">Example</p>
+<ol class="arabic">
+<li><p>Try LoG filter with different Gaussian kernel size and visualize all of them in napari.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">out</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">for_params</span><span class="p">(</span><span class="s2">&quot;log_filter&quot;</span><span class="p">,</span> <span class="n">var</span><span class="o">=</span><span class="p">{</span><span class="s2">&quot;sigma&quot;</span><span class="p">:[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">]})</span>
+<span class="go"># or</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">out</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">for_params</span><span class="p">(</span><span class="s2">&quot;log_filter&quot;</span><span class="p">,</span> <span class="n">sigma</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">])</span>
+<span class="go"># then</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">ip</span><span class="o">.</span><span class="n">gui</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">out</span><span class="p">)</span>
+</pre></div>
+</div>
+</li>
+</ol>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.hist">
+<span class="sig-name descname"><span class="pre">hist</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">contrast</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.hist"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.hist" title="Permalink to this definition">¶</a></dt>
+<dd><p>Show intensity profile.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.imsave">
+<span class="sig-name descname"><span class="pre">imsave</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">save_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Path</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">overwrite</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.imsave"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.imsave" title="Permalink to this definition">¶</a></dt>
+<dd><p>Save image at the same directory as the original image by default.</p>
+<p>For tif file format, if the image contains wrong axes for ImageJ (= except for tzcyx),
+then it will converted automatically if possible. For mrc file format, only zyx and yx is
+allowed. zyx-scale is also saved.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>save_path</strong> (<em>str</em>) – File name.</p></li>
+<li><p><strong>dtype</strong> (<em>dtype-like</em><em>, </em><em>optional</em>) – In what data type img will be saved.</p></li>
+<li><p><strong>overwrite</strong> (<em>bool</em><em>, </em><em>default is True</em>) – Whether to overwrite the file if it already exists.</p></li>
+</ul>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.imshow">
+<span class="sig-name descname"><span class="pre">imshow</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">label</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">plugin</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'matplotlib'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.imshow"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.imshow" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.label">
+<span class="sig-name descname"><span class="pre">label</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ref_image</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">bool</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.label"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.label" title="Permalink to this definition">¶</a></dt>
+<dd><p>Label image using skimage’s label().</p>
+<p>Label image using <cite>ref_image</cite> as reference image, or image itself. If
+<code class="docutils literal notranslate"><span class="pre">filt</span></code> is given, image will be labeled only if certain condition
+dictated in <cite>filt</cite> is satisfied. <cite>regionprops_table</cite> is called inside
+every time image is labeled.</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">filt</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">lbl</span><span class="p">,</span> <span class="n">area</span><span class="p">,</span> <span class="n">major_axis_length</span><span class="p">):</span>
+    <span class="k">return</span> <span class="n">area</span><span class="o">&gt;</span><span class="mi">10</span> <span class="ow">and</span> <span class="n">major_axis_length</span><span class="o">&gt;</span><span class="mi">5</span>
+</pre></div>
+</div>
+</div></blockquote>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>ref_image</strong> (<em>array</em><em>, </em><em>optional</em>) – Image to make label, by default self is used.</p></li>
+<li><p><strong>filt</strong> (<em>callable</em><em>, </em><em>positional argument but not optional</em>) – Filter function. The first argument is intensity image sliced from
+<cite>self</cite>, the second is label image sliced from labeled <cite>ref_image</cite>,
+and the rest arguments is properties that will be calculated using
+<cite>regionprops</cite> function. The property arguments <strong>must be named
+exactly same</strong> as the properties in <cite>regionprops</cite>. Number of
+arguments can be two.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>connectivity</strong> (<em>int</em><em>, </em><em>optional</em>) – Connectivity of pixels. See <code class="docutils literal notranslate"><span class="pre">skimage.measure.label</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Newly created label.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.Label" title="impy.arrays.Label">Label</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<ol class="arabic">
+<li><dl>
+<dt>Label the image with threshold and visualize with napari.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">thr</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">threshold</span><span class="p">()</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">label</span><span class="p">(</span><span class="n">thr</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">ip</span><span class="o">.</span><span class="n">gui</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</li>
+<li><dl>
+<dt>Label regions if only intensity is high.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">high_intensity</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">lbl</span><span class="p">,</span> <span class="nb">slice</span><span class="p">):</span>
+<span class="gp">&gt;&gt;&gt; </span>    <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">img</span><span class="p">[</span><span class="nb">slice</span><span class="p">])</span> <span class="o">&gt;</span> <span class="mi">10000</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">label</span><span class="p">(</span><span class="n">lbl</span><span class="p">,</span> <span class="n">filt</span><span class="p">)</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</li>
+<li><dl>
+<dt>Label regions if no hole exists.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">no_hole</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">lbl</span><span class="p">,</span> <span class="n">euler_number</span><span class="p">):</span>
+<span class="gp">&gt;&gt;&gt; </span>    <span class="k">return</span> <span class="n">euler_number</span> <span class="o">&gt;</span> <span class="mi">0</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">label</span><span class="p">(</span><span class="n">lbl</span><span class="p">,</span> <span class="n">filt</span><span class="p">)</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</li>
+<li><dl>
+<dt>Label regions if centroids are inside themselves.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">no_hole</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">lbl</span><span class="p">,</span> <span class="n">centroid</span><span class="p">):</span>
+<span class="gp">&gt;&gt;&gt; </span>    <span class="n">yc</span><span class="p">,</span> <span class="n">xc</span> <span class="o">=</span> <span class="nb">map</span><span class="p">(</span><span class="nb">int</span><span class="p">,</span> <span class="n">centroid</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span>    <span class="k">return</span> <span class="n">lbl</span><span class="p">[</span><span class="n">yc</span><span class="p">,</span> <span class="n">xc</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">0</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">label</span><span class="p">(</span><span class="n">lbl</span><span class="p">,</span> <span class="n">filt</span><span class="p">)</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</li>
+</ol>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.label_if">
+<span class="sig-name descname"><span class="pre">label_if</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ref_image</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">bool</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">connectivity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.label_if"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.label_if" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.labels">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">labels</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></em><a class="headerlink" href="#impy.arrays.LabeledArray.labels" title="Permalink to this definition">¶</a></dt>
+<dd><p>The label of the image.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.map_coordinates">
+<span class="sig-name descname"><span class="pre">map_coordinates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coordinates</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">PaddingMode</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefilter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">has_nan</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.map_coordinates"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.map_coordinates" title="Permalink to this definition">¶</a></dt>
+<dd><p>Coordinate mapping in the image. See <code class="docutils literal notranslate"><span class="pre">scipy.ndimage.map_coordinates</span></code>.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>coordinates</strong> (<em>ArrayLike</em>) – Interpolation coordinates. Must be (D, N) or (D, X_1, …, X_D) shape.</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+<li><p><strong>prefilter</strong> (<em>bool</em><em>, </em><em>optional</em>) – Spline prefilter applied to the array. By default set to True if <code class="docutils literal notranslate"><span class="pre">order</span></code> is larger
+than 1.</p></li>
+<li><p><strong>has_nan</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If true, nan values will be masked out.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Transformed image. Axes will be correctly filled if possible.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LabeledArray" title="impy.arrays.LabeledArray">LabeledArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.pathprops">
+<span class="sig-name descname"><span class="pre">pathprops</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">paths</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.frame.html#impy.frame.frames.PathFrame" title="impy.frame.frames.PathFrame"><span class="pre">PathFrame</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">ArrayLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">ArrayLike</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">properties</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.html#impy.collections.DataDict" title="impy.collections.DataDict"><span class="pre">DataDict</span></a><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.PropArray" title="impy.arrays.PropArray"><span class="pre">PropArray</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.pathprops"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.pathprops" title="Permalink to this definition">¶</a></dt>
+<dd><p>Measure line property using func(line_scan) for each functions in properties.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>paths</strong> (<a class="reference internal" href="impy.frame.html#impy.frame.frames.PathFrame" title="impy.frame.frames.PathFrame"><em>PathFrame</em></a>) – Paths to measure properties.</p></li>
+<li><p><strong>properties</strong> (<em>str</em><em> or </em><em>callable</em><em>, or </em><em>their iterable</em>) – Properties to be analyzed.</p></li>
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Line properties. Keys are property names and values are the corresponding PropArrays.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.html#impy.collections.DataDict" title="impy.collections.DataDict">DataDict</a> of <a class="reference internal" href="#impy.arrays.PropArray" title="impy.arrays.PropArray">PropArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<ol class="arabic">
+<li><dl>
+<dt>Time-course measurement of intensities on a path.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">pathprops</span><span class="p">([[</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="p">[</span><span class="mi">102</span><span class="p">,</span> <span class="mi">301</span><span class="p">],</span> <span class="p">[</span><span class="mi">200</span><span class="p">,</span> <span class="mi">400</span><span class="p">]])</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</li>
+</ol>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.pointprops">
+<span class="sig-name descname"><span class="pre">pointprops</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coords</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Coords</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.PropArray" title="impy.arrays.PropArray"><span class="pre">PropArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.pointprops"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.pointprops" title="Permalink to this definition">¶</a></dt>
+<dd><p>Measure interpolated intensity at points with float coordinates.</p>
+<p>This method is essentially identical to <a class="reference internal" href="#impy.arrays.LabeledArray.map_coordinates" title="impy.arrays.LabeledArray.map_coordinates"><code class="xref py py-func docutils literal notranslate"><span class="pre">map_coordinates()</span></code></a> but is
+more straightforward for measuring intensities at points.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>coords</strong> (<em>DataFrame</em><em> or </em><em>array-like</em>) – Coordinates of point to be measured.</p></li>
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+<li><p><strong>squeeze</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True and only one point is measured, the redundant dimension ID_AXIS will be deleted.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Intensities at points.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.PropArray" title="impy.arrays.PropArray">PropArray</a> or float</p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<dl>
+<dt>Calculate centroids and measure intensities.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">coords</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">proj</span><span class="p">(</span><span class="s2">&quot;t&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">centroid_sm</span><span class="p">()</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">prop</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">pointprops</span><span class="p">(</span><span class="n">coords</span><span class="p">)</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.proj_labels">
+<span class="sig-name descname"><span class="pre">proj_labels</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">forbid_overlap</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.proj_labels"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.proj_labels" title="Permalink to this definition">¶</a></dt>
+<dd><p>Label projection. This function is useful when zyx-labels are drawn but you want to reduce the
+dimension.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>axis</strong> (<em>str</em><em>, </em><em>optional</em>) – Along which axis projection will be calculated. If None, most plausible one will be chosen.</p></li>
+<li><p><strong>forbid_overlap</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True and there were any label overlap, this function will raise ValueError.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Projected labels.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.Label" title="impy.arrays.Label">Label</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.range">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">range</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#impy.arrays.LabeledArray.range" title="Permalink to this definition">¶</a></dt>
+<dd><p>Return min/max range of the array.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.remove_edges">
+<span class="sig-name descname"><span class="pre">remove_edges</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pixel</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">nDInt</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.remove_edges"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.remove_edges" title="Permalink to this definition">¶</a></dt>
+<dd><p>Remove pixels from the edges.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>pixel</strong> (<em>int</em><em> or </em><em>array-like</em><em>, </em><em>default is 1</em>) – Number of pixels to remove. If an array is given, each axis will be cropped with different pixels,
+using each value respectively.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Cropped image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LabeledArray" title="impy.arrays.LabeledArray">LabeledArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.reslice">
+<span class="sig-name descname"><span class="pre">reslice</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">a</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">b</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefilter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.PropArray" title="impy.arrays.PropArray"><span class="pre">PropArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.reslice"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.reslice" title="Permalink to this definition">¶</a></dt>
+<dd><p>Measure line profile (kymograph) iteratively for every slice of image. This
+function is almost same as <cite>skimage.measure.profile_line</cite>, but can reslice
+3D-images. The argument <cite>linewidth</cite> is not implemented here because it is
+useless.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>a</strong> (<em>array-like</em>) – Path or source coordinate. If the former, it must be like:
+<cite>a = [[y0, x0], [y1, x1], …, [yn, xn]]</cite></p></li>
+<li><p><strong>b</strong> (<em>array-like</em><em>, </em><em>optional</em>) – Destination coordinate. If specified, <cite>a</cite> must be the source coordinate.</p></li>
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Line scans.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.PropArray" title="impy.arrays.PropArray">PropArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<ol class="arabic">
+<li><p>Rescile along a line and fit to a model function for every time frame.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">scan</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">reslice</span><span class="p">([</span><span class="mi">18</span><span class="p">,</span> <span class="mi">32</span><span class="p">],</span> <span class="p">[</span><span class="mi">53</span><span class="p">,</span> <span class="mi">48</span><span class="p">])</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">out</span> <span class="o">=</span> <span class="n">scan</span><span class="o">.</span><span class="n">curve_fit</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">init</span><span class="p">,</span> <span class="n">return_fit</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">scan</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">out</span><span class="o">.</span><span class="n">fit</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
+</pre></div>
+</div>
+</li>
+<li><p>Rescile along a path.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">scan</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">reslice</span><span class="p">([[</span><span class="mi">18</span><span class="p">,</span> <span class="mi">32</span><span class="p">],</span> <span class="p">[</span><span class="mi">53</span><span class="p">,</span><span class="mi">48</span><span class="p">],</span> <span class="p">[</span><span class="mi">22</span><span class="p">,</span><span class="mi">45</span><span class="p">],</span> <span class="p">[</span><span class="mi">28</span><span class="p">,</span> <span class="mi">32</span><span class="p">]])</span>
+</pre></div>
+</div>
+</li>
+</ol>
+</dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.rois">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">rois</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="impy.html#impy.roi.RoiList" title="impy.roi.RoiList"><span class="pre">RoiList</span></a></em><a class="headerlink" href="#impy.arrays.LabeledArray.rois" title="Permalink to this definition">¶</a></dt>
+<dd><p>ROIs of the image.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.rotated_crop">
+<span class="sig-name descname"><span class="pre">rotated_crop</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">origin</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dst1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dst2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.rotated_crop"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.rotated_crop" title="Permalink to this definition">¶</a></dt>
+<dd><p>Crop the image at four courners of an rotated rectangle. Currently only supports rotation within
+yx-plane. An rotated rectangle is specified with positions of a origin and two destinations <cite>dst1</cite>
+and <cite>dst2</cite>, i.e., vectors (dst1-origin) and (dst2-origin) represent a rotated rectangle. Let
+origin be the origin of a xy-plane, the rotation direction from dst1 to dst2 must be counter-
+clockwise, or the cropped image will be reversed.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>origin</strong> (<em>(</em><em>float</em><em>, </em><em>float</em><em>)</em>) – </p></li>
+<li><p><strong>dst1</strong> (<em>(</em><em>float</em><em>, </em><em>float</em><em>)</em>) – </p></li>
+<li><p><strong>dst2</strong> (<em>(</em><em>float</em><em>, </em><em>float</em><em>)</em>) – </p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Cropped array.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LabeledArray" title="impy.arrays.LabeledArray">LabeledArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.set_scale">
+<span class="sig-name descname"><span class="pre">set_scale</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">other</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.set_scale"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.set_scale" title="Permalink to this definition">¶</a></dt>
+<dd><p>Set scales of each axis.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>other</strong> (<em>dict</em><em> or </em><em>object with axes</em>) – New scales. If dict, it should be like {“x”: 0.1, “y”: 0.1}. If MetaArray, only
+scales of common axes are copied.</p></li>
+<li><p><strong>unit</strong> (<em>str</em><em>, </em><em>optional</em>) – Scale unit if needs update.</p></li>
+<li><p><strong>kwargs</strong> – This enables function call like set_scale(x=0.1, y=0.1).</p></li>
+</ul>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.specify">
+<span class="sig-name descname"><span class="pre">specify</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Coords</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Coords</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">labeltype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'square'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.Label" title="impy.arrays.Label"><span class="pre">Label</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.specify"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.specify" title="Permalink to this definition">¶</a></dt>
+<dd><p>Make rectangle or ellipse labels from points.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>center</strong> (<em>array like</em><em> or </em><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame"><em>MarkerFrame</em></a>) – Coordinates of centers. For MarkerFrame, it must have the same axes order.</p></li>
+<li><p><strong>radius</strong> (<em>float</em><em> or </em><em>array-like</em>) – Radius of labels.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>labeltype</strong> (<em>str</em><em>, </em><em>default is &quot;square&quot;</em>) – The shape of labels.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Labeled regions.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.Label" title="impy.arrays.Label">Label</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<dl>
+<dt>Find single molecules, draw circular labels around them if mean values were greater than 100.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">coords</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">find_sm</span><span class="p">()</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">filter_func</span> <span class="o">=</span> <span class="k">lambda</span> <span class="n">a</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">a</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">100</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">specify</span><span class="p">(</span><span class="n">coords</span><span class="p">,</span> <span class="mf">3.5</span><span class="p">,</span> <span class="n">filt</span><span class="o">=</span><span class="n">filter_func</span><span class="p">,</span> <span class="n">labeltype</span><span class="o">=</span><span class="s2">&quot;circle&quot;</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">ip</span><span class="o">.</span><span class="n">gui</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.spline_filter">
+<span class="sig-name descname"><span class="pre">spline_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mirror'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.spline_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.spline_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Run spline filter.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LabeledArray" title="impy.arrays.LabeledArray">LabeledArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.split">
+<span class="sig-name descname"><span class="pre">split</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.html#impy.collections.DataList" title="impy.collections.DataList"><span class="pre">DataList</span></a><span class="p"><span class="pre">[</span></span><span class="pre">Self</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.split"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.split" title="Permalink to this definition">¶</a></dt>
+<dd><p>Split n-dimensional image into (n-1)-dimensional images. This function is different from
+<cite>np.split</cite>, which split an array into smaller pieces (n-D to n-D).</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>axis</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Along which axis the original image will be split, by default “c”</p>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Separate images</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>list of arrays</p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LabeledArray.tile">
+<span class="sig-name descname"><span class="pre">tile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/arrays/labeledarray.html#LabeledArray.tile"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LabeledArray.tile" title="Permalink to this definition">¶</a></dt>
+<dd><p>Tile images in a certain order.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>shape</strong> (<em>tuple</em><em>[</em><em>int</em><em>, </em><em>int</em><em>]</em><em>, </em><em>optional</em>) – Grid shape. This parameter must be specified unless the length of <cite>along</cite> is 2.</p></li>
+<li><p><strong>along</strong> (<em>str</em><em>, </em><em>optional</em>) – Axis (Axes) over which will be iterated.</p></li>
+<li><p><strong>order</strong> (<em>str</em><em>, </em><em>{&quot;r&quot;</em><em>, </em><em>&quot;c&quot;}</em><em>, </em><em>optional</em>) – <p>Order of iteration. “r” means row-wise and “c” means column-wise.</p>
+<dl>
+<dt>row-wise</dt><dd><p>—–&gt;
+—–&gt;
+—–&gt;</p>
+</dd>
+<dt>column-wise</dt><dd><div class="line-block">
+<div class="line">| |</div>
+<div class="line">| |</div>
+</div>
+<p>v v v</p>
+</dd>
+</dl>
+</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Tiled array</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>Labeled</p>
+</dd>
+</dl>
+</dd></dl>
+
+</dd></dl>
+
+<dl class="py class">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.</span></span><span class="sig-name descname"><span class="pre">LazyImgArray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">obj</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DaskArray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">source</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metadata</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <a class="reference internal" href="#impy.arrays.axesmixin.AxesMixin" title="impy.arrays.axesmixin.AxesMixin"><code class="xref py py-class docutils literal notranslate"><span class="pre">AxesMixin</span></code></a></p>
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.GB">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">GB</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">float</span></em><a class="headerlink" href="#impy.arrays.LazyImgArray.GB" title="Permalink to this definition">¶</a></dt>
+<dd><p>Return the array size in GB.</p>
+</dd></dl>
+
+<dl class="py attribute">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.additional_props">
+<span class="sig-name descname"><span class="pre">additional_props</span></span><em class="property"><span class="w"> </span><span class="p"><span class="pre">=</span></span><span class="w"> </span><span class="pre">['_source',</span> <span class="pre">'_metadata',</span> <span class="pre">'_name']</span></em><a class="headerlink" href="#impy.arrays.LazyImgArray.additional_props" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.affine">
+<span class="sig-name descname"><span class="pre">affine</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">matrix</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rotation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shear</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">translation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">output_shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.affine"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.affine" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.affine. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Convert image by Affine transformation. 2D Affine transformation is written as:</p>
+<div class="math notranslate nohighlight">
+\[\begin{split}\begin{bmatrix} y'\\ x' \\1 \end{bmatrix} =
+\begin{bmatrix} A_{00} &amp; A_{01} &amp; A_{02} \\
+                A_{10} &amp; A_{11} &amp; A_{12} \\
+                    0 &amp;      0 &amp;      1  \end{bmatrix}
+                \begin{bmatrix} y \\x\\ 1 \end{bmatrix}\end{split}\]</div>
+<p>and similarly, n-D Affine transformation can be described as (n+1)-D matrix.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>matrix</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
+<li><p><strong>scale</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
+<li><p><strong>rotation</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
+<li><p><strong>shear</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
+<li><p><strong>translation</strong> – Affine transformation parameters. See <code class="docutils literal notranslate"><span class="pre">skimage.transform.AffineTransform</span></code> for details.</p></li>
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>output_shape</strong> (<em>tuple</em><em> of </em><em>int</em><em>, </em><em>optional</em>) – Shape of output array.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Transformed image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.apply_dask_func">
+<span class="sig-name descname"><span class="pre">apply_dask_func</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">funcname</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.apply_dask_func"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.apply_dask_func" title="Permalink to this definition">¶</a></dt>
+<dd><p>Apply dask array function to the connected dask array.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>funcname</strong> (<em>str</em>) – Name of function to apply.</p></li>
+<li><p><strong>args</strong> – Parameters that will be passed to <cite>funcname</cite>.</p></li>
+<li><p><strong>kwargs</strong> – Parameters that will be passed to <cite>funcname</cite>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Updated one</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.as_float">
+<span class="sig-name descname"><span class="pre">as_float</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.as_float"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.as_float" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.as_img_type">
+<span class="sig-name descname"><span class="pre">as_img_type</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dtype=&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.as_img_type"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.as_img_type" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.as_uint16">
+<span class="sig-name descname"><span class="pre">as_uint16</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.as_uint16"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.as_uint16" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.as_uint8">
+<span class="sig-name descname"><span class="pre">as_uint8</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.as_uint8"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.as_uint8" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.binning">
+<span class="sig-name descname"><span class="pre">binning</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">binsize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mean'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_edges</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.binning"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.binning" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.binning. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Binning of images. This function is similar to <code class="docutils literal notranslate"><span class="pre">rescale</span></code> but is strictly
+binned by <span class="math notranslate nohighlight">\(N \times N\)</span> blocks. Also, any numpy functions that accept
+“axis” argument are supported for reduce functions.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>binsize</strong> (<em>int</em><em>, </em><em>default is 2</em>) – Bin size, such as 2x2.</p></li>
+<li><p><strong>method</strong> (<em>str</em><em> or </em><em>callable</em><em>, </em><em>default is numpy.mean</em>) – Reduce function applied to each bin.</p></li>
+<li><p><strong>check_edges</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, only divisible <code class="docutils literal notranslate"><span class="pre">binsize</span></code> is accepted. If False, image is
+cropped at the end to match <cite>binsize</cite>.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Binned image</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.chunk_info">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">chunk_info</span></span><a class="headerlink" href="#impy.arrays.LazyImgArray.chunk_info" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.chunksize">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">chunksize</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">AxesTuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#impy.arrays.LazyImgArray.chunksize" title="Permalink to this definition">¶</a></dt>
+<dd><p>Chunk size of the array.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.chunksizeof">
+<span class="sig-name descname"><span class="pre">chunksizeof</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.chunksizeof"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.chunksizeof" title="Permalink to this definition">¶</a></dt>
+<dd><p>Get the chunk size of the given axis</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.chunksizesof">
+<span class="sig-name descname"><span class="pre">chunksizesof</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.chunksizesof"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.chunksizesof" title="Permalink to this definition">¶</a></dt>
+<dd><p>Get the chunk sizes of the given axes</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.closing">
+<span class="sig-name descname"><span class="pre">closing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.closing"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.closing" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.closing. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Morphological closing.</p>
+<p>If input is binary image, the running function will automatically switched to
+<code class="docutils literal notranslate"><span class="pre">binary_closing</span></code> to speed up calculation.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.compute">
+<span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">ignore_limit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.compute" title="Permalink to this definition">¶</a></dt>
+<dd><p>Compute all the task and convert the result into ImgArray. If image size overwhelms MAX_GB
+then MemoryError is raised.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.convolve">
+<span class="sig-name descname"><span class="pre">convolve</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kernel</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'reflect'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.convolve"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.convolve" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.convolve. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>General linear convolution by running kernel filtering.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>kernel</strong> (<em>array-like</em>) – Convolution kernel.</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Convolved image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.crop_center">
+<span class="sig-name descname"><span class="pre">crop_center</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.5</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.crop_center"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.crop_center" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of LabeledArray.crop_center. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Crop out the center of an image.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>scale</strong> (<em>float</em><em> or </em><em>array-like</em><em>, </em><em>default is 0.5</em>) – Scale of the cropped image. If an array is given, each axis will be cropped in different scales,
+using each value respectively.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>CroppedImage</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>Self</p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<ol class="arabic">
+<li><p>Create a <span class="math notranslate nohighlight">\(512\times512\)</span> image from a <span class="math notranslate nohighlight">\(1024\times1024\)</span> image.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img_cropped</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">crop_center</span><span class="p">(</span><span class="n">scale</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
+</pre></div>
+</div>
+</li>
+<li><p>Create a <span class="math notranslate nohighlight">\(21\times256\times256\)</span> image from a <span class="math notranslate nohighlight">\(63\times1024\times1024\)</span> image.</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img_cropped</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">crop_center</span><span class="p">(</span><span class="n">scale</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="o">/</span><span class="mi">3</span><span class="p">,</span> <span class="mi">1</span><span class="o">/</span><span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="o">/</span><span class="mi">2</span><span class="p">])</span>
+</pre></div>
+</div>
+</li>
+</ol>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.dilation">
+<span class="sig-name descname"><span class="pre">dilation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.dilation"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.dilation" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.dilation. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Morphological dilation. If input is binary image, the running function will automatically switched to
+<code class="docutils literal notranslate"><span class="pre">binary_dilation</span></code> to speed up calculation.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.drift_correction">
+<span class="sig-name descname"><span class="pre">drift_correction</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Coords</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ref</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray"><span class="pre">ImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">zero_ave</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">affine_kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.drift_correction"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.drift_correction" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.drift_correction. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Drift correction using iterative Affine translation. If translation vectors <code class="docutils literal notranslate"><span class="pre">shift</span></code>
+is not given, then it will be determined using <code class="docutils literal notranslate"><span class="pre">track_drift</span></code> method of ImgArray.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>shift</strong> (<em>DataFrame</em><em> or </em><em>(</em><em>N</em><em>, </em><em>D</em><em>) </em><em>array</em><em>, </em><em>optional</em>) – Translation vectors. If DataFrame, it must have columns named with all the symbols
+contained in <code class="docutils literal notranslate"><span class="pre">dims</span></code>.</p></li>
+<li><p><strong>ref</strong> (<a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray"><em>ImgArray</em></a><em>, </em><em>optional</em>) – The reference n-D image to determine drift, if <code class="docutils literal notranslate"><span class="pre">shift</span></code> was not given.</p></li>
+<li><p><strong>zero_ave</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, average shift will be zero.</p></li>
+<li><p><strong>along</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Along which axis drift will be corrected.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+<li><p><strong>affine_kwargs</strong> – Keyword arguments that will be passed to <code class="docutils literal notranslate"><span class="pre">warp</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Corrected image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<dl>
+<dt>Drift correction of multichannel image using the first channel as the reference.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">drift_correction</span><span class="p">(</span><span class="n">ref</span><span class="o">=</span><span class="n">img</span><span class="p">[</span><span class="s2">&quot;c=0&quot;</span><span class="p">])</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.dtype">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">dtype</span></span><a class="headerlink" href="#impy.arrays.LazyImgArray.dtype" title="Permalink to this definition">¶</a></dt>
+<dd><p>Data type of the array</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.edge_filter">
+<span class="sig-name descname"><span class="pre">edge_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'sobel'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.edge_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.edge_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.edge_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Sobel filter. This filter is useful for edge detection.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>method</strong> (<em>str</em><em>, </em><em>{&quot;sobel&quot;</em><em>, </em><em>&quot;farid&quot;</em><em>, </em><em>&quot;scharr&quot;</em><em>, </em><em>&quot;prewitt&quot;}</em><em>, </em><em>default is &quot;sobel&quot;</em>) – Edge operator name.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.erosion">
+<span class="sig-name descname"><span class="pre">erosion</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.erosion"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.erosion" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.erosion. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Morphological erosion.</p>
+<p>If input is binary image, the running function will automatically switched to
+<code class="docutils literal notranslate"><span class="pre">binary_erosion</span></code> to speed up calculation.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.fft">
+<span class="sig-name descname"><span class="pre">fft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'same'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.fft"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.fft" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.fft. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Fast Fourier transformation. This function returns complex array, which is
+inconpatible with some ImgArray functions.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable</em><em> of </em><em>int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
+- integers: padded or cropped to the specified shape.
+- “square”: padded to smallest 2^N-long square.
+- “same” (default): no padding or cropping.</p></li>
+<li><p><strong>shift</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, call <code class="docutils literal notranslate"><span class="pre">np.fft.fftshift</span></code> in the end.</p></li>
+<li><p><strong>double_precision</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, FFT will be calculated using 64-bit float and 128-bit complex.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>FFT image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><code class="xref py py-obj docutils literal notranslate"><span class="pre">local_dft</span></code></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.gaussian_filter">
+<span class="sig-name descname"><span class="pre">gaussian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.gaussian_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.gaussian_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.gaussian_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Run Gaussian filter (Gaussian blur).</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Standard deviation(s) of Gaussian filter.
+If a scalar value is given, same standard deviation will applied to all the spatial dimensions.</p></li>
+<li><p><strong>fourier</strong> (<em>bool</em><em>, </em><em>default is False</em>) – Whether to run the convolution in Fourier space. This option is useful when the kernel or the image is large.
+Note that discrete Fourier transform assumes that the image is periodic, so that if intensities of the input image are not consecutive at img[0] and img[-1], you may get some artifacts at the boundary.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.gb">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">gb</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">float</span></em><a class="headerlink" href="#impy.arrays.LazyImgArray.gb" title="Permalink to this definition">¶</a></dt>
+<dd><p>Return the array size in GB.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.ifft">
+<span class="sig-name descname"><span class="pre">ifft</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">real</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shift</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.ifft"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.ifft" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.ifft. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Fast Inverse Fourier transformation. Complementary function with <cite>fft()</cite>.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>real</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, only the real part is returned.</p></li>
+<li><p><strong>shift</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, call <code class="docutils literal notranslate"><span class="pre">np.fft.ifftshift</span></code> at the first.</p></li>
+<li><p><strong>double_precision</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, FFT will be calculated using 64-bit float and 128-bit complex.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>IFFT image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.imsave">
+<span class="sig-name descname"><span class="pre">imsave</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">save_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Path</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">overwrite</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.imsave"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.imsave" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of LabeledArray.imsave. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Save image at the same directory as the original image by default.</p>
+<p>For tif file format, if the image contains wrong axes for ImageJ (= except for tzcyx),
+then it will converted automatically if possible. For mrc file format, only zyx and yx is
+allowed. zyx-scale is also saved.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>save_path</strong> (<em>str</em>) – File name.</p></li>
+<li><p><strong>dtype</strong> (<em>dtype-like</em><em>, </em><em>optional</em>) – In what data type img will be saved.</p></li>
+<li><p><strong>overwrite</strong> (<em>bool</em><em>, </em><em>default is True</em>) – Whether to overwrite the file if it already exists.</p></li>
+</ul>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.iradon">
+<span class="sig-name descname"><span class="pre">iradon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degrees</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">central_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'y'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">degree_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">height_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">height</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'hamming'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.iradon"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.iradon" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.iradon. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Inverse Radon transformation (weighted back projection) of a tile series.</p>
+<p>Input array must be a tilt series of 1D or 2D images. They are back-
+projected into a 2D or 3D image with arbitrary height.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>degrees</strong> (<em>sequence</em><em> of </em><em>float</em>) – Projection angles in degree. Length must match the length of the degree
+axis of the input image.</p></li>
+<li><p><strong>central_axis</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Axis parallel to the rotation axis.</p></li>
+<li><p><strong>degree_axis</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Axis of rotation degree. By default, the first axis will be used.</p></li>
+<li><p><strong>height_axis</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Axis that will be used to label the new axis after reconstruction. For
+instance, if input image has axes <code class="docutils literal notranslate"><span class="pre">[&quot;degree&quot;,</span> <span class="pre">&quot;y&quot;,</span> <span class="pre">&quot;x&quot;]</span></code> and
+<code class="docutils literal notranslate"><span class="pre">height_axis=&quot;z&quot;</span></code> then reconstructed image will have axes
+<code class="docutils literal notranslate"><span class="pre">[&quot;z&quot;,</span> <span class="pre">&quot;y&quot;,</span> <span class="pre">&quot;x&quot;]</span></code>. By default, “y” will be used for 2D input or “z” for
+3D input.</p></li>
+<li><p><strong>height</strong> (<em>int</em><em>, </em><em>optional</em>) – Height of reconstruction. By default, size equal to the axis perpendicular
+to the rotation axis will be used.</p></li>
+<li><p><strong>window</strong> (<em>str</em><em>, </em><em>default is &quot;hamming&quot;</em>) – Window function that will be applied to the Fourier domain along the axis
+perpendicular to the rotation axis.</p></li>
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Reconstruction.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.LazyImgArray.radon" title="impy.arrays.LazyImgArray.radon"><code class="xref py py-obj docutils literal notranslate"><span class="pre">radon</span></code></a></p>
+</div>
+</dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.itemsize">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">itemsize</span></span><a class="headerlink" href="#impy.arrays.LazyImgArray.itemsize" title="Permalink to this definition">¶</a></dt>
+<dd><p>Size of each element in bytes.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.kalman_filter">
+<span class="sig-name descname"><span class="pre">kalman_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">gain</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">noise_var</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'t'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.kalman_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.kalman_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.kalman_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Kalman filter for image smoothing. This function is same as “Kalman Stack Filter” in ImageJ but support
+batch processing. This filter is useful for preprocessing of particle tracking.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>gain</strong> (<em>float</em><em>, </em><em>default is 0.8</em>) – Filter gain.</p></li>
+<li><p><strong>noise_var</strong> (<em>float</em><em>, </em><em>default is 0.05</em>) – Initial estimate of noise variance.</p></li>
+<li><p><strong>along</strong> (<em>str</em><em>, </em><em>default is &quot;t&quot;</em>) – Which axis will be the time axis.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.laplacian_filter">
+<span class="sig-name descname"><span class="pre">laplacian_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.laplacian_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.laplacian_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.laplacian_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Edge detection using Laplacian filter. Kernel is made by <cite>skimage</cite>’s function.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>int</em><em>, </em><em>default is 1</em>) – Radius of kernel. Shape of kernel will be (2*radius+1, 2*radius+1).</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.lucy">
+<span class="sig-name descname"><span class="pre">lucy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">niter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1e-05</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.lucy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.lucy" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.lucy. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Deconvolution of N-dimensional image, using Richardson-Lucy’s algorithm.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>psf</strong> (<em>ndarray</em><em> or </em><em>callable</em>) – Point spread function. If a function is given, <cite>psf(shape)</cite> will be
+called to generate the PSF.</p></li>
+<li><p><strong>niter</strong> (<em>int</em><em>, </em><em>default is 50.</em>) – Number of iterations.</p></li>
+<li><p><strong>eps</strong> (<em>float</em><em>, </em><em>default is 1e-5</em>) – During deconvolution, division by small values in the convolve image
+of estimation and PSF may cause divergence. Therefore, division by
+values under <cite>eps</cite> is substituted to zero.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Deconvolved image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><code class="xref py py-obj docutils literal notranslate"><span class="pre">lucy_tv</span></code>, <a class="reference internal" href="#impy.arrays.LazyImgArray.wiener" title="impy.arrays.LazyImgArray.wiener"><code class="xref py py-obj docutils literal notranslate"><span class="pre">wiener</span></code></a></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.max">
+<span class="sig-name descname"><span class="pre">max</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keepdims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.max"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.max" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of MetaArray.max. This function returns the same result but the value is evaluated lazily as an dask array.
+Maximum value of the array along a given axis.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.mean">
+<span class="sig-name descname"><span class="pre">mean</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keepdims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.mean"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.mean" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of MetaArray.mean. This function returns the same result but the value is evaluated lazily as an dask array.
+Mean value of the array along a given axis.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.mean_filter">
+<span class="sig-name descname"><span class="pre">mean_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.mean_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.mean_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.mean_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Mean filter. Kernel is filled with same values.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.median_filter">
+<span class="sig-name descname"><span class="pre">median_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.median_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.median_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.median_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Running multi-dimensional median filter.</p>
+<p>This filter is useful for deleting outliers generated by noise.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.metadata">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">metadata</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#impy.arrays.LazyImgArray.metadata" title="Permalink to this definition">¶</a></dt>
+<dd><p>Metadata dictionary of the array.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.min">
+<span class="sig-name descname"><span class="pre">min</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keepdims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.min"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.min" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of MetaArray.min. This function returns the same result but the value is evaluated lazily as an dask array.
+Minimum value of the array along a given axis.</p>
+</dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.name">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">str</span></em><a class="headerlink" href="#impy.arrays.LazyImgArray.name" title="Permalink to this definition">¶</a></dt>
+<dd><p>Name of the array.</p>
+</dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.ndim">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">ndim</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">int</span></em><a class="headerlink" href="#impy.arrays.LazyImgArray.ndim" title="Permalink to this definition">¶</a></dt>
+<dd><p>Number of dimensions of the array.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.opening">
+<span class="sig-name descname"><span class="pre">opening</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.opening"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.opening" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.opening. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Morphological opening. If input is binary image, the running function will automatically switched to
+<code class="docutils literal notranslate"><span class="pre">binary_opening</span></code> to speed up calculation.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>optional</em>) – <p>Radius of kernel structure. For instance, if input has two spatial dimensions, <code class="docutils literal notranslate"><span class="pre">radius=1</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+<p>and <code class="docutils literal notranslate"><span class="pre">radius=1.8</span></code> gives a structure</p>
+<blockquote>
+<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
+ <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
+</pre></div>
+</div>
+</div></blockquote>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.pad">
+<span class="sig-name descname"><span class="pre">pad</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pad_width</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.pad"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.pad" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.pad. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Pad image only for spatial dimensions.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>pad_width</strong> – See documentation of np.pad().</p></li>
+<li><p><strong>mode</strong> – See documentation of np.pad().</p></li>
+<li><p><strong>**kwargs</strong> – See documentation of np.pad().</p></li>
+<li><p><strong>dims</strong> (<em>int</em><em> or </em><em>str</em><em>, </em><em>optional</em>) – Which dimension to pad.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Padded image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<p>Suppose <code class="docutils literal notranslate"><span class="pre">img</span></code> has zyx-axes.</p>
+<ol class="arabic">
+<li><dl>
+<dt>Padding 5 pixels in zyx-direction:</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">pad</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</li>
+<li><dl>
+<dt>Padding 5 pixels in yx-direction:</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">pad</span><span class="p">(</span><span class="mi">5</span><span class="p">,</span> <span class="n">dims</span><span class="o">=</span><span class="s2">&quot;yx&quot;</span><span class="p">)</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</li>
+<li><dl>
+<dt>Padding 5 pixels in yx-direction and 2 pixels in z-direction:</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">pad</span><span class="p">([(</span><span class="mi">5</span><span class="p">,</span><span class="mi">5</span><span class="p">),</span> <span class="p">(</span><span class="mi">4</span><span class="p">,</span><span class="mi">4</span><span class="p">),</span> <span class="p">(</span><span class="mi">4</span><span class="p">,</span><span class="mi">4</span><span class="p">)])</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</li>
+<li><dl>
+<dt>Padding 10 pixels in z-(-)-direction and 5 pixels in z-(+)-direction.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">pad</span><span class="p">([(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">5</span><span class="p">)],</span> <span class="n">dims</span><span class="o">=</span><span class="s2">&quot;z&quot;</span><span class="p">)</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</li>
+</ol>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.power_spectra">
+<span class="sig-name descname"><span class="pre">power_spectra</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'same'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">zero_norm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.power_spectra"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.power_spectra" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.power_spectra. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Return n-D power spectra of images, which is defined as:</p>
+<div class="math notranslate nohighlight">
+\[P = Re(F[I_{img}])^2 + Im(F[I_{img}])^2\]</div>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>shape</strong> (<em>int</em><em>, </em><em>iterable</em><em> of </em><em>int</em><em>, </em><em>&quot;square&quot;</em><em> or </em><em>&quot;same&quot;</em>) – Output shape. Input image is padded or cropped according to this value:
+- integers: padded or cropped to the specified shape.
+- “square”: padded to smallest 2^N-long square.
+- “same” (default): no padding or cropping.</p></li>
+<li><p><strong>norm</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, maximum value of power spectra is adjusted to 1.</p></li>
+<li><p><strong>double_precision</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, FFT will be calculated using 64-bit float and 128-bit complex.</p></li>
+<li><p><strong>shift</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, call <code class="docutils literal notranslate"><span class="pre">np.fft.fftshift</span></code> at the first.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Power spectra</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><code class="xref py py-obj docutils literal notranslate"><span class="pre">local_power_spectra</span></code></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.proj">
+<span class="sig-name descname"><span class="pre">proj</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mean'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.proj"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.proj" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.proj. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Projection along any axis.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>axis</strong> (<em>str</em><em>, </em><em>optional</em>) – Along which axis projection will be calculated. If None, most plausible one will be chosen.</p></li>
+<li><p><strong>method</strong> (<em>str</em><em> or </em><em>callable</em><em>, </em><em>default is mean-projection.</em>) – Projection method. If str is given, it will converted to numpy function.</p></li>
+<li><p><strong>mask</strong> (<em>array-like</em><em>, </em><em>optional</em>) – If provided, input image will be converted to np.ma.array and <code class="docutils literal notranslate"><span class="pre">method</span></code> will also be interpreted
+as an masked functio if possible.</p></li>
+<li><p><strong>**kwargs</strong> – Other keyword arguments that will passed to projection function.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Projected image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.radon">
+<span class="sig-name descname"><span class="pre">radon</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">degrees</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">central_axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.radon"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.radon" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.radon. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Discrete Radon transformation of 2D or 3D image.</p>
+<p>Radon transformation is a list of projection of a same image from different angles.
+It generates tomographic n-D image slices from (n+1)-D image.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>degrees</strong> (<em>float</em><em> or </em><em>iterable</em><em> of </em><em>float</em>) – Rotation angles around the central axis in degrees.</p></li>
+<li><p><strong>central_axis</strong> (<em>axis-like</em><em> or </em><em>sequence</em><em> of </em><em>float</em><em>, </em><em>optional</em>) – Vector that defines the central axis of rotation.</p></li>
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Tomographic image slices. The first spatial axis (“z” for zyx-image) will be dropped.
+If sequence of float is given as <code class="docutils literal notranslate"><span class="pre">degrees</span></code>, “degree” axis will be newly added at
+the position 0. For instance, if a zyx-image and <code class="docutils literal notranslate"><span class="pre">degrees=np.linspace(0,</span> <span class="pre">180,</span> <span class="pre">100)</span></code>
+are given, returned image has axes [“degree”, “y”, “x”].</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.LazyImgArray.iradon" title="impy.arrays.LazyImgArray.iradon"><code class="xref py py-obj docutils literal notranslate"><span class="pre">iradon</span></code></a></p>
+</div>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.rechunk">
+<span class="sig-name descname"><span class="pre">rechunk</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">block_size_limit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">balance</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.rechunk"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.rechunk" title="Permalink to this definition">¶</a></dt>
+<dd><p>Rechunk the bound dask array.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>chunks</strong> – Passed directly to dask.array’s rechunk</p></li>
+<li><p><strong>threshold</strong> – Passed directly to dask.array’s rechunk</p></li>
+<li><p><strong>block_size_limit</strong> – Passed directly to dask.array’s rechunk</p></li>
+<li><p><strong>balance</strong> – Passed directly to dask.array’s rechunk</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Rechunked dask array is bound.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.release">
+<span class="sig-name descname"><span class="pre">release</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.release"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.release" title="Permalink to this definition">¶</a></dt>
+<dd><p>Compute all the tasks and store the data in memory map, and read it as a dask array
+again.</p>
+</dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.shape">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">shape</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">AxesTuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#impy.arrays.LazyImgArray.shape" title="Permalink to this definition">¶</a></dt>
+<dd><p>Shape of the array.</p>
+</dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.size">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">size</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">int</span></em><a class="headerlink" href="#impy.arrays.LazyImgArray.size" title="Permalink to this definition">¶</a></dt>
+<dd><p>Total number of elements in the array.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.sort_axes">
+<span class="sig-name descname"><span class="pre">sort_axes</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.sort_axes"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.sort_axes" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of MetaArray.sort_axes. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Sort image dimensions to ptzcyx-order</p>
+<dl class="field-list simple">
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
+<dd class="field-odd"><p>Sorted image</p>
+</dd>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
+<dd class="field-even"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.source">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">source</span></span><a class="headerlink" href="#impy.arrays.LazyImgArray.source" title="Permalink to this definition">¶</a></dt>
+<dd><p>The source file path.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.spline_filter">
+<span class="sig-name descname"><span class="pre">spline_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'mirror'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.spline_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.spline_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of LabeledArray.spline_filter. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Run spline filter.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.std">
+<span class="sig-name descname"><span class="pre">std</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keepdims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.std"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.std" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of MetaArray.std. This function returns the same result but the value is evaluated lazily as an dask array.
+Standard deviation of the array along a given axis.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.sum">
+<span class="sig-name descname"><span class="pre">sum</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">keepdims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.sum"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.sum" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of MetaArray.sum. This function returns the same result but the value is evaluated lazily as an dask array.
+Sum value of the array along a given axis.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.threshold">
+<span class="sig-name descname"><span class="pre">threshold</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">thr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.threshold"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.threshold" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.threshold. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Apply thresholding to the image and create a binary image.</p>
+<p>The threshold value can be given with a float or a string that indicates what
+thresholding method will be used.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>thr</strong> (<em>float</em><em> or </em><em>str</em><em>, </em><em>optional</em>) – Threshold value, percentage or thresholding algorithm.</p></li>
+<li><p><strong>along</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Dimensions that will not share the same threshold. For instance, if
+<code class="docutils literal notranslate"><span class="pre">along=&quot;c&quot;</span></code> then threshold intensities are determined for every channel.
+If <code class="docutils literal notranslate"><span class="pre">thr</span></code> is float, <code class="docutils literal notranslate"><span class="pre">along</span></code> will be ignored.</p></li>
+<li><p><strong>**kwargs</strong> – Keyword arguments that will passed to function indicated in ‘method’.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Boolian array.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Examples</p>
+<dl>
+<dt>Substitute outliers to 0.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">thr</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">threshold</span><span class="p">(</span><span class="s2">&quot;99%&quot;</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="p">[</span><span class="n">thr</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py attribute">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.tiled">
+<span class="sig-name descname"><span class="pre">tiled</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.tiled.TiledAccessor" title="impy.arrays.tiled.TiledAccessor"><span class="pre">TiledAccessor</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray"><span class="pre">LazyImgArray</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#impy.arrays.LazyImgArray.tiled" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.tiled_lowpass_filter">
+<span class="sig-name descname"><span class="pre">tiled_lowpass_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cutoff</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">overlap</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">16</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.tiled_lowpass_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.tiled_lowpass_filter" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.track_drift">
+<span class="sig-name descname"><span class="pre">track_drift</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">DaskArray</span></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.track_drift"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.track_drift" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.track_drift. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Calculate yx-directional drift using the method equivalent to
+<code class="docutils literal notranslate"><span class="pre">skimage.registration.phase_cross_correlation</span></code>.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>along</strong> (<em>AxisLike</em><em>, </em><em>optional</em>) – Along which axis drift will be calculated.</p></li>
+<li><p><strong>show_drift</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, plot the result.</p></li>
+<li><p><strong>upsample_factor</strong> (<em>int</em><em>, </em><em>default is 10</em>) – Up-sampling factor when calculating phase cross correlation.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>DataFrame structure with x,y columns</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.transpose">
+<span class="sig-name descname"><span class="pre">transpose</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.transpose"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.transpose" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of MetaArray.transpose. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>change the order of image dimensions.
+‘axes’ will also be arranged.</p>
+</dd></dl>
+
+<dl class="py attribute">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.value">
+<span class="sig-name descname"><span class="pre">value</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">DaskArray</span></em><a class="headerlink" href="#impy.arrays.LazyImgArray.value" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.LazyImgArray.wiener">
+<span class="sig-name descname"><span class="pre">wiener</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">psf</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lmd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/lazy.html#LazyImgArray.wiener"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.LazyImgArray.wiener" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of ImgArray.wiener. This function returns the same result but the value is evaluated lazily as an dask array.</p>
+<p>Classical wiener deconvolution. This algorithm has the serious ringing problem
+if parameters are set to wrong values.</p>
+<p><span class="math notranslate nohighlight">\(F[Y_{res}] = \frac{F[Y_{obs}] \cdot \bar{H}}{|H|^2 + \lambda}\)</span></p>
+<p><span class="math notranslate nohighlight">\(Y_{obs}\)</span>: observed image;
+<span class="math notranslate nohighlight">\(Y_{res}\)</span>: restored image;
+<span class="math notranslate nohighlight">\(H\)</span> : FFT of point spread function (PSF);</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>psf</strong> (<em>ndarray</em><em> or </em><em>callable</em>) – Point spread function. If a function is given, <cite>psf(shape)</cite> will be
+called to generate the PSF.</p></li>
+<li><p><strong>lmd</strong> (<em>float</em><em>, </em><em>default is 0.1</em>) – Constant value used in the deconvolution. See Formulation below.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, input itself is updated to the output.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Deconvolved image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.LazyImgArray" title="impy.arrays.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><a class="reference internal" href="#impy.arrays.LazyImgArray.lucy" title="impy.arrays.LazyImgArray.lucy"><code class="xref py py-obj docutils literal notranslate"><span class="pre">lucy</span></code></a>, <code class="xref py py-obj docutils literal notranslate"><span class="pre">lucy_tv</span></code></p>
+</div>
+</dd></dl>
+
+</dd></dl>
+
+<dl class="py class">
+<dt class="sig sig-object py" id="impy.arrays.PhaseArray">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.</span></span><span class="sig-name descname"><span class="pre">PhaseArray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">obj</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">source</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metadata</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">unit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'rad'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">border</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.PhaseArray" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <a class="reference internal" href="#impy.arrays.labeledarray.LabeledArray" title="impy.arrays.labeledarray.LabeledArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">LabeledArray</span></code></a></p>
+<dl class="py attribute">
+<dt class="sig sig-object py" id="impy.arrays.PhaseArray.additional_props">
+<span class="sig-name descname"><span class="pre">additional_props</span></span><em class="property"><span class="w"> </span><span class="p"><span class="pre">=</span></span><span class="w"> </span><span class="pre">['_source',</span> <span class="pre">'_metadata',</span> <span class="pre">'_name',</span> <span class="pre">'unit',</span> <span class="pre">'border']</span></em><a class="headerlink" href="#impy.arrays.PhaseArray.additional_props" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.PhaseArray.as_exp">
+<span class="sig-name descname"><span class="pre">as_exp</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.ImgArray" title="impy.arrays.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.as_exp"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.PhaseArray.as_exp" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.PhaseArray.binning">
+<span class="sig-name descname"><span class="pre">binning</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">binsize</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_edges</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.binning"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.PhaseArray.binning" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py attribute">
+<dt class="sig sig-object py" id="impy.arrays.PhaseArray.border">
+<span class="sig-name descname"><span class="pre">border</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#impy.arrays.PhaseArray.border" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.PhaseArray.deg2rad">
+<span class="sig-name descname"><span class="pre">deg2rad</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.deg2rad"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.PhaseArray.deg2rad" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.PhaseArray.imshow">
+<span class="sig-name descname"><span class="pre">imshow</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">label</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.3</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.imshow"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.PhaseArray.imshow" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.PhaseArray.map_coordinates">
+<span class="sig-name descname"><span class="pre">map_coordinates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coordinates</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'reflect'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'constant'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'nearest'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'mirror'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'wrap'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'constant'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefilter</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.map_coordinates"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.PhaseArray.map_coordinates" title="Permalink to this definition">¶</a></dt>
+<dd><p>Coordinate mapping in the image. See <code class="docutils literal notranslate"><span class="pre">scipy.ndimage.map_coordinates</span></code>.</p>
+<p>For a <code class="docutils literal notranslate"><span class="pre">PhaseArray</span></code>, standard interpolation does not work because of its specific
+addition rule. Phase image is first converted into a complex array by <span class="math notranslate nohighlight">\(e^{-i \psi}\)</span>
+and the phase is restored by logarithm after interpolation.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>coordinates</strong> (<em>ArrayLike</em>) – Interpolation coordinates. Must be (D, N) or (D, X_1, …, X_D) shape.</p></li>
+<li><p><strong>mode</strong> (<em>{&quot;reflect&quot;</em><em>, </em><em>&quot;constant&quot;</em><em>, </em><em>&quot;nearest&quot;</em><em>, </em><em>&quot;mirror&quot;</em><em>, </em><em>&quot;wrap&quot;}</em>) – Edge padding mode.</p></li>
+<li><p><strong>cval</strong> (<em>float</em><em>, </em><em>default is 0.0</em>) – Constant value for constant padding mode.</p></li>
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – <p>Spline interpolation order.
+For more details see <a class="reference external" href="https://scikit-image.org/docs/dev/api/skimage.transform.html#skimage.transform.warp">here</a>.</p>
+</p></li>
+<li><p><strong>prefilter</strong> (<em>bool</em><em>, </em><em>optional</em>) – Spline prefilter applied to the array. By default set to True if <code class="docutils literal notranslate"><span class="pre">order</span></code> is larger
+than 1.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions. If string is given, each symbol is interpeted as an axis name of spatial dimensions. If an integer is given, it is interpreted as the number of spatial dimensions.
+For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Transformed image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.PhaseArray" title="impy.arrays.PhaseArray">PhaseArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.PhaseArray.mean_filter">
+<span class="sig-name descname"><span class="pre">mean_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">update</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.mean_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.PhaseArray.mean_filter" title="Permalink to this definition">¶</a></dt>
+<dd><p>Mean filter using phase averaging method:</p>
+<p><span class="math notranslate nohighlight">\(\arg{\sum_{k}{e^{i X_k}}}\)</span></p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>radius</strong> (<em>float</em><em>, </em><em>default is 1</em>) – Radius of kernel.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em> or </em><em>int</em><em>, </em><em>optional</em>) – Spatial dimensions.</p></li>
+<li><p><strong>update</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If update self to filtered image.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Filtered image.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.PhaseArray" title="impy.arrays.PhaseArray">PhaseArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py property">
+<dt class="sig sig-object py" id="impy.arrays.PhaseArray.periodicity">
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">periodicity</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">float</span></em><a class="headerlink" href="#impy.arrays.PhaseArray.periodicity" title="Permalink to this definition">¶</a></dt>
+<dd><p>Return the periodicity of current border.</p>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.PhaseArray.rad2deg">
+<span class="sig-name descname"><span class="pre">rad2deg</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.phasearray.PhaseArray" title="impy.arrays.phasearray.PhaseArray"><span class="pre">PhaseArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.rad2deg"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.PhaseArray.rad2deg" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.PhaseArray.regionprops">
+<span class="sig-name descname"><span class="pre">regionprops</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">properties</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">('phase_mean',)</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">extra_properties</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.html#impy.collections.DataDict" title="impy.collections.DataDict"><span class="pre">DataDict</span></a><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.regionprops"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.PhaseArray.regionprops" title="Permalink to this definition">¶</a></dt>
+<dd><p>Measure region properties.</p>
+<p>Run <code class="docutils literal notranslate"><span class="pre">skimage</span></code>’s <code class="docutils literal notranslate"><span class="pre">regionprops()</span></code> function and return the results as PropArray, so
+that you can access using flexible slicing. For example, if a tcyx-image is
+analyzed with <code class="docutils literal notranslate"><span class="pre">properties=(&quot;X&quot;,</span> <span class="pre">&quot;Y&quot;)</span></code>, then you can get X’s time-course profile
+of channel 1 at label 3 by <code class="docutils literal notranslate"><span class="pre">prop[&quot;X&quot;][&quot;N=5;c=1&quot;]</span></code> or <code class="docutils literal notranslate"><span class="pre">prop.X[&quot;N=5;c=1&quot;]</span></code>.
+In PhaseArray, instead of mean_intensity you should use “phase_mean”. The
+phase_mean function is included so that it can be passed in <code class="docutils literal notranslate"><span class="pre">properties</span></code> argument.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>properties</strong> (<em>iterable</em><em>, </em><em>optional</em>) – properties to analyze, see skimage.measure.regionprops.</p></li>
+<li><p><strong>extra_properties</strong> (<em>iterable</em><em> of </em><em>callable</em><em>, </em><em>optional</em>) – extra properties to analyze, see skimage.measure.regionprops.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
+<dd class="field-even"><p><a class="reference internal" href="impy.html#impy.collections.DataDict" title="impy.collections.DataDict">DataDict</a> of <a class="reference internal" href="#impy.arrays.PropArray" title="impy.arrays.PropArray">PropArray</a></p>
+</dd>
+</dl>
+<p class="rubric">Example</p>
+<dl>
+<dt>Measure region properties around single molecules.</dt><dd><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">coords</span> <span class="o">=</span> <span class="n">reference_img</span><span class="o">.</span><span class="n">centroid_sm</span><span class="p">()</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">img</span><span class="o">.</span><span class="n">specify</span><span class="p">(</span><span class="n">coords</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">labeltype</span><span class="o">=</span><span class="s2">&quot;circle&quot;</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">props</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">regionprops</span><span class="p">()</span>
+</pre></div>
+</div>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.PhaseArray.reslice">
+<span class="sig-name descname"><span class="pre">reslice</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">src</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dst</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.reslice"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.PhaseArray.reslice" title="Permalink to this definition">¶</a></dt>
+<dd><p>Measure line profile iteratively for every slice of image.</p>
+<p>Because input is phase, we can not apply standard interpolation to calculate
+intensities on float-coordinates.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>src</strong> (<em>array-like</em>) – Source coordinate.</p></li>
+<li><p><strong>dst</strong> (<em>array-like</em>) – Destination coordinate.</p></li>
+<li><p><strong>order</strong> (<em>int</em><em>, </em><em>default is 1</em>) – Spline interpolation order.</p></li>
+<li><p><strong>dims</strong> (<em>int</em><em> or </em><em>str</em><em>, </em><em>optional</em>) – Spatial dimensions.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Line scans.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="#impy.arrays.PropArray" title="impy.arrays.PropArray">PropArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.PhaseArray.set_border">
+<span class="sig-name descname"><span class="pre">set_border</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">a</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">b</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="reference internal" href="../_modules/impy/arrays/phasearray.html#PhaseArray.set_border"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.PhaseArray.set_border" title="Permalink to this definition">¶</a></dt>
+<dd><p>Set new border safely.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>a</strong> (<em>float</em>) – New lower border.</p></li>
+<li><p><strong>b</strong> (<em>float</em>) – New higher border.</p></li>
+</ul>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py attribute">
+<dt class="sig sig-object py" id="impy.arrays.PhaseArray.unit">
+<span class="sig-name descname"><span class="pre">unit</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">str</span></em><a class="headerlink" href="#impy.arrays.PhaseArray.unit" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+</dd></dl>
+
+<dl class="py class">
+<dt class="sig sig-object py" id="impy.arrays.PropArray">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.arrays.</span></span><span class="sig-name descname"><span class="pre">PropArray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">obj</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">source</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">metadata</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">propname</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/specials.html#PropArray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.PropArray" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">MetaArray</span></code></a></p>
+<dl class="py attribute">
+<dt class="sig sig-object py" id="impy.arrays.PropArray.additional_props">
+<span class="sig-name descname"><span class="pre">additional_props</span></span><em class="property"><span class="w"> </span><span class="p"><span class="pre">=</span></span><span class="w"> </span><span class="pre">['_source',</span> <span class="pre">'_metadata',</span> <span class="pre">'_name',</span> <span class="pre">'propname']</span></em><a class="headerlink" href="#impy.arrays.PropArray.additional_props" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.PropArray.as_frame">
+<span class="sig-name descname"><span class="pre">as_frame</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">colname</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'f'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.frame.html#impy.frame.frames.AxesFrame" title="impy.frame.frames.AxesFrame"><span class="pre">AxesFrame</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/specials.html#PropArray.as_frame"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.PropArray.as_frame" title="Permalink to this definition">¶</a></dt>
+<dd><p>N-dimensional data to DataFrame. The intensity data is stored in the <cite>colname</cite> column.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><p><strong>colname</strong> (<em>str</em><em>, </em><em>default is &quot;f&quot;</em>) – The name of new column.</p>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>DataFrame with PropArray data.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.frame.html#impy.frame.frames.AxesFrame" title="impy.frame.frames.AxesFrame">AxesFrame</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.PropArray.curve_fit">
+<span class="sig-name descname"><span class="pre">curve_fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">f</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p0</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'t'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_fit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.html#impy.collections.DataDict" title="impy.collections.DataDict"><span class="pre">DataDict</span></a><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/arrays/specials.html#PropArray.curve_fit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.PropArray.curve_fit" title="Permalink to this definition">¶</a></dt>
+<dd><p>Run scipy.optimize.curve_fit for each dimesion.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>f</strong> (<em>callable</em>) – Model function.</p></li>
+<li><p><strong>p0</strong> (<em>array</em><em> or </em><em>callable</em><em>, </em><em>optional</em>) – Initial parameter. Callable object that estimate initial paramter can also
+be passed here.</p></li>
+<li><p><strong>dims</strong> (<em>str</em><em>, </em><em>by default &quot;t&quot;</em>) – Along which axes fitting algorithms are conducted.</p></li>
+<li><p><strong>return_fit</strong> (<em>bool</em><em>, </em><em>by default True</em>) – If fitting trajectories are returned. If the input array is large, this will
+save much memory.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>params : Fitting parameters
+covs : Covariances
+fit : fitting trajectories (if return_fit==True)</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.html#impy.collections.DataDict" title="impy.collections.DataDict">DataDict</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.PropArray.hist">
+<span class="sig-name descname"><span class="pre">hist</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'N'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bins</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cmap</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'jet'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cmap_range</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">(0.0,</span> <span class="pre">1.0)</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a></span></span><a class="reference internal" href="../_modules/impy/arrays/specials.html#PropArray.hist"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.PropArray.hist" title="Permalink to this definition">¶</a></dt>
+<dd><p>Plot histogram.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>along</strong> (<em>str</em><em>, </em><em>optional</em>) – Which axis will be the x-axis of plot, by default None</p></li>
+<li><p><strong>bins</strong> (<em>int</em><em>, </em><em>optional</em>) – Bin number of histogram.</p></li>
+<li><p><strong>cmap</strong> (<em>str</em><em>, </em><em>default is &quot;jet&quot;</em>) – Colormap of each graph.</p></li>
+<li><p><strong>cmap_range</strong> (<em>tuple</em><em>, </em><em>default is</em><em> (</em><em>0</em><em>, </em><em>1</em><em>)</em>) – Range of float for colormap iteration.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
+<dd class="field-even"><p>self</p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.arrays.PropArray.plot">
+<span class="sig-name descname"><span class="pre">plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">along</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cmap</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'jet'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cmap_range</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">(0,</span> <span class="pre">1)</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/arrays/specials.html#PropArray.plot"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.arrays.PropArray.plot" title="Permalink to this definition">¶</a></dt>
+<dd><p>Plot all the results with x-axis defined by <cite>along</cite>.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>along</strong> (<em>str</em><em>, </em><em>optional</em>) – Which axis will be the x-axis of plot, by default None</p></li>
+<li><p><strong>cmap</strong> (<em>str</em><em>, </em><em>default is &quot;jet&quot;</em>) – Colormap of each graph.</p></li>
+<li><p><strong>cmap_range</strong> (<em>tuple</em><em>, </em><em>default is</em><em> (</em><em>0</em><em>, </em><em>1</em><em>)</em>) – Range of float for colormap iteration.</p></li>
+</ul>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py attribute">
+<dt class="sig sig-object py" id="impy.arrays.PropArray.propname">
+<span class="sig-name descname"><span class="pre">propname</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">str</span></em><a class="headerlink" href="#impy.arrays.PropArray.propname" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+</dd></dl>
+
 </section>
 </section>
 
diff --git a/docs/apidoc/impy.axes.html b/docs/apidoc/impy.axes.html
index 4847228b..bc7f8760 100644
--- a/docs/apidoc/impy.axes.html
+++ b/docs/apidoc/impy.axes.html
@@ -1,10 +1,10 @@
 <!DOCTYPE html>
 <html class="writer-html5" lang="en" >
 <head>
-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
+  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.axes package &mdash; impy 2.2.0 documentation</title>
+  <title>impy.axes package &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -12,9 +12,8 @@
   <![endif]-->
   
         <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-        <script src="../_static/jquery.js"></script>
-        <script src="../_static/underscore.js"></script>
         <script src="../_static/doctools.js"></script>
+        <script src="../_static/sphinx_highlight.js"></script>
     <script src="../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
@@ -27,14 +26,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -61,10 +64,10 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../api.html">API References</a> &raquo;</li>
-          <li><a href="impy.html">impy package</a> &raquo;</li>
-      <li>impy.axes package</li>
+      <li><a href="../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../api.html">API References</a></li>
+          <li class="breadcrumb-item"><a href="impy.html">impy package</a></li>
+      <li class="breadcrumb-item active">impy.axes package</li>
       <li class="wy-breadcrumbs-aside">
             <a href="../_sources/apidoc/impy.axes.rst.txt" rel="nofollow"> View page source</a>
       </li>
@@ -75,9 +78,9 @@
            <div itemprop="articleBody">
              
   <section id="impy-axes-package">
-<h1>impy.axes package<a class="headerlink" href="#impy-axes-package" title="Permalink to this headline">¶</a></h1>
+<h1>impy.axes package<a class="headerlink" href="#impy-axes-package" title="Permalink to this heading">¶</a></h1>
 <section id="module-impy.axes">
-<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-impy.axes" title="Permalink to this headline">¶</a></h2>
+<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-impy.axes" title="Permalink to this heading">¶</a></h2>
 </section>
 </section>
 
diff --git a/docs/apidoc/impy.frame.html b/docs/apidoc/impy.frame.html
index 82f1f534..243eea07 100644
--- a/docs/apidoc/impy.frame.html
+++ b/docs/apidoc/impy.frame.html
@@ -1,10 +1,10 @@
 <!DOCTYPE html>
 <html class="writer-html5" lang="en" >
 <head>
-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
+  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.frame package &mdash; impy 2.2.0 documentation</title>
+  <title>impy.frame package &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
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-        <script src="../_static/jquery.js"></script>
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+        <script src="../_static/sphinx_highlight.js"></script>
     <script src="../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
-    <link rel="next" title="impy.utils package" href="impy.utils.html" />
+    <link rel="next" title="impy.lazy package" href="impy.lazy.html" />
     <link rel="prev" title="impy.axes package" href="impy.axes.html" /> 
 </head>
 
@@ -27,14 +26,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -61,10 +64,10 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../api.html">API References</a> &raquo;</li>
-          <li><a href="impy.html">impy package</a> &raquo;</li>
-      <li>impy.frame package</li>
+      <li><a href="../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../api.html">API References</a></li>
+          <li class="breadcrumb-item"><a href="impy.html">impy package</a></li>
+      <li class="breadcrumb-item active">impy.frame package</li>
       <li class="wy-breadcrumbs-aside">
             <a href="../_sources/apidoc/impy.frame.rst.txt" rel="nofollow"> View page source</a>
       </li>
@@ -75,19 +78,19 @@
            <div itemprop="articleBody">
              
   <section id="impy-frame-package">
-<h1>impy.frame package<a class="headerlink" href="#impy-frame-package" title="Permalink to this headline">¶</a></h1>
+<h1>impy.frame package<a class="headerlink" href="#impy-frame-package" title="Permalink to this heading">¶</a></h1>
 <section id="submodules">
-<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline">¶</a></h2>
+<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this heading">¶</a></h2>
 </section>
 <section id="module-impy.frame.frames">
-<span id="impy-frame-frames-module"></span><h2>impy.frame.frames module<a class="headerlink" href="#module-impy.frame.frames" title="Permalink to this headline">¶</a></h2>
+<span id="impy-frame-frames-module"></span><h2>impy.frame.frames module<a class="headerlink" href="#module-impy.frame.frames" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.frame.frames.AxesFrame">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.frame.frames.</span></span><span class="sig-name descname"><span class="pre">AxesFrame</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">columns</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/frame/frames.html#AxesFrame"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.frame.frames.AxesFrame" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">pandas.core.frame.DataFrame</span></code></p>
+<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">DataFrame</span></code></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.frame.frames.AxesFrame.as_standard_type">
-<span class="sig-name descname"><span class="pre">as_standard_type</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.frame.frames.AxesFrame" title="impy.frame.frames.AxesFrame"><span class="pre">impy.frame.frames.AxesFrame</span></a></span></span><a class="reference internal" href="../_modules/impy/frame/frames.html#AxesFrame.as_standard_type"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.frame.frames.AxesFrame.as_standard_type" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">as_standard_type</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.frame.frames.AxesFrame" title="impy.frame.frames.AxesFrame"><span class="pre">AxesFrame</span></a></span></span><a class="reference internal" href="../_modules/impy/frame/frames.html#AxesFrame.as_standard_type"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.frame.frames.AxesFrame.as_standard_type" title="Permalink to this definition">¶</a></dt>
 <dd><p>t or c -&gt; uint16
 p -&gt; uint32
 z, y, x -&gt; float32</p>
@@ -109,10 +112,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dd><p>Iteration along any axes. This method is almost doing the same thing as <cite>groupby</cite>, but sub-
 DataFrames without axes in columns are yielded.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>axes</strong> (<em>str</em>) – Along which axes to iterate.</p>
 </dd>
-<dt class="field-even">Yields</dt>
+<dt class="field-even">Yields<span class="colon">:</span></dt>
 <dd class="field-even"><p><em>tuple and AxesFrame</em> – slice to generate the AxesFrame.</p>
 </dd>
 </dl>
@@ -133,7 +136,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">set_scale</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">other</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="reference internal" href="../_modules/impy/frame/frames.html#AxesFrame.set_scale"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.frame.frames.AxesFrame.set_scale" title="Permalink to this definition">¶</a></dt>
 <dd><p>Set scales of each axis.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>other</strong> (<em>dict</em><em>, </em><a class="reference internal" href="#impy.frame.frames.AxesFrame" title="impy.frame.frames.AxesFrame"><em>AxesFrame</em></a><em> or </em><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><em>MetaArray</em></a><em>, </em><em>optional</em>) – New scales. If dict, it should be like {“x”: 0.1, “y”: 0.1}. If MetaArray, only
 scales of common axes are copied.</p></li>
@@ -155,14 +158,14 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 “t”, “c”, “y”, “x” and it is split along “c” axis, then output is a list of DataFrame with
 columns “t”, “y”, “x”.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>axis</strong> (<em>str</em><em>, </em><em>default is &quot;c&quot;</em>) – Along which axis to split</p>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Separate DataFrames.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
-<dd class="field-odd"><p>list of AxesFrame</p>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>list of <a class="reference internal" href="#impy.frame.frames.AxesFrame" title="impy.frame.frames.AxesFrame">AxesFrame</a></p>
 </dd>
 </dl>
 </dd></dl>
@@ -172,24 +175,24 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.frame.frames.MarkerFrame">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.frame.frames.</span></span><span class="sig-name descname"><span class="pre">MarkerFrame</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">columns</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/frame/frames.html#MarkerFrame"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.frame.frames.MarkerFrame" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="#impy.frame.frames.AxesFrame" title="impy.frame.frames.AxesFrame"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.frame.frames.AxesFrame</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="#impy.frame.frames.AxesFrame" title="impy.frame.frames.AxesFrame"><code class="xref py py-class docutils literal notranslate"><span class="pre">AxesFrame</span></code></a></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.frame.frames.MarkerFrame.link">
 <span class="sig-name descname"><span class="pre">link</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">search_range</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">memory</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_dwell</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.frame.frames.TrackFrame" title="impy.frame.frames.TrackFrame"><span class="pre">TrackFrame</span></a></span></span><a class="reference internal" href="../_modules/impy/frame/frames.html#MarkerFrame.link"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.frame.frames.MarkerFrame.link" title="Permalink to this definition">¶</a></dt>
 <dd><p>Link separate points to generate tracks.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>search_range</strong> (<em>float</em><em> or </em><em>tuple of float</em>) – How far a molecule can move in the next frame. Large value causes long calculation time.</p></li>
+<li><p><strong>search_range</strong> (<em>float</em><em> or </em><em>tuple</em><em> of </em><em>float</em>) – How far a molecule can move in the next frame. Large value causes long calculation time.</p></li>
 <li><p><strong>memory</strong> (<em>int</em><em>, </em><em>default is 0</em>) – How long a molecule can vanish.</p></li>
 <li><p><strong>min_dwell</strong> (<em>int</em><em>, </em><em>default is 0</em>) – Minimum number of frames that single track should dwell.</p></li>
 <li><p><strong>dims</strong> (<em>int</em><em> or </em><em>str</em><em>, </em><em>optional</em>) – Spatial dimensions.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Result of particle tracking.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.frame.frames.TrackFrame" title="impy.frame.frames.TrackFrame">TrackFrame</a></p>
 </dd>
 </dl>
@@ -200,7 +203,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.frame.frames.PathFrame">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.frame.frames.</span></span><span class="sig-name descname"><span class="pre">PathFrame</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">columns</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/frame/frames.html#PathFrame"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.frame.frames.PathFrame" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="#impy.frame.frames.AxesFrame" title="impy.frame.frames.AxesFrame"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.frame.frames.AxesFrame</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="#impy.frame.frames.AxesFrame" title="impy.frame.frames.AxesFrame"><code class="xref py py-class docutils literal notranslate"><span class="pre">AxesFrame</span></code></a></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.frame.frames.PathFrame.length">
 <span class="sig-name descname"><span class="pre">length</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/frame/frames.html#PathFrame.length"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.frame.frames.PathFrame.length" title="Permalink to this definition">¶</a></dt>
@@ -211,7 +214,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.frame.frames.TrackFrame">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.frame.frames.</span></span><span class="sig-name descname"><span class="pre">TrackFrame</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">columns</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/frame/frames.html#TrackFrame"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.frame.frames.TrackFrame" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="#impy.frame.frames.AxesFrame" title="impy.frame.frames.AxesFrame"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.frame.frames.AxesFrame</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="#impy.frame.frames.AxesFrame" title="impy.frame.frames.AxesFrame"><code class="xref py py-class docutils literal notranslate"><span class="pre">AxesFrame</span></code></a></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.frame.frames.TrackFrame.as_path">
 <span class="sig-name descname"><span class="pre">as_path</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/frame/frames.html#TrackFrame.as_path"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.frame.frames.TrackFrame.as_path" title="Permalink to this definition">¶</a></dt>
@@ -252,7 +255,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.frame">
-<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-impy.frame" title="Permalink to this headline">¶</a></h2>
+<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-impy.frame" title="Permalink to this heading">¶</a></h2>
 </section>
 </section>
 
@@ -261,7 +264,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
           </div>
           <footer><div class="rst-footer-buttons" role="navigation" aria-label="Footer">
         <a href="impy.axes.html" class="btn btn-neutral float-left" title="impy.axes package" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left" aria-hidden="true"></span> Previous</a>
-        <a href="impy.utils.html" class="btn btn-neutral float-right" title="impy.utils package" accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right" aria-hidden="true"></span></a>
+        <a href="impy.lazy.html" class="btn btn-neutral float-right" title="impy.lazy package" accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right" aria-hidden="true"></span></a>
     </div>
 
   <hr/>
diff --git a/docs/apidoc/impy.html b/docs/apidoc/impy.html
index 388e3920..7110d03a 100644
--- a/docs/apidoc/impy.html
+++ b/docs/apidoc/impy.html
@@ -1,10 +1,10 @@
 <!DOCTYPE html>
 <html class="writer-html5" lang="en" >
 <head>
-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
+  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy package &mdash; impy 2.2.0 documentation</title>
+  <title>impy package &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -12,9 +12,8 @@
   <![endif]-->
   
         <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-        <script src="../_static/jquery.js"></script>
-        <script src="../_static/underscore.js"></script>
         <script src="../_static/doctools.js"></script>
+        <script src="../_static/sphinx_highlight.js"></script>
         <script async="async" src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
     <script src="../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../genindex.html" />
@@ -28,14 +27,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -62,9 +65,9 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../api.html">API References</a> &raquo;</li>
-      <li>impy package</li>
+      <li><a href="../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../api.html">API References</a></li>
+      <li class="breadcrumb-item active">impy package</li>
       <li class="wy-breadcrumbs-aside">
             <a href="../_sources/apidoc/impy.rst.txt" rel="nofollow"> View page source</a>
       </li>
@@ -75,9 +78,9 @@
            <div itemprop="articleBody">
              
   <section id="impy-package">
-<h1>impy package<a class="headerlink" href="#impy-package" title="Permalink to this headline">¶</a></h1>
+<h1>impy package<a class="headerlink" href="#impy-package" title="Permalink to this heading">¶</a></h1>
 <section id="subpackages">
-<h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to this headline">¶</a></h2>
+<h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to this heading">¶</a></h2>
 <div class="toctree-wrapper compound">
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="impy.arrays.html">impy.arrays package</a><ul>
@@ -92,15 +95,640 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 </ul>
 </li>
 <li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#submodules">Submodules</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.axesmixin">impy.arrays.axesmixin module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.big">impy.arrays.big module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.imgarray">impy.arrays.imgarray module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.label">impy.arrays.label module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.labeledarray">impy.arrays.labeledarray module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.lazy">impy.arrays.lazy module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.phasearray">impy.arrays.phasearray module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.specials">impy.arrays.specials module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays">Module contents</a></li>
+<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.axesmixin">impy.arrays.axesmixin module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin"><code class="docutils literal notranslate"><span class="pre">AxesMixin</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin.axes"><code class="docutils literal notranslate"><span class="pre">AxesMixin.axes</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin.axisof"><code class="docutils literal notranslate"><span class="pre">AxesMixin.axisof()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin.dtype"><code class="docutils literal notranslate"><span class="pre">AxesMixin.dtype</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin.iter"><code class="docutils literal notranslate"><span class="pre">AxesMixin.iter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin.metadata"><code class="docutils literal notranslate"><span class="pre">AxesMixin.metadata</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin.ndim"><code class="docutils literal notranslate"><span class="pre">AxesMixin.ndim</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin.scale"><code class="docutils literal notranslate"><span class="pre">AxesMixin.scale</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin.scale_unit"><code class="docutils literal notranslate"><span class="pre">AxesMixin.scale_unit</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin.set_axes"><code class="docutils literal notranslate"><span class="pre">AxesMixin.set_axes()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin.set_axis_label"><code class="docutils literal notranslate"><span class="pre">AxesMixin.set_axis_label()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin.set_scale"><code class="docutils literal notranslate"><span class="pre">AxesMixin.set_scale()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin.shape"><code class="docutils literal notranslate"><span class="pre">AxesMixin.shape</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin.shape_info"><code class="docutils literal notranslate"><span class="pre">AxesMixin.shape_info</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin.sizeof"><code class="docutils literal notranslate"><span class="pre">AxesMixin.sizeof()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin.sizesof"><code class="docutils literal notranslate"><span class="pre">AxesMixin.sizesof()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin.spatial_shape"><code class="docutils literal notranslate"><span class="pre">AxesMixin.spatial_shape</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.AxesMixin.value"><code class="docutils literal notranslate"><span class="pre">AxesMixin.value</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.axesmixin.get_axes_tuple"><code class="docutils literal notranslate"><span class="pre">get_axes_tuple()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.big">impy.arrays.big module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray"><code class="docutils literal notranslate"><span class="pre">BigImgArray</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.affine"><code class="docutils literal notranslate"><span class="pre">BigImgArray.affine()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.as_float"><code class="docutils literal notranslate"><span class="pre">BigImgArray.as_float()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.as_img_type"><code class="docutils literal notranslate"><span class="pre">BigImgArray.as_img_type()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.as_uint16"><code class="docutils literal notranslate"><span class="pre">BigImgArray.as_uint16()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.as_uint8"><code class="docutils literal notranslate"><span class="pre">BigImgArray.as_uint8()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.binning"><code class="docutils literal notranslate"><span class="pre">BigImgArray.binning()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.closing"><code class="docutils literal notranslate"><span class="pre">BigImgArray.closing()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.convolve"><code class="docutils literal notranslate"><span class="pre">BigImgArray.convolve()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.dilation"><code class="docutils literal notranslate"><span class="pre">BigImgArray.dilation()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.drift_correction"><code class="docutils literal notranslate"><span class="pre">BigImgArray.drift_correction()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.edge_filter"><code class="docutils literal notranslate"><span class="pre">BigImgArray.edge_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.erosion"><code class="docutils literal notranslate"><span class="pre">BigImgArray.erosion()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.fft"><code class="docutils literal notranslate"><span class="pre">BigImgArray.fft()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.gaussian_filter"><code class="docutils literal notranslate"><span class="pre">BigImgArray.gaussian_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.ifft"><code class="docutils literal notranslate"><span class="pre">BigImgArray.ifft()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.kalman_filter"><code class="docutils literal notranslate"><span class="pre">BigImgArray.kalman_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.laplacian_filter"><code class="docutils literal notranslate"><span class="pre">BigImgArray.laplacian_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.lucy"><code class="docutils literal notranslate"><span class="pre">BigImgArray.lucy()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.mean_filter"><code class="docutils literal notranslate"><span class="pre">BigImgArray.mean_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.median_filter"><code class="docutils literal notranslate"><span class="pre">BigImgArray.median_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.opening"><code class="docutils literal notranslate"><span class="pre">BigImgArray.opening()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.power_spectra"><code class="docutils literal notranslate"><span class="pre">BigImgArray.power_spectra()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.proj"><code class="docutils literal notranslate"><span class="pre">BigImgArray.proj()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.radon"><code class="docutils literal notranslate"><span class="pre">BigImgArray.radon()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.spline_filter"><code class="docutils literal notranslate"><span class="pre">BigImgArray.spline_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.tiled_lowpass_filter"><code class="docutils literal notranslate"><span class="pre">BigImgArray.tiled_lowpass_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.track_drift"><code class="docutils literal notranslate"><span class="pre">BigImgArray.track_drift()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray.wiener"><code class="docutils literal notranslate"><span class="pre">BigImgArray.wiener()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.wrap_method"><code class="docutils literal notranslate"><span class="pre">wrap_method()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.imgarray">impy.arrays.imgarray module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray"><code class="docutils literal notranslate"><span class="pre">ImgArray</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.axes"><code class="docutils literal notranslate"><span class="pre">ImgArray.axes</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.scale"><code class="docutils literal notranslate"><span class="pre">ImgArray.scale</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.metadata"><code class="docutils literal notranslate"><span class="pre">ImgArray.metadata</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.source"><code class="docutils literal notranslate"><span class="pre">ImgArray.source</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.affine"><code class="docutils literal notranslate"><span class="pre">ImgArray.affine()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.area_closing"><code class="docutils literal notranslate"><span class="pre">ImgArray.area_closing()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.area_opening"><code class="docutils literal notranslate"><span class="pre">ImgArray.area_opening()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.binning"><code class="docutils literal notranslate"><span class="pre">ImgArray.binning()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.center_of_mass"><code class="docutils literal notranslate"><span class="pre">ImgArray.center_of_mass()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.centroid_sm"><code class="docutils literal notranslate"><span class="pre">ImgArray.centroid_sm()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.clip"><code class="docutils literal notranslate"><span class="pre">ImgArray.clip()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.closing"><code class="docutils literal notranslate"><span class="pre">ImgArray.closing()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.coef_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.coef_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.convex_hull"><code class="docutils literal notranslate"><span class="pre">ImgArray.convex_hull()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.convolve"><code class="docutils literal notranslate"><span class="pre">ImgArray.convolve()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.corner_harris"><code class="docutils literal notranslate"><span class="pre">ImgArray.corner_harris()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.corner_peaks"><code class="docutils literal notranslate"><span class="pre">ImgArray.corner_peaks()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.count_neighbors"><code class="docutils literal notranslate"><span class="pre">ImgArray.count_neighbors()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.diameter_closing"><code class="docutils literal notranslate"><span class="pre">ImgArray.diameter_closing()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.diameter_opening"><code class="docutils literal notranslate"><span class="pre">ImgArray.diameter_opening()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.dilation"><code class="docutils literal notranslate"><span class="pre">ImgArray.dilation()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.distance_map"><code class="docutils literal notranslate"><span class="pre">ImgArray.distance_map()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.dog_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.dog_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.doh_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.doh_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.drift_correction"><code class="docutils literal notranslate"><span class="pre">ImgArray.drift_correction()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.edge_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.edge_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.edge_grad"><code class="docutils literal notranslate"><span class="pre">ImgArray.edge_grad()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.enhance_contrast"><code class="docutils literal notranslate"><span class="pre">ImgArray.enhance_contrast()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.entropy_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.entropy_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.erosion"><code class="docutils literal notranslate"><span class="pre">ImgArray.erosion()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.estimate_sigma"><code class="docutils literal notranslate"><span class="pre">ImgArray.estimate_sigma()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.fft"><code class="docutils literal notranslate"><span class="pre">ImgArray.fft()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.fill_hole"><code class="docutils literal notranslate"><span class="pre">ImgArray.fill_hole()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.find_corners"><code class="docutils literal notranslate"><span class="pre">ImgArray.find_corners()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.find_sm"><code class="docutils literal notranslate"><span class="pre">ImgArray.find_sm()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.flood"><code class="docutils literal notranslate"><span class="pre">ImgArray.flood()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.focus_map"><code class="docutils literal notranslate"><span class="pre">ImgArray.focus_map()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.gabor_angle"><code class="docutils literal notranslate"><span class="pre">ImgArray.gabor_angle()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.gabor_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.gabor_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.gauss_correction"><code class="docutils literal notranslate"><span class="pre">ImgArray.gauss_correction()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.gauss_sm"><code class="docutils literal notranslate"><span class="pre">ImgArray.gauss_sm()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.gaussfit"><code class="docutils literal notranslate"><span class="pre">ImgArray.gaussfit()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.gaussian_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.gaussian_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.glcm_props"><code class="docutils literal notranslate"><span class="pre">ImgArray.glcm_props()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.hessian_angle"><code class="docutils literal notranslate"><span class="pre">ImgArray.hessian_angle()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.hessian_eig"><code class="docutils literal notranslate"><span class="pre">ImgArray.hessian_eig()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.hessian_eigval"><code class="docutils literal notranslate"><span class="pre">ImgArray.hessian_eigval()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.highpass_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.highpass_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.ifft"><code class="docutils literal notranslate"><span class="pre">ImgArray.ifft()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.inpaint"><code class="docutils literal notranslate"><span class="pre">ImgArray.inpaint()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.iradon"><code class="docutils literal notranslate"><span class="pre">ImgArray.iradon()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.kalman_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.kalman_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.label_threshold"><code class="docutils literal notranslate"><span class="pre">ImgArray.label_threshold()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.laplacian_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.laplacian_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.lbp"><code class="docutils literal notranslate"><span class="pre">ImgArray.lbp()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.local_dft"><code class="docutils literal notranslate"><span class="pre">ImgArray.local_dft()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.local_power_spectra"><code class="docutils literal notranslate"><span class="pre">ImgArray.local_power_spectra()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.log_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.log_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.lowpass_conv_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.lowpass_conv_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.lowpass_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.lowpass_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.lucy"><code class="docutils literal notranslate"><span class="pre">ImgArray.lucy()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.lucy_tv"><code class="docutils literal notranslate"><span class="pre">ImgArray.lucy_tv()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.mean_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.mean_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.median_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.median_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.ncc_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.ncc_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.opening"><code class="docutils literal notranslate"><span class="pre">ImgArray.opening()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.pad"><code class="docutils literal notranslate"><span class="pre">ImgArray.pad()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.pad_defocus"><code class="docutils literal notranslate"><span class="pre">ImgArray.pad_defocus()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.peak_local_max"><code class="docutils literal notranslate"><span class="pre">ImgArray.peak_local_max()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.power_spectra"><code class="docutils literal notranslate"><span class="pre">ImgArray.power_spectra()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.proj"><code class="docutils literal notranslate"><span class="pre">ImgArray.proj()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.radial_profile"><code class="docutils literal notranslate"><span class="pre">ImgArray.radial_profile()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.radon"><code class="docutils literal notranslate"><span class="pre">ImgArray.radon()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.random_walker"><code class="docutils literal notranslate"><span class="pre">ImgArray.random_walker()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.regionprops"><code class="docutils literal notranslate"><span class="pre">ImgArray.regionprops()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.remove_fine_objects"><code class="docutils literal notranslate"><span class="pre">ImgArray.remove_fine_objects()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.remove_large_objects"><code class="docutils literal notranslate"><span class="pre">ImgArray.remove_large_objects()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.remove_skeleton_structure"><code class="docutils literal notranslate"><span class="pre">ImgArray.remove_skeleton_structure()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.rescale"><code class="docutils literal notranslate"><span class="pre">ImgArray.rescale()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.rescale_intensity"><code class="docutils literal notranslate"><span class="pre">ImgArray.rescale_intensity()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.rof_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.rof_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.rolling_ball"><code class="docutils literal notranslate"><span class="pre">ImgArray.rolling_ball()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.rotate"><code class="docutils literal notranslate"><span class="pre">ImgArray.rotate()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.skeletonize"><code class="docutils literal notranslate"><span class="pre">ImgArray.skeletonize()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.smooth_mask"><code class="docutils literal notranslate"><span class="pre">ImgArray.smooth_mask()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.split_pixel_unit"><code class="docutils literal notranslate"><span class="pre">ImgArray.split_pixel_unit()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.std_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.std_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.stokes"><code class="docutils literal notranslate"><span class="pre">ImgArray.stokes()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.stretch"><code class="docutils literal notranslate"><span class="pre">ImgArray.stretch()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.structure_tensor_eig"><code class="docutils literal notranslate"><span class="pre">ImgArray.structure_tensor_eig()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.structure_tensor_eigval"><code class="docutils literal notranslate"><span class="pre">ImgArray.structure_tensor_eigval()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.threshold"><code class="docutils literal notranslate"><span class="pre">ImgArray.threshold()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.tiled"><code class="docutils literal notranslate"><span class="pre">ImgArray.tiled</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.tiled_lowpass_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.tiled_lowpass_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.tiled_lucy"><code class="docutils literal notranslate"><span class="pre">ImgArray.tiled_lucy()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.tophat"><code class="docutils literal notranslate"><span class="pre">ImgArray.tophat()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.track_drift"><code class="docutils literal notranslate"><span class="pre">ImgArray.track_drift()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.track_template"><code class="docutils literal notranslate"><span class="pre">ImgArray.track_template()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.unmix"><code class="docutils literal notranslate"><span class="pre">ImgArray.unmix()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.voronoi"><code class="docutils literal notranslate"><span class="pre">ImgArray.voronoi()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.watershed"><code class="docutils literal notranslate"><span class="pre">ImgArray.watershed()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.wavelet_denoising"><code class="docutils literal notranslate"><span class="pre">ImgArray.wavelet_denoising()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray.wiener"><code class="docutils literal notranslate"><span class="pre">ImgArray.wiener()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.check_filter_func"><code class="docutils literal notranslate"><span class="pre">check_filter_func()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.wave_num"><code class="docutils literal notranslate"><span class="pre">wave_num()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.label">impy.arrays.label module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.label.Label"><code class="docutils literal notranslate"><span class="pre">Label</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.label.Label.add_label"><code class="docutils literal notranslate"><span class="pre">Label.add_label()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.label.Label.as_larger_type"><code class="docutils literal notranslate"><span class="pre">Label.as_larger_type()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.label.Label.delete_label"><code class="docutils literal notranslate"><span class="pre">Label.delete_label()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.label.Label.expand_labels"><code class="docutils literal notranslate"><span class="pre">Label.expand_labels()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.label.Label.imshow"><code class="docutils literal notranslate"><span class="pre">Label.imshow()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.label.Label.increment"><code class="docutils literal notranslate"><span class="pre">Label.increment()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.label.Label.increment_iter"><code class="docutils literal notranslate"><span class="pre">Label.increment_iter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.label.Label.opening"><code class="docutils literal notranslate"><span class="pre">Label.opening()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.label.Label.optimize"><code class="docutils literal notranslate"><span class="pre">Label.optimize()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.label.Label.proj"><code class="docutils literal notranslate"><span class="pre">Label.proj()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.label.Label.relabel"><code class="docutils literal notranslate"><span class="pre">Label.relabel()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.label.best_dtype"><code class="docutils literal notranslate"><span class="pre">best_dtype()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.labeledarray">impy.arrays.labeledarray module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.ArrayCovariates"><code class="docutils literal notranslate"><span class="pre">ArrayCovariates</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.ArrayCovariates.construct_by_copying"><code class="docutils literal notranslate"><span class="pre">ArrayCovariates.construct_by_copying()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.ArrayCovariates.construct_by_slicing"><code class="docutils literal notranslate"><span class="pre">ArrayCovariates.construct_by_slicing()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.ArrayCovariates.parent"><code class="docutils literal notranslate"><span class="pre">ArrayCovariates.parent</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray"><code class="docutils literal notranslate"><span class="pre">LabeledArray</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.append_label"><code class="docutils literal notranslate"><span class="pre">LabeledArray.append_label()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.as_float"><code class="docutils literal notranslate"><span class="pre">LabeledArray.as_float()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.as_img_type"><code class="docutils literal notranslate"><span class="pre">LabeledArray.as_img_type()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.as_uint16"><code class="docutils literal notranslate"><span class="pre">LabeledArray.as_uint16()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.as_uint8"><code class="docutils literal notranslate"><span class="pre">LabeledArray.as_uint8()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.axes"><code class="docutils literal notranslate"><span class="pre">LabeledArray.axes</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.covariates"><code class="docutils literal notranslate"><span class="pre">LabeledArray.covariates</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.crop_center"><code class="docutils literal notranslate"><span class="pre">LabeledArray.crop_center()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.crop_kernel"><code class="docutils literal notranslate"><span class="pre">LabeledArray.crop_kernel()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.extract"><code class="docutils literal notranslate"><span class="pre">LabeledArray.extract()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.for_each_channel"><code class="docutils literal notranslate"><span class="pre">LabeledArray.for_each_channel()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.for_params"><code class="docutils literal notranslate"><span class="pre">LabeledArray.for_params()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.hist"><code class="docutils literal notranslate"><span class="pre">LabeledArray.hist()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.imsave"><code class="docutils literal notranslate"><span class="pre">LabeledArray.imsave()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.imshow"><code class="docutils literal notranslate"><span class="pre">LabeledArray.imshow()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.label"><code class="docutils literal notranslate"><span class="pre">LabeledArray.label()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.label_if"><code class="docutils literal notranslate"><span class="pre">LabeledArray.label_if()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.labels"><code class="docutils literal notranslate"><span class="pre">LabeledArray.labels</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.map_coordinates"><code class="docutils literal notranslate"><span class="pre">LabeledArray.map_coordinates()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.pathprops"><code class="docutils literal notranslate"><span class="pre">LabeledArray.pathprops()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.pointprops"><code class="docutils literal notranslate"><span class="pre">LabeledArray.pointprops()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.proj_labels"><code class="docutils literal notranslate"><span class="pre">LabeledArray.proj_labels()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.range"><code class="docutils literal notranslate"><span class="pre">LabeledArray.range</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.remove_edges"><code class="docutils literal notranslate"><span class="pre">LabeledArray.remove_edges()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.reslice"><code class="docutils literal notranslate"><span class="pre">LabeledArray.reslice()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.rois"><code class="docutils literal notranslate"><span class="pre">LabeledArray.rois</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.rotated_crop"><code class="docutils literal notranslate"><span class="pre">LabeledArray.rotated_crop()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.set_scale"><code class="docutils literal notranslate"><span class="pre">LabeledArray.set_scale()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.specify"><code class="docutils literal notranslate"><span class="pre">LabeledArray.specify()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.spline_filter"><code class="docutils literal notranslate"><span class="pre">LabeledArray.spline_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.split"><code class="docutils literal notranslate"><span class="pre">LabeledArray.split()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray.tile"><code class="docutils literal notranslate"><span class="pre">LabeledArray.tile()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.SegmentedLine"><code class="docutils literal notranslate"><span class="pre">SegmentedLine</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.SegmentedLine.sample_points"><code class="docutils literal notranslate"><span class="pre">SegmentedLine.sample_points()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.SupportAxesSlicing"><code class="docutils literal notranslate"><span class="pre">SupportAxesSlicing</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.SupportAxesSlicing.axes"><code class="docutils literal notranslate"><span class="pre">SupportAxesSlicing.axes</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.SupportAxesSlicing.copy"><code class="docutils literal notranslate"><span class="pre">SupportAxesSlicing.copy()</span></code></a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.lazy">impy.arrays.lazy module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray"><code class="docutils literal notranslate"><span class="pre">LazyImgArray</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.GB"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.GB</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.additional_props"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.additional_props</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.affine"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.affine()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.apply_dask_func"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.apply_dask_func()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.as_float"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.as_float()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.as_img_type"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.as_img_type()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.as_uint16"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.as_uint16()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.as_uint8"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.as_uint8()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.binning"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.binning()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.chunk_info"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.chunk_info</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.chunksize"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.chunksize</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.chunksizeof"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.chunksizeof()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.chunksizesof"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.chunksizesof()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.closing"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.closing()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.compute"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.compute()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.convolve"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.convolve()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.crop_center"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.crop_center()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.dilation"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.dilation()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.drift_correction"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.drift_correction()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.dtype"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.dtype</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.edge_filter"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.edge_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.erosion"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.erosion()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.fft"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.fft()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.gaussian_filter"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.gaussian_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.gb"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.gb</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.ifft"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.ifft()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.imsave"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.imsave()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.iradon"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.iradon()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.itemsize"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.itemsize</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.kalman_filter"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.kalman_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.laplacian_filter"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.laplacian_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.lucy"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.lucy()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.max"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.max()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.mean"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.mean()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.mean_filter"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.mean_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.median_filter"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.median_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.metadata"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.metadata</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.min"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.min()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.name"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.name</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.ndim"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.ndim</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.opening"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.opening()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.pad"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.pad()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.power_spectra"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.power_spectra()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.proj"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.proj()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.radon"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.radon()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.rechunk"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.rechunk()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.release"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.release()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.shape"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.shape</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.size"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.size</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.sort_axes"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.sort_axes()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.source"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.source</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.spline_filter"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.spline_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.std"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.std()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.sum"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.sum()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.threshold"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.threshold()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.tiled"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.tiled</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.tiled_lowpass_filter"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.tiled_lowpass_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.track_drift"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.track_drift()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.transpose"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.transpose()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray.wiener"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.wiener()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.iter_slice"><code class="docutils literal notranslate"><span class="pre">iter_slice()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.phasearray">impy.arrays.phasearray module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.phasearray.PhaseArray"><code class="docutils literal notranslate"><span class="pre">PhaseArray</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.phasearray.PhaseArray.additional_props"><code class="docutils literal notranslate"><span class="pre">PhaseArray.additional_props</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.phasearray.PhaseArray.as_exp"><code class="docutils literal notranslate"><span class="pre">PhaseArray.as_exp()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.phasearray.PhaseArray.binning"><code class="docutils literal notranslate"><span class="pre">PhaseArray.binning()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.phasearray.PhaseArray.border"><code class="docutils literal notranslate"><span class="pre">PhaseArray.border</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.phasearray.PhaseArray.deg2rad"><code class="docutils literal notranslate"><span class="pre">PhaseArray.deg2rad()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.phasearray.PhaseArray.imshow"><code class="docutils literal notranslate"><span class="pre">PhaseArray.imshow()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.phasearray.PhaseArray.map_coordinates"><code class="docutils literal notranslate"><span class="pre">PhaseArray.map_coordinates()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.phasearray.PhaseArray.mean_filter"><code class="docutils literal notranslate"><span class="pre">PhaseArray.mean_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.phasearray.PhaseArray.periodicity"><code class="docutils literal notranslate"><span class="pre">PhaseArray.periodicity</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.phasearray.PhaseArray.rad2deg"><code class="docutils literal notranslate"><span class="pre">PhaseArray.rad2deg()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.phasearray.PhaseArray.regionprops"><code class="docutils literal notranslate"><span class="pre">PhaseArray.regionprops()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.phasearray.PhaseArray.reslice"><code class="docutils literal notranslate"><span class="pre">PhaseArray.reslice()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.phasearray.PhaseArray.set_border"><code class="docutils literal notranslate"><span class="pre">PhaseArray.set_border()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.phasearray.PhaseArray.unit"><code class="docutils literal notranslate"><span class="pre">PhaseArray.unit</span></code></a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.specials">impy.arrays.specials module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray"><code class="docutils literal notranslate"><span class="pre">PropArray</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray.additional_props"><code class="docutils literal notranslate"><span class="pre">PropArray.additional_props</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray.as_frame"><code class="docutils literal notranslate"><span class="pre">PropArray.as_frame()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray.curve_fit"><code class="docutils literal notranslate"><span class="pre">PropArray.curve_fit()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray.hist"><code class="docutils literal notranslate"><span class="pre">PropArray.hist()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray.plot"><code class="docutils literal notranslate"><span class="pre">PropArray.plot()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray.propname"><code class="docutils literal notranslate"><span class="pre">PropArray.propname</span></code></a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.tiled">impy.arrays.tiled module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.tiled.TiledAccessor"><code class="docutils literal notranslate"><span class="pre">TiledAccessor</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.tiled.TiledImage"><code class="docutils literal notranslate"><span class="pre">TiledImage</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.tiled.TiledImage.boundary"><code class="docutils literal notranslate"><span class="pre">TiledImage.boundary</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.tiled.TiledImage.chunks"><code class="docutils literal notranslate"><span class="pre">TiledImage.chunks</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.tiled.TiledImage.depth"><code class="docutils literal notranslate"><span class="pre">TiledImage.depth</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.tiled.TiledImage.dog_filter"><code class="docutils literal notranslate"><span class="pre">TiledImage.dog_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.tiled.TiledImage.gaussian_filter"><code class="docutils literal notranslate"><span class="pre">TiledImage.gaussian_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.tiled.TiledImage.log_filter"><code class="docutils literal notranslate"><span class="pre">TiledImage.log_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.tiled.TiledImage.lowpass_filter"><code class="docutils literal notranslate"><span class="pre">TiledImage.lowpass_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.tiled.TiledImage.lucy"><code class="docutils literal notranslate"><span class="pre">TiledImage.lucy()</span></code></a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.arrays.html#module-impy.arrays">Module contents</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray"><code class="docutils literal notranslate"><span class="pre">BigImgArray</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.affine"><code class="docutils literal notranslate"><span class="pre">BigImgArray.affine()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.as_float"><code class="docutils literal notranslate"><span class="pre">BigImgArray.as_float()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.as_img_type"><code class="docutils literal notranslate"><span class="pre">BigImgArray.as_img_type()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.as_uint16"><code class="docutils literal notranslate"><span class="pre">BigImgArray.as_uint16()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.as_uint8"><code class="docutils literal notranslate"><span class="pre">BigImgArray.as_uint8()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.binning"><code class="docutils literal notranslate"><span class="pre">BigImgArray.binning()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.closing"><code class="docutils literal notranslate"><span class="pre">BigImgArray.closing()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.convolve"><code class="docutils literal notranslate"><span class="pre">BigImgArray.convolve()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.dilation"><code class="docutils literal notranslate"><span class="pre">BigImgArray.dilation()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.drift_correction"><code class="docutils literal notranslate"><span class="pre">BigImgArray.drift_correction()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.edge_filter"><code class="docutils literal notranslate"><span class="pre">BigImgArray.edge_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.erosion"><code class="docutils literal notranslate"><span class="pre">BigImgArray.erosion()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.fft"><code class="docutils literal notranslate"><span class="pre">BigImgArray.fft()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.gaussian_filter"><code class="docutils literal notranslate"><span class="pre">BigImgArray.gaussian_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.ifft"><code class="docutils literal notranslate"><span class="pre">BigImgArray.ifft()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.kalman_filter"><code class="docutils literal notranslate"><span class="pre">BigImgArray.kalman_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.laplacian_filter"><code class="docutils literal notranslate"><span class="pre">BigImgArray.laplacian_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.lucy"><code class="docutils literal notranslate"><span class="pre">BigImgArray.lucy()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.mean_filter"><code class="docutils literal notranslate"><span class="pre">BigImgArray.mean_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.median_filter"><code class="docutils literal notranslate"><span class="pre">BigImgArray.median_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.opening"><code class="docutils literal notranslate"><span class="pre">BigImgArray.opening()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.power_spectra"><code class="docutils literal notranslate"><span class="pre">BigImgArray.power_spectra()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.proj"><code class="docutils literal notranslate"><span class="pre">BigImgArray.proj()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.radon"><code class="docutils literal notranslate"><span class="pre">BigImgArray.radon()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.spline_filter"><code class="docutils literal notranslate"><span class="pre">BigImgArray.spline_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.tiled_lowpass_filter"><code class="docutils literal notranslate"><span class="pre">BigImgArray.tiled_lowpass_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.track_drift"><code class="docutils literal notranslate"><span class="pre">BigImgArray.track_drift()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.BigImgArray.wiener"><code class="docutils literal notranslate"><span class="pre">BigImgArray.wiener()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray"><code class="docutils literal notranslate"><span class="pre">ImgArray</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.axes"><code class="docutils literal notranslate"><span class="pre">ImgArray.axes</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.scale"><code class="docutils literal notranslate"><span class="pre">ImgArray.scale</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.metadata"><code class="docutils literal notranslate"><span class="pre">ImgArray.metadata</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.source"><code class="docutils literal notranslate"><span class="pre">ImgArray.source</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.affine"><code class="docutils literal notranslate"><span class="pre">ImgArray.affine()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.area_closing"><code class="docutils literal notranslate"><span class="pre">ImgArray.area_closing()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.area_opening"><code class="docutils literal notranslate"><span class="pre">ImgArray.area_opening()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.binning"><code class="docutils literal notranslate"><span class="pre">ImgArray.binning()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.center_of_mass"><code class="docutils literal notranslate"><span class="pre">ImgArray.center_of_mass()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.centroid_sm"><code class="docutils literal notranslate"><span class="pre">ImgArray.centroid_sm()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.clip"><code class="docutils literal notranslate"><span class="pre">ImgArray.clip()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.closing"><code class="docutils literal notranslate"><span class="pre">ImgArray.closing()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.coef_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.coef_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.convex_hull"><code class="docutils literal notranslate"><span class="pre">ImgArray.convex_hull()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.convolve"><code class="docutils literal notranslate"><span class="pre">ImgArray.convolve()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.corner_harris"><code class="docutils literal notranslate"><span class="pre">ImgArray.corner_harris()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.corner_peaks"><code class="docutils literal notranslate"><span class="pre">ImgArray.corner_peaks()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.count_neighbors"><code class="docutils literal notranslate"><span class="pre">ImgArray.count_neighbors()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.diameter_closing"><code class="docutils literal notranslate"><span class="pre">ImgArray.diameter_closing()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.diameter_opening"><code class="docutils literal notranslate"><span class="pre">ImgArray.diameter_opening()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.dilation"><code class="docutils literal notranslate"><span class="pre">ImgArray.dilation()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.distance_map"><code class="docutils literal notranslate"><span class="pre">ImgArray.distance_map()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.dog_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.dog_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.doh_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.doh_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.drift_correction"><code class="docutils literal notranslate"><span class="pre">ImgArray.drift_correction()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.edge_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.edge_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.edge_grad"><code class="docutils literal notranslate"><span class="pre">ImgArray.edge_grad()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.enhance_contrast"><code class="docutils literal notranslate"><span class="pre">ImgArray.enhance_contrast()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.entropy_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.entropy_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.erosion"><code class="docutils literal notranslate"><span class="pre">ImgArray.erosion()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.estimate_sigma"><code class="docutils literal notranslate"><span class="pre">ImgArray.estimate_sigma()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.fft"><code class="docutils literal notranslate"><span class="pre">ImgArray.fft()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.fill_hole"><code class="docutils literal notranslate"><span class="pre">ImgArray.fill_hole()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.find_corners"><code class="docutils literal notranslate"><span class="pre">ImgArray.find_corners()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.find_sm"><code class="docutils literal notranslate"><span class="pre">ImgArray.find_sm()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.flood"><code class="docutils literal notranslate"><span class="pre">ImgArray.flood()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.focus_map"><code class="docutils literal notranslate"><span class="pre">ImgArray.focus_map()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.gabor_angle"><code class="docutils literal notranslate"><span class="pre">ImgArray.gabor_angle()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.gabor_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.gabor_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.gauss_correction"><code class="docutils literal notranslate"><span class="pre">ImgArray.gauss_correction()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.gauss_sm"><code class="docutils literal notranslate"><span class="pre">ImgArray.gauss_sm()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.gaussfit"><code class="docutils literal notranslate"><span class="pre">ImgArray.gaussfit()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.gaussian_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.gaussian_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.glcm_props"><code class="docutils literal notranslate"><span class="pre">ImgArray.glcm_props()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.hessian_angle"><code class="docutils literal notranslate"><span class="pre">ImgArray.hessian_angle()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.hessian_eig"><code class="docutils literal notranslate"><span class="pre">ImgArray.hessian_eig()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.hessian_eigval"><code class="docutils literal notranslate"><span class="pre">ImgArray.hessian_eigval()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.highpass_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.highpass_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.ifft"><code class="docutils literal notranslate"><span class="pre">ImgArray.ifft()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.inpaint"><code class="docutils literal notranslate"><span class="pre">ImgArray.inpaint()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.iradon"><code class="docutils literal notranslate"><span class="pre">ImgArray.iradon()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.kalman_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.kalman_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.label_threshold"><code class="docutils literal notranslate"><span class="pre">ImgArray.label_threshold()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.laplacian_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.laplacian_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.lbp"><code class="docutils literal notranslate"><span class="pre">ImgArray.lbp()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.local_dft"><code class="docutils literal notranslate"><span class="pre">ImgArray.local_dft()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.local_power_spectra"><code class="docutils literal notranslate"><span class="pre">ImgArray.local_power_spectra()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.log_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.log_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.lowpass_conv_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.lowpass_conv_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.lowpass_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.lowpass_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.lucy"><code class="docutils literal notranslate"><span class="pre">ImgArray.lucy()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.lucy_tv"><code class="docutils literal notranslate"><span class="pre">ImgArray.lucy_tv()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.mean_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.mean_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.median_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.median_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.ncc_filter"><code class="docutils literal notranslate"><span class="pre">ImgArray.ncc_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.opening"><code class="docutils literal notranslate"><span class="pre">ImgArray.opening()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.pad"><code class="docutils literal notranslate"><span class="pre">ImgArray.pad()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.pad_defocus"><code class="docutils literal notranslate"><span class="pre">ImgArray.pad_defocus()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.peak_local_max"><code class="docutils literal notranslate"><span class="pre">ImgArray.peak_local_max()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.power_spectra"><code class="docutils literal notranslate"><span class="pre">ImgArray.power_spectra()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.proj"><code class="docutils literal notranslate"><span class="pre">ImgArray.proj()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.radial_profile"><code class="docutils literal notranslate"><span class="pre">ImgArray.radial_profile()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.radon"><code class="docutils literal notranslate"><span class="pre">ImgArray.radon()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.random_walker"><code class="docutils literal notranslate"><span class="pre">ImgArray.random_walker()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.regionprops"><code class="docutils literal notranslate"><span class="pre">ImgArray.regionprops()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.remove_fine_objects"><code class="docutils literal notranslate"><span class="pre">ImgArray.remove_fine_objects()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.ImgArray.remove_large_objects"><code class="docutils literal notranslate"><span class="pre">ImgArray.remove_large_objects()</span></code></a></li>
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+</ul>
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+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.Label.as_larger_type"><code class="docutils literal notranslate"><span class="pre">Label.as_larger_type()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.Label.delete_label"><code class="docutils literal notranslate"><span class="pre">Label.delete_label()</span></code></a></li>
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+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.Label.relabel"><code class="docutils literal notranslate"><span class="pre">Label.relabel()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray"><code class="docutils literal notranslate"><span class="pre">LabeledArray</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.append_label"><code class="docutils literal notranslate"><span class="pre">LabeledArray.append_label()</span></code></a></li>
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+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.as_img_type"><code class="docutils literal notranslate"><span class="pre">LabeledArray.as_img_type()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.as_uint16"><code class="docutils literal notranslate"><span class="pre">LabeledArray.as_uint16()</span></code></a></li>
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+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.axes"><code class="docutils literal notranslate"><span class="pre">LabeledArray.axes</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.covariates"><code class="docutils literal notranslate"><span class="pre">LabeledArray.covariates</span></code></a></li>
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+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.for_each_channel"><code class="docutils literal notranslate"><span class="pre">LabeledArray.for_each_channel()</span></code></a></li>
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+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.imsave"><code class="docutils literal notranslate"><span class="pre">LabeledArray.imsave()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.imshow"><code class="docutils literal notranslate"><span class="pre">LabeledArray.imshow()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.label"><code class="docutils literal notranslate"><span class="pre">LabeledArray.label()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.label_if"><code class="docutils literal notranslate"><span class="pre">LabeledArray.label_if()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.labels"><code class="docutils literal notranslate"><span class="pre">LabeledArray.labels</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.map_coordinates"><code class="docutils literal notranslate"><span class="pre">LabeledArray.map_coordinates()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.pathprops"><code class="docutils literal notranslate"><span class="pre">LabeledArray.pathprops()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.pointprops"><code class="docutils literal notranslate"><span class="pre">LabeledArray.pointprops()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.proj_labels"><code class="docutils literal notranslate"><span class="pre">LabeledArray.proj_labels()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.range"><code class="docutils literal notranslate"><span class="pre">LabeledArray.range</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.remove_edges"><code class="docutils literal notranslate"><span class="pre">LabeledArray.remove_edges()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.reslice"><code class="docutils literal notranslate"><span class="pre">LabeledArray.reslice()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.rois"><code class="docutils literal notranslate"><span class="pre">LabeledArray.rois</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.rotated_crop"><code class="docutils literal notranslate"><span class="pre">LabeledArray.rotated_crop()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.set_scale"><code class="docutils literal notranslate"><span class="pre">LabeledArray.set_scale()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.specify"><code class="docutils literal notranslate"><span class="pre">LabeledArray.specify()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.spline_filter"><code class="docutils literal notranslate"><span class="pre">LabeledArray.spline_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.split"><code class="docutils literal notranslate"><span class="pre">LabeledArray.split()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LabeledArray.tile"><code class="docutils literal notranslate"><span class="pre">LabeledArray.tile()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray"><code class="docutils literal notranslate"><span class="pre">LazyImgArray</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.GB"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.GB</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.additional_props"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.additional_props</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.affine"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.affine()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.apply_dask_func"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.apply_dask_func()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.as_float"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.as_float()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.as_img_type"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.as_img_type()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.as_uint16"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.as_uint16()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.as_uint8"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.as_uint8()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.binning"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.binning()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.chunk_info"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.chunk_info</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.chunksize"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.chunksize</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.chunksizeof"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.chunksizeof()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.chunksizesof"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.chunksizesof()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.closing"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.closing()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.compute"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.compute()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.convolve"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.convolve()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.crop_center"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.crop_center()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.dilation"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.dilation()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.drift_correction"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.drift_correction()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.dtype"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.dtype</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.edge_filter"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.edge_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.erosion"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.erosion()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.fft"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.fft()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.gaussian_filter"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.gaussian_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.gb"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.gb</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.ifft"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.ifft()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.imsave"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.imsave()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.iradon"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.iradon()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.itemsize"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.itemsize</span></code></a></li>
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+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.max"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.max()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.mean"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.mean()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.mean_filter"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.mean_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.median_filter"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.median_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.metadata"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.metadata</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.min"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.min()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.name"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.name</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.ndim"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.ndim</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.opening"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.opening()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.pad"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.pad()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.power_spectra"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.power_spectra()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.proj"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.proj()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.radon"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.radon()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.rechunk"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.rechunk()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.release"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.release()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.shape"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.shape</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.size"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.size</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.sort_axes"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.sort_axes()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.source"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.source</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.spline_filter"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.spline_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.std"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.std()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.sum"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.sum()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.threshold"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.threshold()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.tiled"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.tiled</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.tiled_lowpass_filter"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.tiled_lowpass_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.track_drift"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.track_drift()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.transpose"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.transpose()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.value"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.value</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.LazyImgArray.wiener"><code class="docutils literal notranslate"><span class="pre">LazyImgArray.wiener()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.PhaseArray"><code class="docutils literal notranslate"><span class="pre">PhaseArray</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PhaseArray.additional_props"><code class="docutils literal notranslate"><span class="pre">PhaseArray.additional_props</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PhaseArray.as_exp"><code class="docutils literal notranslate"><span class="pre">PhaseArray.as_exp()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PhaseArray.binning"><code class="docutils literal notranslate"><span class="pre">PhaseArray.binning()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PhaseArray.border"><code class="docutils literal notranslate"><span class="pre">PhaseArray.border</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PhaseArray.deg2rad"><code class="docutils literal notranslate"><span class="pre">PhaseArray.deg2rad()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PhaseArray.imshow"><code class="docutils literal notranslate"><span class="pre">PhaseArray.imshow()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PhaseArray.map_coordinates"><code class="docutils literal notranslate"><span class="pre">PhaseArray.map_coordinates()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PhaseArray.mean_filter"><code class="docutils literal notranslate"><span class="pre">PhaseArray.mean_filter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PhaseArray.periodicity"><code class="docutils literal notranslate"><span class="pre">PhaseArray.periodicity</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PhaseArray.rad2deg"><code class="docutils literal notranslate"><span class="pre">PhaseArray.rad2deg()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PhaseArray.regionprops"><code class="docutils literal notranslate"><span class="pre">PhaseArray.regionprops()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PhaseArray.reslice"><code class="docutils literal notranslate"><span class="pre">PhaseArray.reslice()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PhaseArray.set_border"><code class="docutils literal notranslate"><span class="pre">PhaseArray.set_border()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PhaseArray.unit"><code class="docutils literal notranslate"><span class="pre">PhaseArray.unit</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.arrays.html#impy.arrays.PropArray"><code class="docutils literal notranslate"><span class="pre">PropArray</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PropArray.additional_props"><code class="docutils literal notranslate"><span class="pre">PropArray.additional_props</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PropArray.as_frame"><code class="docutils literal notranslate"><span class="pre">PropArray.as_frame()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PropArray.curve_fit"><code class="docutils literal notranslate"><span class="pre">PropArray.curve_fit()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PropArray.hist"><code class="docutils literal notranslate"><span class="pre">PropArray.hist()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PropArray.plot"><code class="docutils literal notranslate"><span class="pre">PropArray.plot()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#impy.arrays.PropArray.propname"><code class="docutils literal notranslate"><span class="pre">PropArray.propname</span></code></a></li>
+</ul>
+</li>
+</ul>
+</li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="impy.axes.html">impy.axes package</a><ul>
@@ -109,25 +737,194 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 </li>
 <li class="toctree-l1"><a class="reference internal" href="impy.frame.html">impy.frame package</a><ul>
 <li class="toctree-l2"><a class="reference internal" href="impy.frame.html#submodules">Submodules</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.frame.html#module-impy.frame.frames">impy.frame.frames module</a></li>
+<li class="toctree-l2"><a class="reference internal" href="impy.frame.html#module-impy.frame.frames">impy.frame.frames module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.frame.html#impy.frame.frames.AxesFrame"><code class="docutils literal notranslate"><span class="pre">AxesFrame</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.frame.html#impy.frame.frames.AxesFrame.as_standard_type"><code class="docutils literal notranslate"><span class="pre">AxesFrame.as_standard_type()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.frame.html#impy.frame.frames.AxesFrame.col_axes"><code class="docutils literal notranslate"><span class="pre">AxesFrame.col_axes</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.frame.html#impy.frame.frames.AxesFrame.get_coords"><code class="docutils literal notranslate"><span class="pre">AxesFrame.get_coords()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.frame.html#impy.frame.frames.AxesFrame.iter"><code class="docutils literal notranslate"><span class="pre">AxesFrame.iter()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.frame.html#impy.frame.frames.AxesFrame.proj"><code class="docutils literal notranslate"><span class="pre">AxesFrame.proj()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.frame.html#impy.frame.frames.AxesFrame.scale"><code class="docutils literal notranslate"><span class="pre">AxesFrame.scale</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.frame.html#impy.frame.frames.AxesFrame.set_scale"><code class="docutils literal notranslate"><span class="pre">AxesFrame.set_scale()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.frame.html#impy.frame.frames.AxesFrame.sort"><code class="docutils literal notranslate"><span class="pre">AxesFrame.sort()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.frame.html#impy.frame.frames.AxesFrame.split"><code class="docutils literal notranslate"><span class="pre">AxesFrame.split()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame"><code class="docutils literal notranslate"><span class="pre">MarkerFrame</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame.link"><code class="docutils literal notranslate"><span class="pre">MarkerFrame.link()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.frame.html#impy.frame.frames.PathFrame"><code class="docutils literal notranslate"><span class="pre">PathFrame</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.frame.html#impy.frame.frames.PathFrame.length"><code class="docutils literal notranslate"><span class="pre">PathFrame.length()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.frame.html#impy.frame.frames.TrackFrame"><code class="docutils literal notranslate"><span class="pre">TrackFrame</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.frame.html#impy.frame.frames.TrackFrame.as_path"><code class="docutils literal notranslate"><span class="pre">TrackFrame.as_path()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.frame.html#impy.frame.frames.TrackFrame.emsd"><code class="docutils literal notranslate"><span class="pre">TrackFrame.emsd()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.frame.html#impy.frame.frames.TrackFrame.filter_stubs"><code class="docutils literal notranslate"><span class="pre">TrackFrame.filter_stubs()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.frame.html#impy.frame.frames.TrackFrame.imsd"><code class="docutils literal notranslate"><span class="pre">TrackFrame.imsd()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.frame.html#impy.frame.frames.TrackFrame.msd"><code class="docutils literal notranslate"><span class="pre">TrackFrame.msd()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.frame.html#impy.frame.frames.TrackFrame.track_drift"><code class="docutils literal notranslate"><span class="pre">TrackFrame.track_drift()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.frame.html#impy.frame.frames.tp_no_verbose"><code class="docutils literal notranslate"><span class="pre">tp_no_verbose()</span></code></a></li>
+</ul>
+</li>
 <li class="toctree-l2"><a class="reference internal" href="impy.frame.html#module-impy.frame">Module contents</a></li>
 </ul>
 </li>
+<li class="toctree-l1"><a class="reference internal" href="impy.lazy.html">impy.lazy package</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="impy.lazy.html#submodules">Submodules</a></li>
+<li class="toctree-l2"><a class="reference internal" href="impy.lazy.html#module-impy.lazy.core">impy.lazy.core module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.lazy.html#impy.lazy.core.arange"><code class="docutils literal notranslate"><span class="pre">arange()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.lazy.html#impy.lazy.core.array"><code class="docutils literal notranslate"><span class="pre">array()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.lazy.html#impy.lazy.core.asarray"><code class="docutils literal notranslate"><span class="pre">asarray()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.lazy.html#impy.lazy.core.empty"><code class="docutils literal notranslate"><span class="pre">empty()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.lazy.html#impy.lazy.core.full"><code class="docutils literal notranslate"><span class="pre">full()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.lazy.html#impy.lazy.core.imread"><code class="docutils literal notranslate"><span class="pre">imread()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.lazy.html#impy.lazy.core.indices"><code class="docutils literal notranslate"><span class="pre">indices()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.lazy.html#impy.lazy.core.ones"><code class="docutils literal notranslate"><span class="pre">ones()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.lazy.html#impy.lazy.core.zeros"><code class="docutils literal notranslate"><span class="pre">zeros()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.lazy.html#module-impy.lazy.random">impy.lazy.random module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.lazy.html#impy.lazy.random.ImageGenerator"><code class="docutils literal notranslate"><span class="pre">ImageGenerator</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.lazy.html#impy.lazy.random.ImageGenerator.normal"><code class="docutils literal notranslate"><span class="pre">ImageGenerator.normal()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.lazy.html#impy.lazy.random.ImageGenerator.poisson"><code class="docutils literal notranslate"><span class="pre">ImageGenerator.poisson()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.lazy.html#impy.lazy.random.ImageGenerator.random"><code class="docutils literal notranslate"><span class="pre">ImageGenerator.random()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.lazy.html#impy.lazy.random.ImageGenerator.random_uint16"><code class="docutils literal notranslate"><span class="pre">ImageGenerator.random_uint16()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.lazy.html#impy.lazy.random.ImageGenerator.random_uint8"><code class="docutils literal notranslate"><span class="pre">ImageGenerator.random_uint8()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.lazy.html#impy.lazy.random.ImageGenerator.standard_exponential"><code class="docutils literal notranslate"><span class="pre">ImageGenerator.standard_exponential()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.lazy.html#impy.lazy.random.ImageGenerator.standard_normal"><code class="docutils literal notranslate"><span class="pre">ImageGenerator.standard_normal()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.lazy.html#impy.lazy.random.default_rng"><code class="docutils literal notranslate"><span class="pre">default_rng()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.lazy.html#impy.lazy.random.normal"><code class="docutils literal notranslate"><span class="pre">normal()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.lazy.html#impy.lazy.random.random"><code class="docutils literal notranslate"><span class="pre">random()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.lazy.html#impy.lazy.random.random_uint16"><code class="docutils literal notranslate"><span class="pre">random_uint16()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.lazy.html#impy.lazy.random.random_uint8"><code class="docutils literal notranslate"><span class="pre">random_uint8()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.lazy.html#module-impy.lazy">Module contents</a></li>
+</ul>
+</li>
 <li class="toctree-l1"><a class="reference internal" href="impy.utils.html">impy.utils package</a><ul>
 <li class="toctree-l2"><a class="reference internal" href="impy.utils.html#submodules">Submodules</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.utils.html#module-impy.utils.axesop">impy.utils.axesop module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.utils.html#module-impy.utils.deco">impy.utils.deco module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.utils.html#module-impy.utils.gauss">impy.utils.gauss module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.utils.html#module-impy.utils.misc">impy.utils.misc module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.utils.html#module-impy.utils.slicer">impy.utils.slicer module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.utils.html#module-impy.utils.utilcls">impy.utils.utilcls module</a></li>
+<li class="toctree-l2"><a class="reference internal" href="impy.utils.html#module-impy.utils.axesop">impy.utils.axesop module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.axesop.add_axes"><code class="docutils literal notranslate"><span class="pre">add_axes()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.axesop.complement_axes"><code class="docutils literal notranslate"><span class="pre">complement_axes()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.axesop.find_first_appeared"><code class="docutils literal notranslate"><span class="pre">find_first_appeared()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.axesop.slice_axes"><code class="docutils literal notranslate"><span class="pre">slice_axes()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.axesop.switch_slice"><code class="docutils literal notranslate"><span class="pre">switch_slice()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.utils.html#module-impy.utils.deco">impy.utils.deco module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.deco.check_input_and_output"><code class="docutils literal notranslate"><span class="pre">check_input_and_output()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.deco.check_input_and_output_lazy"><code class="docutils literal notranslate"><span class="pre">check_input_and_output_lazy()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.deco.dims_to_spatial_axes"><code class="docutils literal notranslate"><span class="pre">dims_to_spatial_axes()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.deco.same_dtype"><code class="docutils literal notranslate"><span class="pre">same_dtype()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.utils.html#module-impy.utils.gauss">impy.utils.gauss module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.DiagonalGaussian"><code class="docutils literal notranslate"><span class="pre">DiagonalGaussian</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.DiagonalGaussian.asdict"><code class="docutils literal notranslate"><span class="pre">DiagonalGaussian.asdict()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.DiagonalGaussian.fit"><code class="docutils literal notranslate"><span class="pre">DiagonalGaussian.fit()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.DiagonalGaussian.generate"><code class="docutils literal notranslate"><span class="pre">DiagonalGaussian.generate()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.DiagonalGaussian.mu"><code class="docutils literal notranslate"><span class="pre">DiagonalGaussian.mu</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.DiagonalGaussian.ndim"><code class="docutils literal notranslate"><span class="pre">DiagonalGaussian.ndim</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.DiagonalGaussian.params"><code class="docutils literal notranslate"><span class="pre">DiagonalGaussian.params</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.DiagonalGaussian.rescale"><code class="docutils literal notranslate"><span class="pre">DiagonalGaussian.rescale()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.DiagonalGaussian.sg"><code class="docutils literal notranslate"><span class="pre">DiagonalGaussian.sg</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.DiagonalGaussian.shift"><code class="docutils literal notranslate"><span class="pre">DiagonalGaussian.shift()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.Gaussian"><code class="docutils literal notranslate"><span class="pre">Gaussian</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.Gaussian.mu_inrange"><code class="docutils literal notranslate"><span class="pre">Gaussian.mu_inrange()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.Gaussian.sg_inrange"><code class="docutils literal notranslate"><span class="pre">Gaussian.sg_inrange()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.GaussianBackground"><code class="docutils literal notranslate"><span class="pre">GaussianBackground</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.GaussianParticle"><code class="docutils literal notranslate"><span class="pre">GaussianParticle</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.diagonal_gaussian"><code class="docutils literal notranslate"><span class="pre">diagonal_gaussian()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.masked_square"><code class="docutils literal notranslate"><span class="pre">masked_square()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.gauss.square"><code class="docutils literal notranslate"><span class="pre">square()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.utils.html#module-impy.utils.misc">impy.utils.misc module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.misc.check_nd"><code class="docutils literal notranslate"><span class="pre">check_nd()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.misc.largest_zeros"><code class="docutils literal notranslate"><span class="pre">largest_zeros()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.utils.html#module-impy.utils.slicer">impy.utils.slicer module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.slicer.axis_targeted_slicing"><code class="docutils literal notranslate"><span class="pre">axis_targeted_slicing()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.slicer.solve_slicer"><code class="docutils literal notranslate"><span class="pre">solve_slicer()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.slicer.str_to_slice"><code class="docutils literal notranslate"><span class="pre">str_to_slice()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.utils.html#module-impy.utils.utilcls">impy.utils.utilcls module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.utils.html#impy.utils.utilcls.ImportOnRequest"><code class="docutils literal notranslate"><span class="pre">ImportOnRequest</span></code></a></li>
+</ul>
+</li>
 <li class="toctree-l2"><a class="reference internal" href="impy.utils.html#module-impy.utils">Module contents</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="impy.viewer.html">impy.viewer package</a><ul>
 <li class="toctree-l2"><a class="reference internal" href="impy.viewer.html#submodules">Submodules</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.viewer.html#module-impy.viewer.utils">impy.viewer.utils module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.viewer.html#module-impy.viewer.viewer">impy.viewer.viewer module</a></li>
+<li class="toctree-l2"><a class="reference internal" href="impy.viewer.html#module-impy.viewer.utils">impy.viewer.utils module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.ComplexArrayView"><code class="docutils literal notranslate"><span class="pre">ComplexArrayView</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.ComplexArrayView.data_raw"><code class="docutils literal notranslate"><span class="pre">ComplexArrayView.data_raw</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.ComplexArrayView.dtype"><code class="docutils literal notranslate"><span class="pre">ComplexArrayView.dtype</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.ComplexArrayView.nbytes"><code class="docutils literal notranslate"><span class="pre">ComplexArrayView.nbytes</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.ComplexArrayView.ndim"><code class="docutils literal notranslate"><span class="pre">ComplexArrayView.ndim</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.ComplexArrayView.shape"><code class="docutils literal notranslate"><span class="pre">ComplexArrayView.shape</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.add_dask"><code class="docutils literal notranslate"><span class="pre">add_dask()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.add_labeledarray"><code class="docutils literal notranslate"><span class="pre">add_labeledarray()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.add_labels"><code class="docutils literal notranslate"><span class="pre">add_labels()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.add_paths"><code class="docutils literal notranslate"><span class="pre">add_paths()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.add_points"><code class="docutils literal notranslate"><span class="pre">add_points()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.add_rois"><code class="docutils literal notranslate"><span class="pre">add_rois()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.add_tracks"><code class="docutils literal notranslate"><span class="pre">add_tracks()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.front_image"><code class="docutils literal notranslate"><span class="pre">front_image()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.get_a_selected_layer"><code class="docutils literal notranslate"><span class="pre">get_a_selected_layer()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.get_viewer_scale"><code class="docutils literal notranslate"><span class="pre">get_viewer_scale()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.iter_layer"><code class="docutils literal notranslate"><span class="pre">iter_layer()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.iter_selected_layer"><code class="docutils literal notranslate"><span class="pre">iter_selected_layer()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.layer_to_impy_object"><code class="docutils literal notranslate"><span class="pre">layer_to_impy_object()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.make_world_scale"><code class="docutils literal notranslate"><span class="pre">make_world_scale()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.to_labels"><code class="docutils literal notranslate"><span class="pre">to_labels()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.utils.viewer_imread"><code class="docutils literal notranslate"><span class="pre">viewer_imread()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.viewer.html#module-impy.viewer.viewer">impy.viewer.viewer module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers"><code class="docutils literal notranslate"><span class="pre">napariViewers</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.add"><code class="docutils literal notranslate"><span class="pre">napariViewers.add()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.add_image"><code class="docutils literal notranslate"><span class="pre">napariViewers.add_image()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.add_labels"><code class="docutils literal notranslate"><span class="pre">napariViewers.add_labels()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.add_points"><code class="docutils literal notranslate"><span class="pre">napariViewers.add_points()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.add_shapes"><code class="docutils literal notranslate"><span class="pre">napariViewers.add_shapes()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.add_surface"><code class="docutils literal notranslate"><span class="pre">napariViewers.add_surface()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.add_table"><code class="docutils literal notranslate"><span class="pre">napariViewers.add_table()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.add_tracks"><code class="docutils literal notranslate"><span class="pre">napariViewers.add_tracks()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.add_vectors"><code class="docutils literal notranslate"><span class="pre">napariViewers.add_vectors()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.axes"><code class="docutils literal notranslate"><span class="pre">napariViewers.axes</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.axisof"><code class="docutils literal notranslate"><span class="pre">napariViewers.axisof()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.current_slice"><code class="docutils literal notranslate"><span class="pre">napariViewers.current_slice</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.cursor_pos"><code class="docutils literal notranslate"><span class="pre">napariViewers.cursor_pos</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.cursor_to_pixel"><code class="docutils literal notranslate"><span class="pre">napariViewers.cursor_to_pixel()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.get"><code class="docutils literal notranslate"><span class="pre">napariViewers.get()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.goto"><code class="docutils literal notranslate"><span class="pre">napariViewers.goto()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.layers"><code class="docutils literal notranslate"><span class="pre">napariViewers.layers</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.scale"><code class="docutils literal notranslate"><span class="pre">napariViewers.scale</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.selection"><code class="docutils literal notranslate"><span class="pre">napariViewers.selection</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.start"><code class="docutils literal notranslate"><span class="pre">napariViewers.start()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.stepof"><code class="docutils literal notranslate"><span class="pre">napariViewers.stepof()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.viewer.html#impy.viewer.viewer.napariViewers.viewer"><code class="docutils literal notranslate"><span class="pre">napariViewers.viewer</span></code></a></li>
+</ul>
+</li>
+</ul>
+</li>
 <li class="toctree-l2"><a class="reference internal" href="impy.viewer.html#module-impy.viewer">Module contents</a></li>
 </ul>
 </li>
@@ -135,10 +932,10 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 </div>
 </section>
 <section id="submodules">
-<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline">¶</a></h2>
+<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this heading">¶</a></h2>
 </section>
 <section id="module-impy.array_api">
-<span id="impy-array-api-module"></span><h2>impy.array_api module<a class="headerlink" href="#module-impy.array_api" title="Permalink to this headline">¶</a></h2>
+<span id="impy-array-api-module"></span><h2>impy.array_api module<a class="headerlink" href="#module-impy.array_api" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.array_api.XP">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.array_api.</span></span><span class="sig-name descname"><span class="pre">XP</span></span><a class="reference internal" href="../_modules/impy/array_api.html#XP"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.array_api.XP" title="Permalink to this definition">¶</a></dt>
@@ -162,7 +959,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.binder">
-<span id="impy-binder-module"></span><h2>impy.binder module<a class="headerlink" href="#module-impy.binder" title="Permalink to this headline">¶</a></h2>
+<span id="impy-binder-module"></span><h2>impy.binder module<a class="headerlink" href="#module-impy.binder" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.binder.bind">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.binder.</span></span><span class="sig-name descname"><span class="pre">bind</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">funcname</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">indtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outdtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'image'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ndim</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/binder.html#bind"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.binder.bind" title="Permalink to this definition">¶</a></dt>
@@ -172,7 +969,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 This class is designed as a kind of decorator class so that it can be used as decorator of
 any function or directly takes a function as the first argument.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>func</strong> (<em>callable</em>) – Function to wrapped and bound to ImgArray.</p></li>
 <li><p><strong>funcname</strong> (<em>str</em><em>, </em><em>optional</em>) – Method name after set to ImgArray. The name of <cite>func</cite> itself will be set by default.</p></li>
@@ -261,11 +1058,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.collections">
-<span id="impy-collections-module"></span><h2>impy.collections module<a class="headerlink" href="#module-impy.collections" title="Permalink to this headline">¶</a></h2>
+<span id="impy-collections-module"></span><h2>impy.collections module<a class="headerlink" href="#module-impy.collections" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.collections.DataDict">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.collections.</span></span><span class="sig-name descname"><span class="pre">DataDict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">d</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="p"><span class="pre">[</span></span><span class="pre">_K</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_T</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span><span class="p"><span class="pre">[</span></span><span class="pre">_K</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_T</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/collections.html#DataDict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.collections.DataDict" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">impy.collections.CollectionBase</span></code>, <code class="xref py py-class docutils literal notranslate"><span class="pre">MutableMapping</span></code>[<code class="xref py py-obj docutils literal notranslate"><span class="pre">impy.collections._K</span></code>, <code class="xref py py-obj docutils literal notranslate"><span class="pre">impy.collections._T</span></code>]</p>
+<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">CollectionBase</span></code>, <code class="xref py py-class docutils literal notranslate"><span class="pre">MutableMapping</span></code>[<code class="xref py py-obj docutils literal notranslate"><span class="pre">_K</span></code>, <code class="xref py py-obj docutils literal notranslate"><span class="pre">_T</span></code>]</p>
 <p>Dictionary-like class that can call same method for every object containded in the values. Accordingly,
 DataDict cannot have objects with different types as values. It is checked every time constructor or
 <cite>__setitem__</cite> method is called.</p>
@@ -284,17 +1081,17 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">apply</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/collections.html#DataDict.apply"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.collections.DataDict.apply" title="Permalink to this definition">¶</a></dt>
 <dd><p>Apply same function to each components. It can be any callable objects or any method of the components.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>func</strong> (<em>Callable</em><em> or </em><em>str</em>) – Function to be applied to each components.</p></li>
 <li><p><strong>args</strong> – Other arguments of <cite>func</cite>.</p></li>
 <li><p><strong>kwargs</strong> – Other keyword arguments of <cite>func</cite>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>This list is composed of {“name0”: func(data[0]), “name1”: func(data[1]), …}</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.collections.DataDict" title="impy.collections.DataDict">DataDict</a></p>
 </dd>
 </dl>
@@ -304,8 +1101,8 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.collections.DataList">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.collections.</span></span><span class="sig-name descname"><span class="pre">DataList</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">iterable</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">impy.collections._T</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">()</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/collections.html#DataList"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.collections.DataList" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">impy.collections.CollectionBase</span></code>, <code class="xref py py-class docutils literal notranslate"><span class="pre">MutableSequence</span></code>[<code class="xref py py-obj docutils literal notranslate"><span class="pre">impy.collections._T</span></code>]</p>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.collections.</span></span><span class="sig-name descname"><span class="pre">DataList</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">iterable</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">_T</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">()</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/collections.html#DataList"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.collections.DataList" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">CollectionBase</span></code>, <code class="xref py py-class docutils literal notranslate"><span class="pre">MutableSequence</span></code>[<code class="xref py py-obj docutils literal notranslate"><span class="pre">_T</span></code>]</p>
 <p>List-like class that can call same method for every object containded in it.
 Accordingly, DataList cannot have objects with different types. It is checked
 every time constructor or <cite>append</cite> method is called.</p>
@@ -328,17 +1125,17 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">apply</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.collections.DataList" title="impy.collections.DataList"><span class="pre">DataList</span></a></span></span><a class="reference internal" href="../_modules/impy/collections.html#DataList.apply"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.collections.DataList.apply" title="Permalink to this definition">¶</a></dt>
 <dd><p>Apply same function to each components. It can be any callable objects or any method of the components.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>func</strong> (<em>Callable</em><em> or </em><em>str</em>) – Function to be applied to each components.</p></li>
 <li><p><strong>args</strong> – Other arguments of <cite>func</cite>.</p></li>
 <li><p><strong>kwargs</strong> – Other keyword arguments of <cite>func</cite>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>This list is composed of [func(data[0]), func(data[1]), …]</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.collections.DataList" title="impy.collections.DataList">DataList</a></p>
 </dd>
 </dl>
@@ -346,7 +1143,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.collections.DataList.insert">
-<span class="sig-name descname"><span class="pre">insert</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">component</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">impy.collections._T</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="reference internal" href="../_modules/impy/collections.html#DataList.insert"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.collections.DataList.insert" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">insert</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">component</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">_T</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="reference internal" href="../_modules/impy/collections.html#DataList.insert"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.collections.DataList.insert" title="Permalink to this definition">¶</a></dt>
 <dd><p>S.insert(index, value) – insert value before index</p>
 </dd></dl>
 
@@ -354,10 +1151,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.core">
-<span id="impy-core-module"></span><h2>impy.core module<a class="headerlink" href="#module-impy.core" title="Permalink to this headline">¶</a></h2>
+<span id="impy-core-module"></span><h2>impy.core module<a class="headerlink" href="#module-impy.core" title="Permalink to this heading">¶</a></h2>
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.core.arange">
-<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">arange</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">stop</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">Ellipsis</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Any</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">Ellipsis</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#arange"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.arange" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">arange</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">stop</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#arange"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.arange" title="Permalink to this definition">¶</a></dt>
 <dd><blockquote>
 <div><p>impy version of numpy.arange. This function has additional parameters <code class="docutils literal notranslate"><span class="pre">axes</span></code>
 and <code class="docutils literal notranslate"><span class="pre">name</span></code>. Original docstring follows.</p>
@@ -366,6 +1163,8 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 <dt>name: str, optional</dt><dd><p>Image name.</p>
 </dd>
+<dt>like: MetaArray, optional</dt><dd><p>Reference array from which name and axes will be copied.</p>
+</dd>
 </dl>
 <p>arange([start,] stop[, step,], dtype=None, <a href="#id1"><span class="problematic" id="id2">*</span></a>, like=None)</p>
 </div></blockquote>
@@ -388,7 +1187,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <cite>numpy.linspace</cite>.</p>
 <p>See the Warning sections below for more information.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>start</strong> (<em>integer</em><em> or </em><em>real</em><em>, </em><em>optional</em>) – Start of interval.  The interval includes this value.  The default
 start value is 0.</p></li>
@@ -412,7 +1211,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p><p><strong>arange</strong> – Array of evenly spaced values.</p>
 <p>For floating point arguments, the length of the result is
 <code class="docutils literal notranslate"><span class="pre">ceil((stop</span> <span class="pre">-</span> <span class="pre">start)/step)</span></code>.  Because of floating point overflow,
@@ -420,7 +1219,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 than <cite>stop</cite>.</p>
 </p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>ndarray</p>
 </dd>
 </dl>
@@ -442,9 +1241,9 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </div>
 <p>In such cases, the use of <cite>numpy.linspace</cite> should be preferred.</p>
 <p>The built-in <code class="xref py py-class docutils literal notranslate"><span class="pre">range</span></code> generates <span class="xref std std-doc">Python built-in integers
-that have arbitrary size</span>, while <cite>numpy.arange</cite> produces
-<cite>numpy.int32</cite> or <cite>numpy.int64</cite> numbers. This may result in incorrect
-results for large integer values:</p>
+that have arbitrary size</span>, while <cite>numpy.arange</cite>
+produces <cite>numpy.int32</cite> or <cite>numpy.int64</cite> numbers. This may result in
+incorrect results for large integer values:</p>
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">power</span> <span class="o">=</span> <span class="mi">40</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">modulo</span> <span class="o">=</span> <span class="mi">10000</span>
 <span class="gp">&gt;&gt;&gt; </span><span class="n">x1</span> <span class="o">=</span> <span class="p">[(</span><span class="n">n</span> <span class="o">**</span> <span class="n">power</span><span class="p">)</span> <span class="o">%</span> <span class="n">modulo</span> <span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">8</span><span class="p">)]</span>
@@ -466,6 +1265,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.mgrid</span></code></dt><dd><p>Grid-shaped arrays of evenly spaced numbers in N-dimensions.</p>
 </dd>
 </dl>
+<p><span class="xref std std-ref">how-to-partition</span></p>
 </div>
 <p class="rubric">Examples</p>
 <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
@@ -485,7 +1285,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">array</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">/</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">copy</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#array"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.array" title="Permalink to this definition">¶</a></dt>
 <dd><p>make an ImgArray object, like <code class="docutils literal notranslate"><span class="pre">np.array(x)</span></code></p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>arr</strong> (<em>array-like</em>) – Base array.</p></li>
 <li><p><strong>copy</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, a copy of the original array is made.</p></li>
@@ -494,7 +1294,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>axes</strong> (<em>str</em><em>, </em><em>optional</em>) – Image axes.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -502,10 +1302,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.core.asarray">
-<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">asarray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#asarray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.asarray" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">asarray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#asarray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.asarray" title="Permalink to this definition">¶</a></dt>
 <dd><p>make an ImgArray object, like <code class="docutils literal notranslate"><span class="pre">np.asarray(x)</span></code></p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>arr</strong> (<em>array-like</em>) – Base array.</p></li>
 <li><p><strong>dtype</strong> (<em>data type</em><em>, </em><em>optional</em>) – Image data type.</p></li>
@@ -514,7 +1314,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>copy</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, a copy of the original array is made.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -522,16 +1322,16 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.core.asbigarray">
-<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">asbigarray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray" title="impy.arrays.big.BigImgArray"><span class="pre">BigImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#asbigarray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.asbigarray" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">asbigarray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray" title="impy.arrays.big.BigImgArray"><span class="pre">BigImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#asbigarray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.asbigarray" title="Permalink to this definition">¶</a></dt>
 <dd><p>Make an BigImgArray object from other types of array.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>arr</strong> (<em>array-like</em>) – Base array.</p></li>
 <li><p><strong>{}</strong> – </p></li>
 </ul>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray" title="impy.arrays.big.BigImgArray">BigImgArray</a></p>
 </dd>
 </dl>
@@ -539,12 +1339,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.core.aslabel">
-<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">aslabel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#aslabel"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.aslabel" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">aslabel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#aslabel"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.aslabel" title="Permalink to this definition">¶</a></dt>
 <dd><p>Make an Label object.</p>
 <p>This function helps to create a Label object from an array. Dtype check is performed
 on array creation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>arr</strong> (<em>array-like</em>) – Base array.</p></li>
 <li><p><strong>dtype</strong> (<em>data type</em><em>, </em><em>optional</em>) – Image data type.</p></li>
@@ -552,7 +1352,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>axes</strong> (<em>str</em><em>, </em><em>optional</em>) – Image axes.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.label.Label" title="impy.arrays.label.Label">Label</a></p>
 </dd>
 </dl>
@@ -560,23 +1360,8 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.core.aslazy">
-<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">aslazy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#aslazy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.aslazy" title="Permalink to this definition">¶</a></dt>
-<dd><p>Make an LazyImgArray object from other types of array.</p>
-<dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><ul class="simple">
-<li><p><strong>arr</strong> (<em>array-like</em>) – Base array.</p></li>
-<li><p><strong>dtype</strong> (<em>data type</em><em>, </em><em>optional</em>) – Image data type.</p></li>
-<li><p><strong>name</strong> (<em>str</em><em>, </em><em>optional</em>) – Name of image.</p></li>
-<li><p><strong>axes</strong> (<em>str</em><em>, </em><em>optional</em>) – Image axes.</p></li>
-<li><p><strong>chunks</strong> (<em>int</em><em>, </em><em>tuple</em>) – How to chunk the array. For details see <code class="docutils literal notranslate"><span class="pre">dask.array.from_array</span></code>.</p></li>
-</ul>
-</dd>
-<dt class="field-even">Return type</dt>
-<dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
-</dd>
-</dl>
-</dd></dl>
+<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">aslazy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#aslazy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.aslazy" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.core.big_imread">
@@ -584,7 +1369,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dd><p>Read an image lazily. Image file is first opened as an memory map, and subsequently converted
 to <cite>numpy.ndarray</cite> or <cite>cupy.ndarray</cite> chunkwise by <cite>dask.array.map_blocks</cite>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>path</strong> (<em>str</em>) – Path to the file.</p></li>
 <li><p><strong>chunks</strong> (<em>optional</em>) – Specify chunk sizes. By default, yx-axes are assigned to the same chunk for every slice of
@@ -593,7 +1378,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>squeeze</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True and there is one-sized axis, then call <cite>np.squeeze</cite>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.big.BigImgArray" title="impy.arrays.big.BigImgArray">BigImgArray</a></p>
 </dd>
 </dl>
@@ -601,26 +1386,26 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.core.broadcast_arrays">
-<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">broadcast_arrays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">arrays</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">impy.arrays.bases.metaarray.MetaArray</span></a></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">list</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">impy.arrays.bases.metaarray.MetaArray</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/core.html#broadcast_arrays"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.broadcast_arrays" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">broadcast_arrays</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">arrays</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">list</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">impy.arrays.bases.metaarray.MetaArray</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/core.html#broadcast_arrays"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.broadcast_arrays" title="Permalink to this definition">¶</a></dt>
 <dd><p>Broadcast input arrays to the same shape and axes</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.core.circular_mask">
-<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">circular_mask</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">nDFloat</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ShapeLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'center'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#circular_mask"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.circular_mask" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">circular_mask</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">radius</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">nDFloat</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ShapeLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">center</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'center'</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'center'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">soft</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out_value</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#circular_mask"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.circular_mask" title="Permalink to this definition">¶</a></dt>
 <dd><p>Make a circular or ellipsoid shaped mask. Region close to center will be filled with <code class="docutils literal notranslate"><span class="pre">False</span></code>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>radius</strong> (<em>float</em><em> or </em><em>array-like</em>) – Radius of non-mask region</p></li>
 <li><p><strong>shape</strong> (<em>tuple</em>) – Shape of mask.</p></li>
 <li><p><strong>center</strong> (<em>tuple</em><em> or </em><em>&quot;center&quot;</em>) – Center of circle. By default circle locates at the center.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Boolean image with zyx or yx axes</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -628,7 +1413,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.core.empty">
-<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">empty</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape:</span> <span class="pre">ShapeLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">DTypeLike</span> <span class="pre">=</span> <span class="pre">&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name:</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes:</span> <span class="pre">AxesLike</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like:</span> <span class="pre">MetaArray</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#empty"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.empty" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">empty</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape:</span> <span class="pre">ShapeLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">DTypeLike</span> <span class="pre">=</span> <span class="pre">&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name:</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes:</span> <span class="pre">AxesLike</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like:</span> <span class="pre">MetaArray</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#empty"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.empty" title="Permalink to this definition">¶</a></dt>
 <dd><blockquote>
 <div><p>impy version of numpy.empty. This function has additional parameters <code class="docutils literal notranslate"><span class="pre">axes</span></code>
 and <code class="docutils literal notranslate"><span class="pre">name</span></code>. Original docstring follows.</p>
@@ -637,14 +1422,16 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 <dt>name: str, optional</dt><dd><p>Image name.</p>
 </dd>
+<dt>like: MetaArray, optional</dt><dd><p>Reference array from which name and axes will be copied.</p>
+</dd>
 </dl>
 <p>empty(shape, dtype=float, order=’C’, <a href="#id3"><span class="problematic" id="id4">*</span></a>, like=None)</p>
 </div></blockquote>
 <p>Return a new array of given shape and type, without initializing entries.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>shape</strong> (<em>int</em><em> or </em><em>tuple of int</em>) – Shape of the empty array, e.g., <code class="docutils literal notranslate"><span class="pre">(2,</span> <span class="pre">3)</span></code> or <code class="docutils literal notranslate"><span class="pre">2</span></code>.</p></li>
+<li><p><strong>shape</strong> (<em>int</em><em> or </em><em>tuple</em><em> of </em><em>int</em>) – Shape of the empty array, e.g., <code class="docutils literal notranslate"><span class="pre">(2,</span> <span class="pre">3)</span></code> or <code class="docutils literal notranslate"><span class="pre">2</span></code>.</p></li>
 <li><p><strong>dtype</strong> (<em>data-type</em><em>, </em><em>optional</em>) – Desired output data-type for the array, e.g, <cite>numpy.int8</cite>. Default is
 <cite>numpy.float64</cite>.</p></li>
 <li><p><strong>order</strong> (<em>{'C'</em><em>, </em><em>'F'}</em><em>, </em><em>optional</em><em>, </em><em>default: 'C'</em>) – Whether to store multi-dimensional data in row-major
@@ -661,11 +1448,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p><strong>out</strong> – Array of uninitialized (arbitrary) data of the given shape, dtype, and
 order.  Object arrays will be initialized to None.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>ndarray</p>
 </dd>
 </dl>
@@ -702,7 +1489,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.core.full">
-<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">full</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape:</span> <span class="pre">ShapeLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fill_value:</span> <span class="pre">Any</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">DTypeLike</span> <span class="pre">=</span> <span class="pre">&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name:</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes:</span> <span class="pre">AxesLike</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like:</span> <span class="pre">MetaArray</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#full"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.full" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">full</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape:</span> <span class="pre">ShapeLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fill_value:</span> <span class="pre">Any</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">DTypeLike</span> <span class="pre">=</span> <span class="pre">&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name:</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes:</span> <span class="pre">AxesLike</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like:</span> <span class="pre">MetaArray</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#full"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.full" title="Permalink to this definition">¶</a></dt>
 <dd><blockquote>
 <div><p>impy version of numpy.full. This function has additional parameters <code class="docutils literal notranslate"><span class="pre">axes</span></code>
 and <code class="docutils literal notranslate"><span class="pre">name</span></code>. Original docstring follows.</p>
@@ -711,13 +1498,15 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 <dt>name: str, optional</dt><dd><p>Image name.</p>
 </dd>
+<dt>like: MetaArray, optional</dt><dd><p>Reference array from which name and axes will be copied.</p>
+</dd>
 </dl>
 </div></blockquote>
 <p>Return a new array of given shape and type, filled with <cite>fill_value</cite>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>shape</strong> (<em>int</em><em> or </em><em>sequence of ints</em>) – Shape of the new array, e.g., <code class="docutils literal notranslate"><span class="pre">(2,</span> <span class="pre">3)</span></code> or <code class="docutils literal notranslate"><span class="pre">2</span></code>.</p></li>
+<li><p><strong>shape</strong> (<em>int</em><em> or </em><em>sequence</em><em> of </em><em>ints</em>) – Shape of the new array, e.g., <code class="docutils literal notranslate"><span class="pre">(2,</span> <span class="pre">3)</span></code> or <code class="docutils literal notranslate"><span class="pre">2</span></code>.</p></li>
 <li><p><strong>fill_value</strong> (<em>scalar</em><em> or </em><em>array_like</em>) – Fill value.</p></li>
 <li><p><strong>dtype</strong> (<em>data-type</em><em>, </em><em>optional</em>) – <dl class="simple">
 <dt>The desired data-type for the array  The default, None, means</dt><dd><p><code class="docutils literal notranslate"><span class="pre">np.array(fill_value).dtype</span></code>.</p>
@@ -737,10 +1526,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p><strong>out</strong> – Array of <cite>fill_value</cite> with the given shape, dtype, and order.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>ndarray</p>
 </dd>
 </dl>
@@ -778,17 +1567,17 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">gaussian_kernel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ShapeLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sigma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">nDFloat</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">peak</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#gaussian_kernel"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.gaussian_kernel" title="Permalink to this definition">¶</a></dt>
 <dd><p>Make an Gaussian kernel or Gaussian image.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>shape</strong> (<em>tuple of int</em>) – Shape of image.</p></li>
+<li><p><strong>shape</strong> (<em>tuple</em><em> of </em><em>int</em>) – Shape of image.</p></li>
 <li><p><strong>sigma</strong> (<em>float</em><em> or </em><em>array-like</em><em>, </em><em>default is 1.0</em>) – Standard deviation of Gaussian.</p></li>
 <li><p><strong>peak</strong> (<em>float</em><em>, </em><em>default is 1.0</em>) – Peak intensity.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Gaussian image</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -800,7 +1589,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dd><p>Load image(s) from a path. You can read list of images from directories with
 wildcards or <code class="docutils literal notranslate"><span class="pre">&quot;$&quot;</span></code> in <code class="docutils literal notranslate"><span class="pre">path</span></code>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>path</strong> (<em>str</em>) – Path to the image or directory.</p></li>
 <li><p><strong>dtype</strong> (<em>Any type that np.dtype accepts</em>) – Data type of images.</p></li>
@@ -811,10 +1600,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>squeeze</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True, redundant dimensions will be squeezed.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Image data read from the file.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -831,18 +1620,18 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.core.imread_collection">
-<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">imread_collection</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="pre">np.ndarray</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">bool</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.collections.DataList" title="impy.collections.DataList"><span class="pre">DataList</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#imread_collection"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.imread_collection" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">imread_collection</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filt</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">bool</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.collections.DataList" title="impy.collections.DataList"><span class="pre">DataList</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#imread_collection"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.imread_collection" title="Permalink to this definition">¶</a></dt>
 <dd><p>Open images as ImgArray and store them in DataList.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>path</strong> (<em>str</em><em> or </em><em>list of str</em>) – Path than can be passed to <code class="docutils literal notranslate"><span class="pre">glob.glob</span></code>. If a list of path is given, all the matched
+<li><p><strong>path</strong> (<em>str</em><em> or </em><em>list</em><em> of </em><em>str</em>) – Path than can be passed to <code class="docutils literal notranslate"><span class="pre">glob.glob</span></code>. If a list of path is given, all the matched
 images will be read and concatenated into a DataList.</p></li>
 <li><p><strong>filt</strong> (<em>callable</em><em>, </em><em>optional</em>) – If specified, only images that satisfies filt(img)==True will be stored in the returned
 DataList.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="#impy.collections.DataList" title="impy.collections.DataList">DataList</a></p>
 </dd>
 </dl>
@@ -853,7 +1642,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">indices</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dimensions:</span> <span class="pre">ShapeLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">DTypeLike</span> <span class="pre">=</span> <span class="pre">&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name:</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes:</span> <span class="pre">AxesLike</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like:</span> <span class="pre">MetaArray</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">AxesTuple</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/core.html#indices"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.indices" title="Permalink to this definition">¶</a></dt>
 <dd><p>Copy of <code class="docutils literal notranslate"><span class="pre">numpy.indices</span></code>.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>dimensions</strong> (<em>shape-like</em>) – The shape of the grid.</p></li>
 <li><p><strong>dtype</strong> (<em>dtype</em><em>, </em><em>optional</em>) – Data type of the result.</p></li>
@@ -862,36 +1651,20 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>like</strong> (<a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><em>MetaArray</em></a><em>, </em><em>optional</em>) – Reference array from which name and axes will be copied.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Return type</dt>
-<dd class="field-even"><p>tuple of ImgArray</p>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
+<dd class="field-even"><p>tuple of <a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.core.lazy_imread">
-<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">lazy_imread</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#lazy_imread"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.lazy_imread" title="Permalink to this definition">¶</a></dt>
-<dd><p>Read an image lazily. Image file is first opened as an memory map, and subsequently converted
-to <cite>numpy.ndarray</cite> or <cite>cupy.ndarray</cite> chunkwise by <cite>dask.array.map_blocks</cite>.</p>
-<dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
-<dd class="field-odd"><ul class="simple">
-<li><p><strong>path</strong> (<em>str</em>) – Path to the file.</p></li>
-<li><p><strong>chunks</strong> (<em>optional</em>) – Specify chunk sizes. By default, yx-axes are assigned to the same chunk for every slice of
-image, whild chunk sizes of the rest of axes are automatically set with “auto” option.</p></li>
-<li><p><strong>name</strong> (<em>str</em><em>, </em><em>optional</em>) – Name of array.</p></li>
-<li><p><strong>squeeze</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True and there is one-sized axis, then call <cite>np.squeeze</cite>.</p></li>
-</ul>
-</dd>
-<dt class="field-even">Return type</dt>
-<dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
-</dd>
-</dl>
-</dd></dl>
+<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">lazy_imread</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#lazy_imread"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.lazy_imread" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.core.ones">
-<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">ones</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape:</span> <span class="pre">ShapeLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">DTypeLike</span> <span class="pre">=</span> <span class="pre">&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name:</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes:</span> <span class="pre">AxesLike</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like:</span> <span class="pre">MetaArray</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#ones"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.ones" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">ones</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape:</span> <span class="pre">ShapeLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">DTypeLike</span> <span class="pre">=</span> <span class="pre">&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name:</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes:</span> <span class="pre">AxesLike</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like:</span> <span class="pre">MetaArray</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#ones"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.ones" title="Permalink to this definition">¶</a></dt>
 <dd><blockquote>
 <div><p>impy version of numpy.ones. This function has additional parameters <code class="docutils literal notranslate"><span class="pre">axes</span></code>
 and <code class="docutils literal notranslate"><span class="pre">name</span></code>. Original docstring follows.</p>
@@ -900,13 +1673,15 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 <dt>name: str, optional</dt><dd><p>Image name.</p>
 </dd>
+<dt>like: MetaArray, optional</dt><dd><p>Reference array from which name and axes will be copied.</p>
+</dd>
 </dl>
 </div></blockquote>
 <p>Return a new array of given shape and type, filled with ones.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>shape</strong> (<em>int</em><em> or </em><em>sequence of ints</em>) – Shape of the new array, e.g., <code class="docutils literal notranslate"><span class="pre">(2,</span> <span class="pre">3)</span></code> or <code class="docutils literal notranslate"><span class="pre">2</span></code>.</p></li>
+<li><p><strong>shape</strong> (<em>int</em><em> or </em><em>sequence</em><em> of </em><em>ints</em>) – Shape of the new array, e.g., <code class="docutils literal notranslate"><span class="pre">(2,</span> <span class="pre">3)</span></code> or <code class="docutils literal notranslate"><span class="pre">2</span></code>.</p></li>
 <li><p><strong>dtype</strong> (<em>data-type</em><em>, </em><em>optional</em>) – The desired data-type for the array, e.g., <cite>numpy.int8</cite>.  Default is
 <cite>numpy.float64</cite>.</p></li>
 <li><p><strong>order</strong> (<em>{'C'</em><em>, </em><em>'F'}</em><em>, </em><em>optional</em><em>, </em><em>default: C</em>) – Whether to store multi-dimensional data in row-major
@@ -923,10 +1698,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p><strong>out</strong> – Array of ones with the given shape, dtype, and order.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>ndarray</p>
 </dd>
 </dl>
@@ -970,13 +1745,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">read_meta</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/core.html#read_meta"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.read_meta" title="Permalink to this definition">¶</a></dt>
 <dd><p>Read the metadata of an image file.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>path</strong> (<em>str</em>) – Path to the image file.</p>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Dictionary of keys {“axes”, “scale”, “metadata”}</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>dict</p>
 </dd>
 </dl>
@@ -990,16 +1765,16 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.core.sample_image">
-<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">sample_image</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#sample_image"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.sample_image" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">sample_image</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#sample_image"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.sample_image" title="Permalink to this definition">¶</a></dt>
 <dd><p>Get sample images from <code class="docutils literal notranslate"><span class="pre">skimage</span></code> and convert it into ImgArray.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>name</strong> (<em>str</em>) – Name of sample image, such as “camera”.</p>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Sample image.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1007,7 +1782,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.core.zeros">
-<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">zeros</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape:</span> <span class="pre">ShapeLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">DTypeLike</span> <span class="pre">=</span> <span class="pre">&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name:</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes:</span> <span class="pre">AxesLike</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like:</span> <span class="pre">MetaArray</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#zeros"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.zeros" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.core.</span></span><span class="sig-name descname"><span class="pre">zeros</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape:</span> <span class="pre">ShapeLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">DTypeLike</span> <span class="pre">=</span> <span class="pre">&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name:</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes:</span> <span class="pre">AxesLike</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like:</span> <span class="pre">MetaArray</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/core.html#zeros"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.core.zeros" title="Permalink to this definition">¶</a></dt>
 <dd><blockquote>
 <div><p>impy version of numpy.zeros. This function has additional parameters <code class="docutils literal notranslate"><span class="pre">axes</span></code>
 and <code class="docutils literal notranslate"><span class="pre">name</span></code>. Original docstring follows.</p>
@@ -1016,14 +1791,16 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 <dt>name: str, optional</dt><dd><p>Image name.</p>
 </dd>
+<dt>like: MetaArray, optional</dt><dd><p>Reference array from which name and axes will be copied.</p>
+</dd>
 </dl>
 <p>zeros(shape, dtype=float, order=’C’, <a href="#id5"><span class="problematic" id="id6">*</span></a>, like=None)</p>
 </div></blockquote>
 <p>Return a new array of given shape and type, filled with zeros.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>shape</strong> (<em>int</em><em> or </em><em>tuple of ints</em>) – Shape of the new array, e.g., <code class="docutils literal notranslate"><span class="pre">(2,</span> <span class="pre">3)</span></code> or <code class="docutils literal notranslate"><span class="pre">2</span></code>.</p></li>
+<li><p><strong>shape</strong> (<em>int</em><em> or </em><em>tuple</em><em> of </em><em>ints</em>) – Shape of the new array, e.g., <code class="docutils literal notranslate"><span class="pre">(2,</span> <span class="pre">3)</span></code> or <code class="docutils literal notranslate"><span class="pre">2</span></code>.</p></li>
 <li><p><strong>dtype</strong> (<em>data-type</em><em>, </em><em>optional</em>) – The desired data-type for the array, e.g., <cite>numpy.int8</cite>.  Default is
 <cite>numpy.float64</cite>.</p></li>
 <li><p><strong>order</strong> (<em>{'C'</em><em>, </em><em>'F'}</em><em>, </em><em>optional</em><em>, </em><em>default: 'C'</em>) – Whether to store multi-dimensional data in row-major
@@ -1040,10 +1817,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p><strong>out</strong> – Array of zeros with the given shape, dtype, and order.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>ndarray</p>
 </dd>
 </dl>
@@ -1089,13 +1866,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.correlation">
-<span id="impy-correlation-module"></span><h2>impy.correlation module<a class="headerlink" href="#module-impy.correlation" title="Permalink to this headline">¶</a></h2>
+<span id="impy-correlation-module"></span><h2>impy.correlation module<a class="headerlink" href="#module-impy.correlation" title="Permalink to this heading">¶</a></h2>
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.correlation.fourier_ncc">
-<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">fourier_ncc</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#fourier_ncc"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.fourier_ncc" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">fourier_ncc</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#fourier_ncc"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.fourier_ncc" title="Permalink to this definition">¶</a></dt>
 <dd><p>Normalized Cross Correlation in Fourier space.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1116,10 +1893,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Correlation value(s).</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray">PropArray</a> or float</p>
 </dd>
 </dl>
@@ -1127,7 +1904,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.correlation.fourier_shell_correlation">
-<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">fourier_shell_correlation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">dfreq</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.02</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">numpy.ndarray</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">numpy.ndarray</span><span class="p"><span class="pre">]</span></span></span></span><a class="headerlink" href="#impy.correlation.fourier_shell_correlation" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">fourier_shell_correlation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">dfreq</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.02</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">numpy.ndarray</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">numpy.ndarray</span><span class="p"><span class="pre">]</span></span></span></span><a class="headerlink" href="#impy.correlation.fourier_shell_correlation" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate Fourier Shell Correlation (FSC; or Fourier Ring Correlation, FRC, for 2-D images)
 between two images. FSC is defined as:</p>
 <div class="math notranslate nohighlight">
@@ -1140,7 +1917,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </div>
 <p>and frequencies calculated in each bin will be 0.05, 0.15, …, 0.45.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1152,10 +1929,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>The first array is frequency, and the second array is FSC.</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p>Two np.ndarray</p>
 </dd>
 </dl>
@@ -1163,10 +1940,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.correlation.fourier_zncc">
-<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">fourier_zncc</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#fourier_zncc"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.fourier_zncc" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">fourier_zncc</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#fourier_zncc"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.fourier_zncc" title="Permalink to this definition">¶</a></dt>
 <dd><p>Zero-mean Normalized Cross Correlation in Fourier space.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1187,10 +1964,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Correlation value(s).</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray">PropArray</a> or float</p>
 </dd>
 </dl>
@@ -1198,7 +1975,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.correlation.fsc">
-<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">fsc</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">dfreq</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.02</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">numpy.ndarray</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">numpy.ndarray</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#fsc"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.fsc" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">fsc</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">dfreq</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.02</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">numpy.ndarray</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">numpy.ndarray</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#fsc"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.fsc" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate Fourier Shell Correlation (FSC; or Fourier Ring Correlation, FRC, for 2-D images)
 between two images. FSC is defined as:</p>
 <div class="math notranslate nohighlight">
@@ -1211,7 +1988,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </div>
 <p>and frequencies calculated in each bin will be 0.05, 0.15, …, 0.45.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1223,10 +2000,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>The first array is frequency, and the second array is FSC.</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p>Two np.ndarray</p>
 </dd>
 </dl>
@@ -1239,7 +2016,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <p>This function takes Fourier transformed images as input. If you have to repetitively
 use a same template image, this function is faster.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1252,10 +2029,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Landscape image.</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1263,12 +2040,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.correlation.ft_pcc_maximum">
-<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">ft_pcc_maximum</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">np.ndarray</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#ft_pcc_maximum"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.ft_pcc_maximum" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">ft_pcc_maximum</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#ft_pcc_maximum"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.ft_pcc_maximum" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate lateral shift between two images using phase cross correlation.</p>
 <p>This function takes Fourier transformed images as input. If you have to repetitively
 use a same template image, this function is faster.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1283,10 +2060,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Shift in pixel.</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p>np.ndarray</p>
 </dd>
 </dl>
@@ -1294,12 +2071,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.correlation.ft_pcc_maximum_with_corr">
-<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">ft_pcc_maximum_with_corr</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">np.ndarray</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#ft_pcc_maximum_with_corr"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.ft_pcc_maximum_with_corr" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">ft_pcc_maximum_with_corr</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#ft_pcc_maximum_with_corr"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.ft_pcc_maximum_with_corr" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate lateral shift between two images using phase cross correlation.</p>
 <p>This function takes Fourier transformed images as input. If you have to repetitively
 use a same template image, this function is faster.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1314,10 +2091,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Shift in pixel and phase cross correlation.</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p>np.ndarray and float</p>
 </dd>
 </dl>
@@ -1325,13 +2102,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.correlation.manders_coloc">
-<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">manders_coloc</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">np.ndarray</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#manders_coloc"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.manders_coloc" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">manders_coloc</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#manders_coloc"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.manders_coloc" title="Permalink to this definition">¶</a></dt>
 <dd><p>Manders’ correlation coefficient. This is defined as following:</p>
 <p><span class="math notranslate nohighlight">\(r = \frac{\sum_{i \in I_{ref}} I_i}{\sum_{i} I_i}\)</span></p>
 <p>This value is NOT independent of background intensity. You need to correctly subtract
 background from self. This value is NOT interchangable between channels.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1341,10 +2118,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 For instance, <code class="docutils literal notranslate"><span class="pre">dims=&quot;yx&quot;</span></code> means axes <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;</span></code> and <code class="docutils literal notranslate"><span class="pre">&quot;x&quot;</span></code> are spatial dimensions and function is applied to other axes, say, <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code> and/or <code class="docutils literal notranslate"><span class="pre">&quot;c&quot;</span></code>. <code class="docutils literal notranslate"><span class="pre">dims=3</span></code> is equivalent to <code class="docutils literal notranslate"><span class="pre">dims=&quot;zyx&quot;</span></code>.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Correlation coefficient(s).</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray">PropArray</a> or float</p>
 </dd>
 </dl>
@@ -1352,10 +2129,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.correlation.ncc">
-<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">ncc</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#ncc"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.ncc" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">ncc</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#ncc"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.ncc" title="Permalink to this definition">¶</a></dt>
 <dd><p>Normalized Cross Correlation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1376,10 +2153,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Correlation value(s).</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray">PropArray</a> or float</p>
 </dd>
 </dl>
@@ -1387,12 +2164,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.correlation.nmi">
-<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">nmi</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bins</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#nmi"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.nmi" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">nmi</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bins</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#nmi"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.nmi" title="Permalink to this definition">¶</a></dt>
 <dd><p>Normalized Mutual Information.</p>
 <p><span class="math notranslate nohighlight">\(Y(A, B) = \frac{H(A) + H(B)}{H(A, B)}\)</span></p>
 <p>See “Elegant SciPy”</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1415,10 +2192,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Correlation value(s).</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray">PropArray</a> or float</p>
 </dd>
 </dl>
@@ -1429,7 +2206,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">pcc_landscape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/correlation.html#pcc_landscape"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.pcc_landscape" title="Permalink to this definition">¶</a></dt>
 <dd><p>Create landscape of phase cross correlation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1442,10 +2219,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Landscape image.</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1453,12 +2230,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.correlation.pcc_maximum">
-<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">pcc_maximum</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">np.ndarray</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#pcc_maximum"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.pcc_maximum" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">pcc_maximum</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#pcc_maximum"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.pcc_maximum" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate lateral shift between two images using phase cross correlation.</p>
 <p>Same as <code class="docutils literal notranslate"><span class="pre">skimage.registration.phase_cross_correlation</span></code> but some additional parameters
 are supported.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1473,10 +2250,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Shift in pixel.</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p>np.ndarray</p>
 </dd>
 </dl>
@@ -1484,12 +2261,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.correlation.pcc_maximum_with_corr">
-<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">pcc_maximum_with_corr</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">np.ndarray</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#pcc_maximum_with_corr"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.pcc_maximum_with_corr" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">pcc_maximum_with_corr</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#pcc_maximum_with_corr"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.pcc_maximum_with_corr" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate lateral shift between two images using phase cross correlation.</p>
 <p>Same as <code class="docutils literal notranslate"><span class="pre">skimage.registration.phase_cross_correlation</span></code> but some additional parameters
 are supported.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1504,10 +2281,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Shift in pixel and phase cross correlation</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p>np.ndarray and float</p>
 </dd>
 </dl>
@@ -1515,10 +2292,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.correlation.pearson_coloc">
-<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">pearson_coloc</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></span><a class="headerlink" href="#impy.correlation.pearson_coloc" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">pearson_coloc</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></span><a class="headerlink" href="#impy.correlation.pearson_coloc" title="Permalink to this definition">¶</a></dt>
 <dd><p>Zero-mean Normalized Cross Correlation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1539,10 +2316,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Correlation value(s).</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray">PropArray</a> or float</p>
 </dd>
 </dl>
@@ -1550,10 +2327,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.correlation.polar_pcc_maximum">
-<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">polar_pcc_maximum</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#polar_pcc_maximum"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.polar_pcc_maximum" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">polar_pcc_maximum</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#polar_pcc_maximum"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.polar_pcc_maximum" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate rotational shift between two images using polar Fourier transformation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1567,10 +2344,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Rotation in degree</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p>float</p>
 </dd>
 </dl>
@@ -1578,10 +2355,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.correlation.polar_pcc_maximum_with_corr">
-<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">polar_pcc_maximum_with_corr</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">impy.arrays.imgarray.ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#polar_pcc_maximum_with_corr"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.polar_pcc_maximum_with_corr" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">polar_pcc_maximum_with_corr</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_degree</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#polar_pcc_maximum_with_corr"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.polar_pcc_maximum_with_corr" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate rotational shift between two images using polar Fourier transformation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1595,10 +2372,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Rotation in degree and phase cross correlation</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p>float and float</p>
 </dd>
 </dl>
@@ -1606,10 +2383,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.correlation.zncc">
-<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">zncc</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dims</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#zncc"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.zncc" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">zncc</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray"><span class="pre">PropArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">float</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#zncc"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.zncc" title="Permalink to this definition">¶</a></dt>
 <dd><p>Zero-mean Normalized Cross Correlation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1630,10 +2407,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Correlation value(s).</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.specials.PropArray" title="impy.arrays.specials.PropArray">PropArray</a> or float</p>
 </dd>
 </dl>
@@ -1644,7 +2421,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">zncc_landscape</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/correlation.html#zncc_landscape"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.zncc_landscape" title="Permalink to this definition">¶</a></dt>
 <dd><p>Create landscape of zero-mean normalized cross correlation.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>img0</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – First image.</p></li>
 <li><p><strong>img1</strong> (<a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><em>ImgArray</em></a>) – Second image.</p></li>
@@ -1657,10 +2434,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Landscape image.</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1668,7 +2445,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.correlation.zncc_maximum">
-<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">zncc_maximum</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">np.ndarray</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#zncc_maximum"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.zncc_maximum" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">zncc_maximum</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#zncc_maximum"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.zncc_maximum" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate lateral shift between two images using zero-mean normalized cross correlation.</p>
 <p>Similar to <a class="reference internal" href="#impy.correlation.pcc_maximum" title="impy.correlation.pcc_maximum"><code class="xref py py-func docutils literal notranslate"><span class="pre">pcc_maximum()</span></code></a>, this function can determine shift at sub-pixel precision.
 Since ZNCC uses real space, this function performs better than PCC when the input images
@@ -1687,10 +2464,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Shift in pixel .</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p>np.ndarray</p>
 </dd>
 </dl>
@@ -1698,7 +2475,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.correlation.zncc_maximum_with_corr">
-<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">zncc_maximum_with_corr</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">np.ndarray</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#zncc_maximum_with_corr"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.zncc_maximum_with_corr" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.correlation.</span></span><span class="sig-name descname"><span class="pre">zncc_maximum_with_corr</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">img0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">img1</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">upsample_factor</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_shifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">numpy.ndarray</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/correlation.html#zncc_maximum_with_corr"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.correlation.zncc_maximum_with_corr" title="Permalink to this definition">¶</a></dt>
 <dd><p>Calculate lateral shift between two images using zero-mean normalized cross correlation.</p>
 <p>Similar to <a class="reference internal" href="#impy.correlation.pcc_maximum" title="impy.correlation.pcc_maximum"><code class="xref py py-func docutils literal notranslate"><span class="pre">pcc_maximum()</span></code></a>, this function can determine shift at sub-pixel precision.
 Since ZNCC uses real space, this function performs better than PCC when the input images
@@ -1716,10 +2493,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </dd>
 </dl>
 <dl class="field-list simple">
-<dt class="field-odd">Returns</dt>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
 <dd class="field-odd"><p>Shift in pixel and ZNCC value.</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p>np.ndarray and float</p>
 </dd>
 </dl>
@@ -1727,23 +2504,23 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.io">
-<span id="impy-io-module"></span><h2>impy.io module<a class="headerlink" href="#module-impy.io" title="Permalink to this headline">¶</a></h2>
+<span id="impy-io-module"></span><h2>impy.io module<a class="headerlink" href="#module-impy.io" title="Permalink to this heading">¶</a></h2>
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.io.imread">
-<span class="sig-prename descclassname"><span class="pre">impy.io.</span></span><span class="sig-name descname"><span class="pre">imread</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">memmap</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">impy.io.ImageData</span></span></span><a class="headerlink" href="#impy.io.imread" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.io.</span></span><span class="sig-name descname"><span class="pre">imread</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">memmap</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ImageData</span></span></span><a class="headerlink" href="#impy.io.imread" title="Permalink to this definition">¶</a></dt>
 <dd><p>Read an image file.</p>
 <p>The reader is chosen according to the file extension.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>path</strong> (<em>str</em>) – File path of an image.</p></li>
 <li><p><strong>memmap</strong> (<em>bool</em><em>, </em><em>default is False</em>) – Read image as a memory-mapped-like state.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Image data tuple.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>ImageData</p>
 </dd>
 </dl>
@@ -1751,21 +2528,21 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.io.imread_dask">
-<span class="sig-prename descclassname"><span class="pre">impy.io.</span></span><span class="sig-name descname"><span class="pre">imread_dask</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Any</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">impy.io.ImageData</span></span></span><a class="headerlink" href="#impy.io.imread_dask" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.io.</span></span><span class="sig-name descname"><span class="pre">imread_dask</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Any</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ImageData</span></span></span><a class="headerlink" href="#impy.io.imread_dask" title="Permalink to this definition">¶</a></dt>
 <dd><p>Read an image file as a dask array.</p>
 <p>The reader is chosen according to the file extension.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>path</strong> (<em>str</em>) – File path of an image.</p></li>
 <li><p><strong>chunks</strong> (<em>Any</em>) – Parameter that will be passed to <code class="docutils literal notranslate"><span class="pre">dask.array.from_array</span></code> or
 <code class="docutils literal notranslate"><span class="pre">dask.array.from_zarr</span></code> function.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Image data tuple.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>ImageData</p>
 </dd>
 </dl>
@@ -1802,24 +2579,24 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.random">
-<span id="impy-random-module"></span><h2>impy.random module<a class="headerlink" href="#module-impy.random" title="Permalink to this headline">¶</a></h2>
+<span id="impy-random-module"></span><h2>impy.random module<a class="headerlink" href="#module-impy.random" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.random.ImageGenerator">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.random.</span></span><span class="sig-name descname"><span class="pre">ImageGenerator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">rng</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">numpy.random._generator.Generator</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/random.html#ImageGenerator"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.random.ImageGenerator" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.random.</span></span><span class="sig-name descname"><span class="pre">ImageGenerator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">rng</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Generator</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/random.html#ImageGenerator"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.random.ImageGenerator" title="Permalink to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.random.ImageGenerator.normal">
-<span class="sig-name descname"><span class="pre">normal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">loc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">np.ndarray</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">np.ndarray</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/random.html#ImageGenerator.normal"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.random.ImageGenerator.normal" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">normal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">loc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">ndarray</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">ndarray</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/random.html#ImageGenerator.normal"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.random.ImageGenerator.normal" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.random.ImageGenerator.poisson">
-<span class="sig-name descname"><span class="pre">poisson</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">lam</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/random.html#ImageGenerator.poisson"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.random.ImageGenerator.poisson" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">poisson</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">lam</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/random.html#ImageGenerator.poisson"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.random.ImageGenerator.poisson" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.random.ImageGenerator.random">
-<span class="sig-name descname"><span class="pre">random</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/random.html#ImageGenerator.random"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.random.ImageGenerator.random" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">random</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/random.html#ImageGenerator.random"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.random.ImageGenerator.random" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
@@ -1834,19 +2611,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.random.ImageGenerator.standard_exponential">
-<span class="sig-name descname"><span class="pre">standard_exponential</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'zig'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'inv'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/random.html#ImageGenerator.standard_exponential"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.random.ImageGenerator.standard_exponential" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">standard_exponential</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'zig'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'inv'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/random.html#ImageGenerator.standard_exponential"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.random.ImageGenerator.standard_exponential" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.random.ImageGenerator.standard_normal">
-<span class="sig-name descname"><span class="pre">standard_normal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/random.html#ImageGenerator.standard_normal"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.random.ImageGenerator.standard_normal" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">standard_normal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/random.html#ImageGenerator.standard_normal"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.random.ImageGenerator.standard_normal" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.random.default_rng">
-<span class="sig-prename descclassname"><span class="pre">impy.random.</span></span><span class="sig-name descname"><span class="pre">default_rng</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">seed</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.random.ImageGenerator" title="impy.random.ImageGenerator"><span class="pre">impy.random.ImageGenerator</span></a></span></span><a class="reference internal" href="../_modules/impy/random.html#default_rng"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.random.default_rng" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.random.</span></span><span class="sig-name descname"><span class="pre">default_rng</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">seed</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.random.ImageGenerator" title="impy.random.ImageGenerator"><span class="pre">ImageGenerator</span></a></span></span><a class="reference internal" href="../_modules/impy/random.html#default_rng"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.random.default_rng" title="Permalink to this definition">¶</a></dt>
 <dd><p>Get the default random number generator.</p>
 </dd></dl>
 
@@ -1856,33 +2633,34 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dd><p>Draw random samples from a normal (Gaussian) distribution.</p>
 <p>The probability density function of the normal distribution, first
 derived by De Moivre and 200 years later by both Gauss and Laplace
-independently <a class="footnote-reference brackets" href="#id11" id="id7">2</a>, is often called the bell curve because of
+independently <a class="footnote-reference brackets" href="#id11" id="id7" role="doc-noteref"><span class="fn-bracket">[</span>2<span class="fn-bracket">]</span></a>, is often called the bell curve because of
 its characteristic shape (see the example below).</p>
 <p>The normal distributions occurs often in nature.  For example, it
 describes the commonly occurring distribution of samples influenced
 by a large number of tiny, random disturbances, each with its own
-unique distribution <a class="footnote-reference brackets" href="#id11" id="id8">2</a>.</p>
+unique distribution <a class="footnote-reference brackets" href="#id11" id="id8" role="doc-noteref"><span class="fn-bracket">[</span>2<span class="fn-bracket">]</span></a>.</p>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
-<p>New code should use the <code class="docutils literal notranslate"><span class="pre">normal</span></code> method of a <code class="docutils literal notranslate"><span class="pre">default_rng()</span></code>
-instance instead; please see the <span class="xref std std-ref">random-quick-start</span>.</p>
+<p>New code should use the <cite>~numpy.random.Generator.normal</cite>
+method of a <cite>~numpy.random.Generator</cite> instance instead;
+please see the <span class="xref std std-ref">random-quick-start</span>.</p>
 </div>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>loc</strong> (<em>float</em><em> or </em><em>array_like of floats</em>) – Mean (“centre”) of the distribution.</p></li>
-<li><p><strong>scale</strong> (<em>float</em><em> or </em><em>array_like of floats</em>) – Standard deviation (spread or “width”) of the distribution. Must be
+<li><p><strong>loc</strong> (<em>float</em><em> or </em><em>array_like</em><em> of </em><em>floats</em>) – Mean (“centre”) of the distribution.</p></li>
+<li><p><strong>scale</strong> (<em>float</em><em> or </em><em>array_like</em><em> of </em><em>floats</em>) – Standard deviation (spread or “width”) of the distribution. Must be
 non-negative.</p></li>
-<li><p><strong>size</strong> (<em>int</em><em> or </em><em>tuple of ints</em><em>, </em><em>optional</em>) – Output shape.  If the given shape is, e.g., <code class="docutils literal notranslate"><span class="pre">(m,</span> <span class="pre">n,</span> <span class="pre">k)</span></code>, then
+<li><p><strong>size</strong> (<em>int</em><em> or </em><em>tuple</em><em> of </em><em>ints</em><em>, </em><em>optional</em>) – Output shape.  If the given shape is, e.g., <code class="docutils literal notranslate"><span class="pre">(m,</span> <span class="pre">n,</span> <span class="pre">k)</span></code>, then
 <code class="docutils literal notranslate"><span class="pre">m</span> <span class="pre">*</span> <span class="pre">n</span> <span class="pre">*</span> <span class="pre">k</span></code> samples are drawn.  If size is <code class="docutils literal notranslate"><span class="pre">None</span></code> (default),
 a single value is returned if <code class="docutils literal notranslate"><span class="pre">loc</span></code> and <code class="docutils literal notranslate"><span class="pre">scale</span></code> are both scalars.
 Otherwise, <code class="docutils literal notranslate"><span class="pre">np.broadcast(loc,</span> <span class="pre">scale).size</span></code> samples are drawn.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p><strong>out</strong> – Drawn samples from the parameterized normal distribution.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>ndarray or scalar</p>
 </dd>
 </dl>
@@ -1905,21 +2683,24 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 is called the variance.</p>
 <p>The function has its peak at the mean, and its “spread” increases with
 the standard deviation (the function reaches 0.607 times its maximum at
-<span class="math notranslate nohighlight">\(x + \sigma\)</span> and <span class="math notranslate nohighlight">\(x - \sigma\)</span> <a class="footnote-reference brackets" href="#id11" id="id9">2</a>).  This implies that
+<span class="math notranslate nohighlight">\(x + \sigma\)</span> and <span class="math notranslate nohighlight">\(x - \sigma\)</span> <a class="footnote-reference brackets" href="#id11" id="id9" role="doc-noteref"><span class="fn-bracket">[</span>2<span class="fn-bracket">]</span></a>).  This implies that
 normal is more likely to return samples lying close to the mean, rather
 than those far away.</p>
 <p class="rubric">References</p>
-<dl class="footnote brackets">
-<dt class="label" id="id10"><span class="brackets">1</span></dt>
-<dd><p>Wikipedia, “Normal distribution”,
+<aside class="footnote-list brackets">
+<aside class="footnote brackets" id="id10" role="note">
+<span class="label"><span class="fn-bracket">[</span>1<span class="fn-bracket">]</span></span>
+<p>Wikipedia, “Normal distribution”,
 <a class="reference external" href="https://en.wikipedia.org/wiki/Normal_distribution">https://en.wikipedia.org/wiki/Normal_distribution</a></p>
-</dd>
-<dt class="label" id="id11"><span class="brackets">2</span><span class="fn-backref">(<a href="#id7">1</a>,<a href="#id8">2</a>,<a href="#id9">3</a>)</span></dt>
-<dd><p>P. R. Peebles Jr., “Central Limit Theorem” in “Probability,
+</aside>
+<aside class="footnote brackets" id="id11" role="note">
+<span class="label"><span class="fn-bracket">[</span>2<span class="fn-bracket">]</span></span>
+<span class="backrefs">(<a role="doc-backlink" href="#id7">1</a>,<a role="doc-backlink" href="#id8">2</a>,<a role="doc-backlink" href="#id9">3</a>)</span>
+<p>P. R. Peebles Jr., “Central Limit Theorem” in “Probability,
 Random Variables and Random Signal Principles”, 4th ed., 2001,
 pp. 51, 51, 125.</p>
-</dd>
-</dl>
+</aside>
+</aside>
 <p class="rubric">Examples</p>
 <p>Draw samples from the distribution:</p>
 <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">mu</span><span class="p">,</span> <span class="n">sigma</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="mf">0.1</span> <span class="c1"># mean and standard deviation</span>
@@ -1945,7 +2726,8 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="gp">&gt;&gt;&gt; </span><span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
 </pre></div>
 </div>
-<p>Two-by-four array of samples from N(3, 6.25):</p>
+<p>Two-by-four array of samples from the normal distribution with
+mean 3 and standard deviation 2.5:</p>
 <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">normal</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mf">2.5</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
 <span class="go">array([[-4.49401501,  4.00950034, -1.81814867,  7.29718677],   # random</span>
 <span class="go">       [ 0.39924804,  4.68456316,  4.99394529,  4.84057254]])  # random</span>
@@ -1965,17 +2747,17 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-prename descclassname"><span class="pre">impy.random.</span></span><span class="sig-name descname"><span class="pre">random_uint16</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/random.html#random_uint16"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.random.random_uint16" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return a random uint16 image, ranging 0-65535.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>size</strong> (<em>int</em><em> or </em><em>tuple of int</em>) – Image shape.</p></li>
+<li><p><strong>size</strong> (<em>int</em><em> or </em><em>tuple</em><em> of </em><em>int</em>) – Image shape.</p></li>
 <li><p><strong>name</strong> (<em>str</em><em>, </em><em>optional</em>) – Image name.</p></li>
 <li><p><strong>axes</strong> (<em>str</em><em>, </em><em>optional</em>) – Image axes.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Random Image in dtype <code class="docutils literal notranslate"><span class="pre">np.uint16</span></code>.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -1986,17 +2768,17 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-prename descclassname"><span class="pre">impy.random.</span></span><span class="sig-name descname"><span class="pre">random_uint8</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray"><span class="pre">ImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/random.html#random_uint8"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.random.random_uint8" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return a random uint8 image, ranging 0-255.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>size</strong> (<em>int</em><em> or </em><em>tuple of int</em>) – Image shape.</p></li>
+<li><p><strong>size</strong> (<em>int</em><em> or </em><em>tuple</em><em> of </em><em>int</em>) – Image shape.</p></li>
 <li><p><strong>name</strong> (<em>str</em><em>, </em><em>optional</em>) – Image name.</p></li>
 <li><p><strong>axes</strong> (<em>str</em><em>, </em><em>optional</em>) – Image axes.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>Random Image in dtype <code class="docutils literal notranslate"><span class="pre">np.uint8</span></code>.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
 </dd>
 </dl>
@@ -2004,32 +2786,32 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.roi">
-<span id="impy-roi-module"></span><h2>impy.roi module<a class="headerlink" href="#module-impy.roi" title="Permalink to this headline">¶</a></h2>
+<span id="impy-roi-module"></span><h2>impy.roi module<a class="headerlink" href="#module-impy.roi" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.roi.LineRoi">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.roi.</span></span><span class="sig-name descname"><span class="pre">LineRoi</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/roi.html#LineRoi"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.LineRoi" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="#impy.roi.PolyLineRoi" title="impy.roi.PolyLineRoi"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.roi.PolyLineRoi</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="#impy.roi.PolyLineRoi" title="impy.roi.PolyLineRoi"><code class="xref py py-class docutils literal notranslate"><span class="pre">PolyLineRoi</span></code></a></p>
 </dd></dl>
 
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.roi.PointRoi">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.roi.</span></span><span class="sig-name descname"><span class="pre">PointRoi</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/roi.html#PointRoi"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.PointRoi" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="#impy.roi.Roi" title="impy.roi.Roi"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.roi.Roi</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="#impy.roi.Roi" title="impy.roi.Roi"><code class="xref py py-class docutils literal notranslate"><span class="pre">Roi</span></code></a></p>
 </dd></dl>
 
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.roi.PolyLineRoi">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.roi.</span></span><span class="sig-name descname"><span class="pre">PolyLineRoi</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/roi.html#PolyLineRoi"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.PolyLineRoi" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="#impy.roi.Roi" title="impy.roi.Roi"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.roi.Roi</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="#impy.roi.Roi" title="impy.roi.Roi"><code class="xref py py-class docutils literal notranslate"><span class="pre">Roi</span></code></a></p>
 </dd></dl>
 
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.roi.PolygonRoi">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.roi.</span></span><span class="sig-name descname"><span class="pre">PolygonRoi</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/roi.html#PolygonRoi"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.PolygonRoi" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="#impy.roi.Roi" title="impy.roi.Roi"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.roi.Roi</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="#impy.roi.Roi" title="impy.roi.Roi"><code class="xref py py-class docutils literal notranslate"><span class="pre">Roi</span></code></a></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.roi.PolygonRoi.get_coordinates">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_coordinates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coords</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">numpy.ndarray</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/roi.html#PolygonRoi.get_coordinates"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.PolygonRoi.get_coordinates" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_coordinates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coords</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/roi.html#PolygonRoi.get_coordinates"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.PolygonRoi.get_coordinates" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convert coordinates.</p>
 </dd></dl>
 
@@ -2038,7 +2820,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.roi.RectangleRoi">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.roi.</span></span><span class="sig-name descname"><span class="pre">RectangleRoi</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">AxesLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_dims</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/roi.html#RectangleRoi"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.RectangleRoi" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="#impy.roi.PolygonRoi" title="impy.roi.PolygonRoi"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.roi.PolygonRoi</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="#impy.roi.PolygonRoi" title="impy.roi.PolygonRoi"><code class="xref py py-class docutils literal notranslate"><span class="pre">PolygonRoi</span></code></a></p>
 </dd></dl>
 
 <dl class="py class">
@@ -2051,7 +2833,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 extra-dimensions (stored in <code class="docutils literal notranslate"><span class="pre">_multi_dims</span></code>).</p>
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.roi.Roi.axes">
-<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">axes</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">impy.axes._axes.Axes</span></em><a class="headerlink" href="#impy.roi.Roi.axes" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">axes</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">Axes</span></em><a class="headerlink" href="#impy.roi.Roi.axes" title="Permalink to this definition">¶</a></dt>
 <dd><p>Roi axes.</p>
 </dd></dl>
 
@@ -2063,7 +2845,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.roi.Roi.drop">
-<span class="sig-name descname"><span class="pre">drop</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">AxisLike</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/roi.html#Roi.drop"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.Roi.drop" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">drop</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/roi.html#Roi.drop"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.Roi.drop" title="Permalink to this definition">¶</a></dt>
 <dd><p>Drop an axis from the ROI.</p>
 </dd></dl>
 
@@ -2075,7 +2857,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.roi.Roi.get_coordinates">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_coordinates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coords</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">numpy.ndarray</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/roi.html#Roi.get_coordinates"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.Roi.get_coordinates" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">get_coordinates</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">coords</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/roi.html#Roi.get_coordinates"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.Roi.get_coordinates" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convert coordinates.</p>
 </dd></dl>
 
@@ -2098,18 +2880,18 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.roi.RoiList">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.roi.</span></span><span class="sig-name descname"><span class="pre">RoiList</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rois</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#impy.roi.Roi" title="impy.roi.Roi"><span class="pre">impy.roi.Roi</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">()</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/roi.html#RoiList"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.RoiList" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">MutableSequence</span></code>[<a class="reference internal" href="#impy.roi.Roi" title="impy.roi.Roi"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.roi.Roi</span></code></a>]</p>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.roi.</span></span><span class="sig-name descname"><span class="pre">RoiList</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rois</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="#impy.roi.Roi" title="impy.roi.Roi"><span class="pre">Roi</span></a><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">()</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/roi.html#RoiList"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.RoiList" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">MutableSequence</span></code>[<a class="reference internal" href="#impy.roi.Roi" title="impy.roi.Roi"><code class="xref py py-class docutils literal notranslate"><span class="pre">Roi</span></code></a>]</p>
 <p>A list of ROIs.</p>
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.roi.RoiList.axes">
-<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">axes</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">impy.axes._axes.Axes</span></em><a class="headerlink" href="#impy.roi.RoiList.axes" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">axes</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">Axes</span></em><a class="headerlink" href="#impy.roi.RoiList.axes" title="Permalink to this definition">¶</a></dt>
 <dd><p>RoiList axes.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.roi.RoiList.drop">
-<span class="sig-name descname"><span class="pre">drop</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">AxisLike</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/roi.html#RoiList.drop"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.RoiList.drop" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">drop</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axis</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/roi.html#RoiList.drop"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.RoiList.drop" title="Permalink to this definition">¶</a></dt>
 <dd><p>Drop an axis from all the ROIs.</p>
 </dd></dl>
 
@@ -2118,13 +2900,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">fromfile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Self</span></span></span><a class="reference internal" href="../_modules/impy/roi.html#RoiList.fromfile"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.RoiList.fromfile" title="Permalink to this definition">¶</a></dt>
 <dd><p>Construct a RoiList from a file.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>path</strong> (<em>str</em>) – Path to the ROI file.</p>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>A RoiList object with the ROIs read from the file.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="#impy.roi.RoiList" title="impy.roi.RoiList">RoiList</a></p>
 </dd>
 </dl>
@@ -2132,11 +2914,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.roi.RoiList.insert">
-<span class="sig-name descname"><span class="pre">insert</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">index</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">roi</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#impy.roi.Roi" title="impy.roi.Roi"><span class="pre">impy.roi.Roi</span></a></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/roi.html#RoiList.insert"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.RoiList.insert" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">insert</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">index</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">roi</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="#impy.roi.Roi" title="impy.roi.Roi"><span class="pre">Roi</span></a></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/roi.html#RoiList.insert"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.RoiList.insert" title="Permalink to this definition">¶</a></dt>
 <dd><p>Insert a ROI at the given index.</p>
 <p>The axes of the ROI must match the axes of the ROI list.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>index</strong> (<em>int</em>) – Index at which to insert the ROI.</p></li>
 <li><p><strong>roi</strong> (<a class="reference internal" href="#impy.roi.Roi" title="impy.roi.Roi"><em>Roi</em></a>) – ROI to insert.</p></li>
@@ -2156,7 +2938,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">tofile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="reference internal" href="../_modules/impy/roi.html#RoiList.tofile"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.roi.RoiList.tofile" title="Permalink to this definition">¶</a></dt>
 <dd><p>Save the RoiList to a file.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>path</strong> (<em>str</em>) – Path to the file.</p>
 </dd>
 </dl>
@@ -2166,7 +2948,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy">
-<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-impy" title="Permalink to this headline">¶</a></h2>
+<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-impy" title="Permalink to this heading">¶</a></h2>
 </section>
 </section>
 
diff --git a/docs/apidoc/impy.lazy.html b/docs/apidoc/impy.lazy.html
new file mode 100644
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--- /dev/null
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+             
+  <section id="impy-lazy-package">
+<h1>impy.lazy package<a class="headerlink" href="#impy-lazy-package" title="Permalink to this heading">¶</a></h1>
+<section id="submodules">
+<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this heading">¶</a></h2>
+</section>
+<section id="module-impy.lazy.core">
+<span id="impy-lazy-core-module"></span><h2>impy.lazy.core module<a class="headerlink" href="#module-impy.lazy.core" title="Permalink to this heading">¶</a></h2>
+<dl class="py function">
+<dt class="sig sig-object py" id="impy.lazy.core.arange">
+<span class="sig-prename descclassname"><span class="pre">impy.lazy.core.</span></span><span class="sig-name descname"><span class="pre">arange</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">stop</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/core.html#arange"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.core.arange" title="Permalink to this definition">¶</a></dt>
+<dd><blockquote>
+<div><p>impy.lazy version of numpy.arange. This function has additional parameters
+<code class="docutils literal notranslate"><span class="pre">axes</span></code> and <code class="docutils literal notranslate"><span class="pre">name</span></code>. Original docstring follows.</p>
+<dl class="simple">
+<dt>axes<span class="classifier">str, optional</span></dt><dd><p>Image axes. Must be same length as image dimension.</p>
+</dd>
+<dt>name: str, optional</dt><dd><p>Image name.</p>
+</dd>
+<dt>like: MetaArray, optional</dt><dd><p>Reference array from which name and axes will be copied.</p>
+</dd>
+</dl>
+</div></blockquote>
+<p>Return evenly spaced values from <cite>start</cite> to <cite>stop</cite> with step size <cite>step</cite>.</p>
+<p>The values are half-open [start, stop), so including start and excluding
+stop. This is basically the same as python’s range function but for dask
+arrays.</p>
+<p>When using a non-integer step, such as 0.1, the results will often not be
+consistent. It is better to use linspace for these cases.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>start</strong> (<em>int</em><em>, </em><em>optional</em>) – The starting value of the sequence. The default is 0.</p></li>
+<li><p><strong>stop</strong> (<em>int</em>) – The end of the interval, this value is excluded from the interval.</p></li>
+<li><p><strong>step</strong> (<em>int</em><em>, </em><em>optional</em>) – The spacing between the values. The default is 1 when not specified.
+The last value of the sequence.</p></li>
+<li><p><strong>chunks</strong> (<em>int</em>) – The number of samples on each block. Note that the last block will have
+fewer samples if <code class="docutils literal notranslate"><span class="pre">len(array)</span> <span class="pre">%</span> <span class="pre">chunks</span> <span class="pre">!=</span> <span class="pre">0</span></code>.
+Defaults to “auto” which will automatically determine chunk sizes.</p></li>
+<li><p><strong>dtype</strong> (<em>numpy.dtype</em>) – Output dtype. Omit to infer it from start, stop, step
+Defaults to <code class="docutils literal notranslate"><span class="pre">None</span></code>.</p></li>
+<li><p><strong>like</strong> (array type or <code class="docutils literal notranslate"><span class="pre">None</span></code>) – Array to extract meta from. Defaults to <code class="docutils literal notranslate"><span class="pre">None</span></code>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p><strong>samples</strong></p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>dask array</p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<p><code class="xref py py-obj docutils literal notranslate"><span class="pre">dask.array.linspace</span></code></p>
+</div>
+</dd></dl>
+
+<dl class="py function">
+<dt class="sig sig-object py" id="impy.lazy.core.array">
+<span class="sig-prename descclassname"><span class="pre">impy.lazy.core.</span></span><span class="sig-name descname"><span class="pre">array</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">/</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">copy</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/core.html#array"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.core.array" title="Permalink to this definition">¶</a></dt>
+<dd><p>make an LazyImgArray object, like <code class="docutils literal notranslate"><span class="pre">np.array(x)</span></code></p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>arr</strong> (<em>array-like</em>) – Base array.</p></li>
+<li><p><strong>copy</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, a copy of the original array is made.</p></li>
+<li><p><strong>dtype</strong> (<em>data type</em><em>, </em><em>optional</em>) – Image data type.</p></li>
+<li><p><strong>name</strong> (<em>str</em><em>, </em><em>optional</em>) – Name of image.</p></li>
+<li><p><strong>axes</strong> (<em>str</em><em>, </em><em>optional</em>) – Image axes.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
+<dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py function">
+<dt class="sig sig-object py" id="impy.lazy.core.asarray">
+<span class="sig-prename descclassname"><span class="pre">impy.lazy.core.</span></span><span class="sig-name descname"><span class="pre">asarray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arr</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ArrayLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">DTypeLike</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/core.html#asarray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.core.asarray" title="Permalink to this definition">¶</a></dt>
+<dd><p>make an LazyImgArray object, like <code class="docutils literal notranslate"><span class="pre">np.asarray(x)</span></code></p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>arr</strong> (<em>array-like</em>) – Base array.</p></li>
+<li><p><strong>dtype</strong> (<em>data type</em><em>, </em><em>optional</em>) – Image data type.</p></li>
+<li><p><strong>name</strong> (<em>str</em><em>, </em><em>optional</em>) – Name of image.</p></li>
+<li><p><strong>axes</strong> (<em>str</em><em>, </em><em>optional</em>) – Image axes.</p></li>
+<li><p><strong>copy</strong> (<em>bool</em><em>, </em><em>default is True</em>) – If True, a copy of the original array is made.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
+<dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py function">
+<dt class="sig sig-object py" id="impy.lazy.core.empty">
+<span class="sig-prename descclassname"><span class="pre">impy.lazy.core.</span></span><span class="sig-name descname"><span class="pre">empty</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape:</span> <span class="pre">ShapeLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">DTypeLike</span> <span class="pre">=</span> <span class="pre">&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name:</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes:</span> <span class="pre">AxesLike</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like:</span> <span class="pre">MetaArray</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/core.html#empty"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.core.empty" title="Permalink to this definition">¶</a></dt>
+<dd><blockquote>
+<div><p>impy.lazy version of numpy.empty. This function has additional parameters
+<code class="docutils literal notranslate"><span class="pre">axes</span></code> and <code class="docutils literal notranslate"><span class="pre">name</span></code>. Original docstring follows.</p>
+<dl class="simple">
+<dt>axes<span class="classifier">str, optional</span></dt><dd><p>Image axes. Must be same length as image dimension.</p>
+</dd>
+<dt>name: str, optional</dt><dd><p>Image name.</p>
+</dd>
+<dt>like: MetaArray, optional</dt><dd><p>Reference array from which name and axes will be copied.</p>
+</dd>
+</dl>
+</div></blockquote>
+<p>Blocked variant of empty_like</p>
+<p>Follows the signature of empty_like exactly except that it also features
+optional keyword arguments <code class="docutils literal notranslate"><span class="pre">chunks:</span> <span class="pre">int,</span> <span class="pre">tuple,</span> <span class="pre">or</span> <span class="pre">dict</span></code> and <code class="docutils literal notranslate"><span class="pre">name:</span> <span class="pre">str</span></code>.</p>
+<p>Original signature follows below.</p>
+<p>empty_like(prototype, dtype=None, order=’K’, subok=True, shape=None)</p>
+<p>Return a new array with the same shape and type as a given array.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>prototype</strong> (<em>array_like</em>) – The shape and data-type of <cite>prototype</cite> define these same attributes
+of the returned array.</p></li>
+<li><p><strong>dtype</strong> (<em>data-type</em><em>, </em><em>optional</em>) – <p>Overrides the data type of the result.</p>
+<div class="versionadded">
+<p><span class="versionmodified added">New in version 1.6.0.</span></p>
+</div>
+</p></li>
+<li><p><strong>order</strong> (<em>{'C'</em><em>, </em><em>'F'</em><em>, </em><em>'A'</em><em>, or </em><em>'K'}</em><em>, </em><em>optional</em>) – <p>Overrides the memory layout of the result. ‘C’ means C-order,
+‘F’ means F-order, ‘A’ means ‘F’ if <cite>prototype</cite> is Fortran
+contiguous, ‘C’ otherwise. ‘K’ means match the layout of <cite>prototype</cite>
+as closely as possible.</p>
+<div class="versionadded">
+<p><span class="versionmodified added">New in version 1.6.0.</span></p>
+</div>
+</p></li>
+<li><p><strong>subok</strong> (<em>bool</em><em>, </em><em>optional.</em>) – If True, then the newly created array will use the sub-class
+type of <cite>prototype</cite>, otherwise it will be a base-class array. Defaults
+to True.</p></li>
+<li><p><strong>shape</strong> (<em>int</em><em> or </em><em>sequence</em><em> of </em><em>ints</em><em>, </em><em>optional.</em>) – <p>Overrides the shape of the result. If order=’K’ and the number of
+dimensions is unchanged, will try to keep order, otherwise,
+order=’C’ is implied.</p>
+<div class="versionadded">
+<p><span class="versionmodified added">New in version 1.17.0.</span></p>
+</div>
+</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p><strong>out</strong> – Array of uninitialized (arbitrary) data with the same
+shape and type as <cite>prototype</cite>.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>ndarray</p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<dl class="simple">
+<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">ones_like</span></code></dt><dd><p>Return an array of ones with shape and type of input.</p>
+</dd>
+<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">zeros_like</span></code></dt><dd><p>Return an array of zeros with shape and type of input.</p>
+</dd>
+<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">full_like</span></code></dt><dd><p>Return a new array with shape of input filled with value.</p>
+</dd>
+<dt><a class="reference internal" href="#impy.lazy.core.empty" title="impy.lazy.core.empty"><code class="xref py py-obj docutils literal notranslate"><span class="pre">empty</span></code></a></dt><dd><p>Return a new uninitialized array.</p>
+</dd>
+</dl>
+</div>
+<p class="rubric">Notes</p>
+<p>This function does <em>not</em> initialize the returned array; to do that use
+<cite>zeros_like</cite> or <cite>ones_like</cite> instead.  It may be marginally faster than
+the functions that do set the array values.</p>
+<p class="rubric">Examples</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">a</span> <span class="o">=</span> <span class="p">([</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">],</span> <span class="p">[</span><span class="mi">4</span><span class="p">,</span><span class="mi">5</span><span class="p">,</span><span class="mi">6</span><span class="p">])</span>                         <span class="c1"># a is array-like</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">empty_like</span><span class="p">(</span><span class="n">a</span><span class="p">)</span>
+<span class="go">array([[-1073741821, -1073741821,           3],    # uninitialized</span>
+<span class="go">       [          0,           0, -1073741821]])</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">a</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mf">1.</span><span class="p">,</span> <span class="mf">2.</span><span class="p">,</span> <span class="mf">3.</span><span class="p">],[</span><span class="mf">4.</span><span class="p">,</span><span class="mf">5.</span><span class="p">,</span><span class="mf">6.</span><span class="p">]])</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">empty_like</span><span class="p">(</span><span class="n">a</span><span class="p">)</span>
+<span class="go">array([[ -2.00000715e+000,   1.48219694e-323,  -2.00000572e+000], # uninitialized</span>
+<span class="go">       [  4.38791518e-305,  -2.00000715e+000,   4.17269252e-309]])</span>
+</pre></div>
+</div>
+</dd></dl>
+
+<dl class="py function">
+<dt class="sig sig-object py" id="impy.lazy.core.full">
+<span class="sig-prename descclassname"><span class="pre">impy.lazy.core.</span></span><span class="sig-name descname"><span class="pre">full</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape:</span> <span class="pre">ShapeLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fill_value:</span> <span class="pre">Any</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">DTypeLike</span> <span class="pre">=</span> <span class="pre">&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name:</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes:</span> <span class="pre">AxesLike</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like:</span> <span class="pre">MetaArray</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/core.html#full"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.core.full" title="Permalink to this definition">¶</a></dt>
+<dd><blockquote>
+<div><p>impy.lazy version of numpy.full. This function has additional parameters
+<code class="docutils literal notranslate"><span class="pre">axes</span></code> and <code class="docutils literal notranslate"><span class="pre">name</span></code>. Original docstring follows.</p>
+<dl class="simple">
+<dt>axes<span class="classifier">str, optional</span></dt><dd><p>Image axes. Must be same length as image dimension.</p>
+</dd>
+<dt>name: str, optional</dt><dd><p>Image name.</p>
+</dd>
+<dt>like: MetaArray, optional</dt><dd><p>Reference array from which name and axes will be copied.</p>
+</dd>
+</dl>
+</div></blockquote>
+<p>Blocked variant of full_like</p>
+<p>Follows the signature of full_like exactly except that it also features
+optional keyword arguments <code class="docutils literal notranslate"><span class="pre">chunks:</span> <span class="pre">int,</span> <span class="pre">tuple,</span> <span class="pre">or</span> <span class="pre">dict</span></code> and <code class="docutils literal notranslate"><span class="pre">name:</span> <span class="pre">str</span></code>.</p>
+<p>Original signature follows below.</p>
+<p>Return a full array with the same shape and type as a given array.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>a</strong> (<em>array_like</em>) – The shape and data-type of <cite>a</cite> define these same attributes of
+the returned array.</p></li>
+<li><p><strong>fill_value</strong> (<em>array_like</em>) – Fill value.</p></li>
+<li><p><strong>dtype</strong> (<em>data-type</em><em>, </em><em>optional</em>) – Overrides the data type of the result.</p></li>
+<li><p><strong>order</strong> (<em>{'C'</em><em>, </em><em>'F'</em><em>, </em><em>'A'</em><em>, or </em><em>'K'}</em><em>, </em><em>optional</em>) – Overrides the memory layout of the result. ‘C’ means C-order,
+‘F’ means F-order, ‘A’ means ‘F’ if <cite>a</cite> is Fortran contiguous,
+‘C’ otherwise. ‘K’ means match the layout of <cite>a</cite> as closely
+as possible.</p></li>
+<li><p><strong>subok</strong> (<em>bool</em><em>, </em><em>optional.</em>) – If True, then the newly created array will use the sub-class
+type of <cite>a</cite>, otherwise it will be a base-class array. Defaults
+to True.</p></li>
+<li><p><strong>shape</strong> (<em>int</em><em> or </em><em>sequence</em><em> of </em><em>ints</em><em>, </em><em>optional.</em>) – <p>Overrides the shape of the result. If order=’K’ and the number of
+dimensions is unchanged, will try to keep order, otherwise,
+order=’C’ is implied.</p>
+<div class="versionadded">
+<p><span class="versionmodified added">New in version 1.17.0.</span></p>
+</div>
+</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p><strong>out</strong> – Array of <cite>fill_value</cite> with the same shape and type as <cite>a</cite>.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>ndarray</p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<dl class="simple">
+<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">empty_like</span></code></dt><dd><p>Return an empty array with shape and type of input.</p>
+</dd>
+<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">ones_like</span></code></dt><dd><p>Return an array of ones with shape and type of input.</p>
+</dd>
+<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">zeros_like</span></code></dt><dd><p>Return an array of zeros with shape and type of input.</p>
+</dd>
+<dt><a class="reference internal" href="#impy.lazy.core.full" title="impy.lazy.core.full"><code class="xref py py-obj docutils literal notranslate"><span class="pre">full</span></code></a></dt><dd><p>Return a new array of given shape filled with value.</p>
+</dd>
+</dl>
+</div>
+<p class="rubric">Examples</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">6</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">int</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">full_like</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
+<span class="go">array([1, 1, 1, 1, 1, 1])</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">full_like</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="mf">0.1</span><span class="p">)</span>
+<span class="go">array([0, 0, 0, 0, 0, 0])</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">full_like</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="mf">0.1</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">double</span><span class="p">)</span>
+<span class="go">array([0.1, 0.1, 0.1, 0.1, 0.1, 0.1])</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">full_like</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">double</span><span class="p">)</span>
+<span class="go">array([nan, nan, nan, nan, nan, nan])</span>
+</pre></div>
+</div>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">6</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">double</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">full_like</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="mf">0.1</span><span class="p">)</span>
+<span class="go">array([0.1, 0.1, 0.1, 0.1, 0.1, 0.1])</span>
+</pre></div>
+</div>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">([</span><span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">int</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">full_like</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">255</span><span class="p">])</span>  
+<span class="go">array([[[  0,   0, 255],</span>
+<span class="go">        [  0,   0, 255]],</span>
+<span class="go">       [[  0,   0, 255],</span>
+<span class="go">        [  0,   0, 255]]])</span>
+</pre></div>
+</div>
+</dd></dl>
+
+<dl class="py function">
+<dt class="sig sig-object py" id="impy.lazy.core.imread">
+<span class="sig-prename descclassname"><span class="pre">impy.lazy.core.</span></span><span class="sig-name descname"><span class="pre">imread</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">squeeze</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/core.html#imread"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.core.imread" title="Permalink to this definition">¶</a></dt>
+<dd><p>Read an image lazily. Image file is first opened as an memory map, and subsequently converted
+to <cite>numpy.ndarray</cite> or <cite>cupy.ndarray</cite> chunkwise by <cite>dask.array.map_blocks</cite>.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>path</strong> (<em>str</em>) – Path to the file.</p></li>
+<li><p><strong>chunks</strong> (<em>optional</em>) – Specify chunk sizes. By default, yx-axes are assigned to the same chunk for every slice of
+image, whild chunk sizes of the rest of axes are automatically set with “auto” option.</p></li>
+<li><p><strong>name</strong> (<em>str</em><em>, </em><em>optional</em>) – Name of array.</p></li>
+<li><p><strong>squeeze</strong> (<em>bool</em><em>, </em><em>default is False</em>) – If True and there is one-sized axis, then call <cite>np.squeeze</cite>.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
+<dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py function">
+<dt class="sig sig-object py" id="impy.lazy.core.indices">
+<span class="sig-prename descclassname"><span class="pre">impy.lazy.core.</span></span><span class="sig-name descname"><span class="pre">indices</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">dimensions:</span> <span class="pre">ShapeLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">DTypeLike</span> <span class="pre">=</span> <span class="pre">&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name:</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes:</span> <span class="pre">AxesLike</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like:</span> <span class="pre">MetaArray</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">AxesTuple</span><span class="p"><span class="pre">[</span></span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/lazy/core.html#indices"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.core.indices" title="Permalink to this definition">¶</a></dt>
+<dd><p>Copy of <code class="docutils literal notranslate"><span class="pre">numpy.indices</span></code>.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>dimensions</strong> (<em>shape-like</em>) – The shape of the grid.</p></li>
+<li><p><strong>dtype</strong> (<em>dtype</em><em>, </em><em>optional</em>) – Data type of the result.</p></li>
+<li><p><strong>name</strong> (<em>str</em><em>, </em><em>optional</em>) – Name of the result arrays.</p></li>
+<li><p><strong>axes</strong> (<em>AxesLike</em><em>, </em><em>optional</em>) – Axes of the result arrays.</p></li>
+<li><p><strong>like</strong> (<a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><em>MetaArray</em></a><em>, </em><em>optional</em>) – Reference array from which name and axes will be copied.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
+<dd class="field-even"><p>tuple of <a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray">LazyImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py function">
+<dt class="sig sig-object py" id="impy.lazy.core.ones">
+<span class="sig-prename descclassname"><span class="pre">impy.lazy.core.</span></span><span class="sig-name descname"><span class="pre">ones</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape:</span> <span class="pre">ShapeLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">DTypeLike</span> <span class="pre">=</span> <span class="pre">&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name:</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes:</span> <span class="pre">AxesLike</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like:</span> <span class="pre">MetaArray</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/core.html#ones"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.core.ones" title="Permalink to this definition">¶</a></dt>
+<dd><blockquote>
+<div><p>impy.lazy version of numpy.ones. This function has additional parameters
+<code class="docutils literal notranslate"><span class="pre">axes</span></code> and <code class="docutils literal notranslate"><span class="pre">name</span></code>. Original docstring follows.</p>
+<dl class="simple">
+<dt>axes<span class="classifier">str, optional</span></dt><dd><p>Image axes. Must be same length as image dimension.</p>
+</dd>
+<dt>name: str, optional</dt><dd><p>Image name.</p>
+</dd>
+<dt>like: MetaArray, optional</dt><dd><p>Reference array from which name and axes will be copied.</p>
+</dd>
+</dl>
+</div></blockquote>
+<p>Blocked variant of ones_like</p>
+<p>Follows the signature of ones_like exactly except that it also features
+optional keyword arguments <code class="docutils literal notranslate"><span class="pre">chunks:</span> <span class="pre">int,</span> <span class="pre">tuple,</span> <span class="pre">or</span> <span class="pre">dict</span></code> and <code class="docutils literal notranslate"><span class="pre">name:</span> <span class="pre">str</span></code>.</p>
+<p>Original signature follows below.</p>
+<p>Return an array of ones with the same shape and type as a given array.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>a</strong> (<em>array_like</em>) – The shape and data-type of <cite>a</cite> define these same attributes of
+the returned array.</p></li>
+<li><p><strong>dtype</strong> (<em>data-type</em><em>, </em><em>optional</em>) – <p>Overrides the data type of the result.</p>
+<div class="versionadded">
+<p><span class="versionmodified added">New in version 1.6.0.</span></p>
+</div>
+</p></li>
+<li><p><strong>order</strong> (<em>{'C'</em><em>, </em><em>'F'</em><em>, </em><em>'A'</em><em>, or </em><em>'K'}</em><em>, </em><em>optional</em>) – <p>Overrides the memory layout of the result. ‘C’ means C-order,
+‘F’ means F-order, ‘A’ means ‘F’ if <cite>a</cite> is Fortran contiguous,
+‘C’ otherwise. ‘K’ means match the layout of <cite>a</cite> as closely
+as possible.</p>
+<div class="versionadded">
+<p><span class="versionmodified added">New in version 1.6.0.</span></p>
+</div>
+</p></li>
+<li><p><strong>subok</strong> (<em>bool</em><em>, </em><em>optional.</em>) – If True, then the newly created array will use the sub-class
+type of <cite>a</cite>, otherwise it will be a base-class array. Defaults
+to True.</p></li>
+<li><p><strong>shape</strong> (<em>int</em><em> or </em><em>sequence</em><em> of </em><em>ints</em><em>, </em><em>optional.</em>) – <p>Overrides the shape of the result. If order=’K’ and the number of
+dimensions is unchanged, will try to keep order, otherwise,
+order=’C’ is implied.</p>
+<div class="versionadded">
+<p><span class="versionmodified added">New in version 1.17.0.</span></p>
+</div>
+</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p><strong>out</strong> – Array of ones with the same shape and type as <cite>a</cite>.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>ndarray</p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<dl class="simple">
+<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">empty_like</span></code></dt><dd><p>Return an empty array with shape and type of input.</p>
+</dd>
+<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">zeros_like</span></code></dt><dd><p>Return an array of zeros with shape and type of input.</p>
+</dd>
+<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">full_like</span></code></dt><dd><p>Return a new array with shape of input filled with value.</p>
+</dd>
+<dt><a class="reference internal" href="#impy.lazy.core.ones" title="impy.lazy.core.ones"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ones</span></code></a></dt><dd><p>Return a new array setting values to one.</p>
+</dd>
+</dl>
+</div>
+<p class="rubric">Examples</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">6</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span>
+<span class="go">array([[0, 1, 2],</span>
+<span class="go">       [3, 4, 5]])</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">ones_like</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
+<span class="go">array([[1, 1, 1],</span>
+<span class="go">       [1, 1, 1]])</span>
+</pre></div>
+</div>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">float</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">y</span>
+<span class="go">array([0., 1., 2.])</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">ones_like</span><span class="p">(</span><span class="n">y</span><span class="p">)</span>
+<span class="go">array([1.,  1.,  1.])</span>
+</pre></div>
+</div>
+</dd></dl>
+
+<dl class="py function">
+<dt class="sig sig-object py" id="impy.lazy.core.zeros">
+<span class="sig-prename descclassname"><span class="pre">impy.lazy.core.</span></span><span class="sig-name descname"><span class="pre">zeros</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape:</span> <span class="pre">ShapeLike</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype:</span> <span class="pre">DTypeLike</span> <span class="pre">=</span> <span class="pre">&lt;class</span> <span class="pre">'numpy.uint16'&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name:</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes:</span> <span class="pre">AxesLike</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like:</span> <span class="pre">MetaArray</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/core.html#zeros"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.core.zeros" title="Permalink to this definition">¶</a></dt>
+<dd><blockquote>
+<div><p>impy.lazy version of numpy.zeros. This function has additional parameters
+<code class="docutils literal notranslate"><span class="pre">axes</span></code> and <code class="docutils literal notranslate"><span class="pre">name</span></code>. Original docstring follows.</p>
+<dl class="simple">
+<dt>axes<span class="classifier">str, optional</span></dt><dd><p>Image axes. Must be same length as image dimension.</p>
+</dd>
+<dt>name: str, optional</dt><dd><p>Image name.</p>
+</dd>
+<dt>like: MetaArray, optional</dt><dd><p>Reference array from which name and axes will be copied.</p>
+</dd>
+</dl>
+</div></blockquote>
+<p>Blocked variant of zeros_like</p>
+<p>Follows the signature of zeros_like exactly except that it also features
+optional keyword arguments <code class="docutils literal notranslate"><span class="pre">chunks:</span> <span class="pre">int,</span> <span class="pre">tuple,</span> <span class="pre">or</span> <span class="pre">dict</span></code> and <code class="docutils literal notranslate"><span class="pre">name:</span> <span class="pre">str</span></code>.</p>
+<p>Original signature follows below.</p>
+<p>Return an array of zeros with the same shape and type as a given array.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>a</strong> (<em>array_like</em>) – The shape and data-type of <cite>a</cite> define these same attributes of
+the returned array.</p></li>
+<li><p><strong>dtype</strong> (<em>data-type</em><em>, </em><em>optional</em>) – <p>Overrides the data type of the result.</p>
+<div class="versionadded">
+<p><span class="versionmodified added">New in version 1.6.0.</span></p>
+</div>
+</p></li>
+<li><p><strong>order</strong> (<em>{'C'</em><em>, </em><em>'F'</em><em>, </em><em>'A'</em><em>, or </em><em>'K'}</em><em>, </em><em>optional</em>) – <p>Overrides the memory layout of the result. ‘C’ means C-order,
+‘F’ means F-order, ‘A’ means ‘F’ if <cite>a</cite> is Fortran contiguous,
+‘C’ otherwise. ‘K’ means match the layout of <cite>a</cite> as closely
+as possible.</p>
+<div class="versionadded">
+<p><span class="versionmodified added">New in version 1.6.0.</span></p>
+</div>
+</p></li>
+<li><p><strong>subok</strong> (<em>bool</em><em>, </em><em>optional.</em>) – If True, then the newly created array will use the sub-class
+type of <cite>a</cite>, otherwise it will be a base-class array. Defaults
+to True.</p></li>
+<li><p><strong>shape</strong> (<em>int</em><em> or </em><em>sequence</em><em> of </em><em>ints</em><em>, </em><em>optional.</em>) – <p>Overrides the shape of the result. If order=’K’ and the number of
+dimensions is unchanged, will try to keep order, otherwise,
+order=’C’ is implied.</p>
+<div class="versionadded">
+<p><span class="versionmodified added">New in version 1.17.0.</span></p>
+</div>
+</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p><strong>out</strong> – Array of zeros with the same shape and type as <cite>a</cite>.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>ndarray</p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<dl class="simple">
+<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">empty_like</span></code></dt><dd><p>Return an empty array with shape and type of input.</p>
+</dd>
+<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">ones_like</span></code></dt><dd><p>Return an array of ones with shape and type of input.</p>
+</dd>
+<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">full_like</span></code></dt><dd><p>Return a new array with shape of input filled with value.</p>
+</dd>
+<dt><a class="reference internal" href="#impy.lazy.core.zeros" title="impy.lazy.core.zeros"><code class="xref py py-obj docutils literal notranslate"><span class="pre">zeros</span></code></a></dt><dd><p>Return a new array setting values to zero.</p>
+</dd>
+</dl>
+</div>
+<p class="rubric">Examples</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">6</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">x</span>
+<span class="go">array([[0, 1, 2],</span>
+<span class="go">       [3, 4, 5]])</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">zeros_like</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
+<span class="go">array([[0, 0, 0],</span>
+<span class="go">       [0, 0, 0]])</span>
+</pre></div>
+</div>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">float</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">y</span>
+<span class="go">array([0., 1., 2.])</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">zeros_like</span><span class="p">(</span><span class="n">y</span><span class="p">)</span>
+<span class="go">array([0.,  0.,  0.])</span>
+</pre></div>
+</div>
+</dd></dl>
+
+</section>
+<section id="module-impy.lazy.random">
+<span id="impy-lazy-random-module"></span><h2>impy.lazy.random module<a class="headerlink" href="#module-impy.lazy.random" title="Permalink to this heading">¶</a></h2>
+<dl class="py class">
+<dt class="sig sig-object py" id="impy.lazy.random.ImageGenerator">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.lazy.random.</span></span><span class="sig-name descname"><span class="pre">ImageGenerator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">rng</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Generator</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/lazy/random.html#ImageGenerator"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.random.ImageGenerator" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.lazy.random.ImageGenerator.normal">
+<span class="sig-name descname"><span class="pre">normal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">loc</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">ndarray</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">ndarray</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/random.html#ImageGenerator.normal"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.random.ImageGenerator.normal" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.lazy.random.ImageGenerator.poisson">
+<span class="sig-name descname"><span class="pre">poisson</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">lam</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/random.html#ImageGenerator.poisson"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.random.ImageGenerator.poisson" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.lazy.random.ImageGenerator.random">
+<span class="sig-name descname"><span class="pre">random</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size:</span> <span class="pre">int</span> <span class="pre">|</span> <span class="pre">tuple[int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">...]</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype=&lt;class</span> <span class="pre">'numpy.float32'&gt;</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes:</span> <span class="pre">~typing.Iterable[str</span> <span class="pre">|</span> <span class="pre">~impy.axes._axis.Axis]</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name:</span> <span class="pre">str</span> <span class="pre">|</span> <span class="pre">None</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like:</span> <span class="pre">~impy.arrays.bases.metaarray.MetaArray</span> <span class="pre">|</span> <span class="pre">~impy.arrays.lazy.LazyImgArray</span> <span class="pre">=</span> <span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks='auto'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/random.html#ImageGenerator.random"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.random.ImageGenerator.random" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.lazy.random.ImageGenerator.random_uint16">
+<span class="sig-name descname"><span class="pre">random_uint16</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/random.html#ImageGenerator.random_uint16"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.random.ImageGenerator.random_uint16" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.lazy.random.ImageGenerator.random_uint8">
+<span class="sig-name descname"><span class="pre">random_uint8</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/random.html#ImageGenerator.random_uint8"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.random.ImageGenerator.random_uint8" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.lazy.random.ImageGenerator.standard_exponential">
+<span class="sig-name descname"><span class="pre">standard_exponential</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="s"><span class="pre">'zig'</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="s"><span class="pre">'inv'</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/random.html#ImageGenerator.standard_exponential"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.random.ImageGenerator.standard_exponential" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="py method">
+<dt class="sig sig-object py" id="impy.lazy.random.ImageGenerator.standard_normal">
+<span class="sig-name descname"><span class="pre">standard_normal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Iterable</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/random.html#ImageGenerator.standard_normal"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.random.ImageGenerator.standard_normal" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+</dd></dl>
+
+<dl class="py function">
+<dt class="sig sig-object py" id="impy.lazy.random.default_rng">
+<span class="sig-prename descclassname"><span class="pre">impy.lazy.random.</span></span><span class="sig-name descname"><span class="pre">default_rng</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">seed</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="#impy.lazy.random.ImageGenerator" title="impy.lazy.random.ImageGenerator"><span class="pre">ImageGenerator</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/random.html#default_rng"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.random.default_rng" title="Permalink to this definition">¶</a></dt>
+<dd><p>Get the default random number generator.</p>
+</dd></dl>
+
+<dl class="py function">
+<dt class="sig sig-object py" id="impy.lazy.random.normal">
+<span class="sig-prename descclassname"><span class="pre">impy.lazy.random.</span></span><span class="sig-name descname"><span class="pre">normal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">loc</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">scale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/lazy/random.html#normal"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.random.normal" title="Permalink to this definition">¶</a></dt>
+<dd><p>Draw random samples from a normal (Gaussian) distribution.</p>
+<p>The probability density function of the normal distribution, first
+derived by De Moivre and 200 years later by both Gauss and Laplace
+independently <a class="footnote-reference brackets" href="#id5" id="id1" role="doc-noteref"><span class="fn-bracket">[</span>2<span class="fn-bracket">]</span></a>, is often called the bell curve because of
+its characteristic shape (see the example below).</p>
+<p>The normal distributions occurs often in nature.  For example, it
+describes the commonly occurring distribution of samples influenced
+by a large number of tiny, random disturbances, each with its own
+unique distribution <a class="footnote-reference brackets" href="#id5" id="id2" role="doc-noteref"><span class="fn-bracket">[</span>2<span class="fn-bracket">]</span></a>.</p>
+<div class="admonition note">
+<p class="admonition-title">Note</p>
+<p>New code should use the <cite>~numpy.random.Generator.normal</cite>
+method of a <cite>~numpy.random.Generator</cite> instance instead;
+please see the <span class="xref std std-ref">random-quick-start</span>.</p>
+</div>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>loc</strong> (<em>float</em><em> or </em><em>array_like</em><em> of </em><em>floats</em>) – Mean (“centre”) of the distribution.</p></li>
+<li><p><strong>scale</strong> (<em>float</em><em> or </em><em>array_like</em><em> of </em><em>floats</em>) – Standard deviation (spread or “width”) of the distribution. Must be
+non-negative.</p></li>
+<li><p><strong>size</strong> (<em>int</em><em> or </em><em>tuple</em><em> of </em><em>ints</em><em>, </em><em>optional</em>) – Output shape.  If the given shape is, e.g., <code class="docutils literal notranslate"><span class="pre">(m,</span> <span class="pre">n,</span> <span class="pre">k)</span></code>, then
+<code class="docutils literal notranslate"><span class="pre">m</span> <span class="pre">*</span> <span class="pre">n</span> <span class="pre">*</span> <span class="pre">k</span></code> samples are drawn.  If size is <code class="docutils literal notranslate"><span class="pre">None</span></code> (default),
+a single value is returned if <code class="docutils literal notranslate"><span class="pre">loc</span></code> and <code class="docutils literal notranslate"><span class="pre">scale</span></code> are both scalars.
+Otherwise, <code class="docutils literal notranslate"><span class="pre">np.broadcast(loc,</span> <span class="pre">scale).size</span></code> samples are drawn.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p><strong>out</strong> – Drawn samples from the parameterized normal distribution.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p>ndarray or scalar</p>
+</dd>
+</dl>
+<div class="admonition seealso">
+<p class="admonition-title">See also</p>
+<dl class="simple">
+<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">scipy.stats.norm</span></code></dt><dd><p>probability density function, distribution or cumulative density function, etc.</p>
+</dd>
+<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">random.Generator.normal</span></code></dt><dd><p>which should be used for new code.</p>
+</dd>
+</dl>
+</div>
+<p class="rubric">Notes</p>
+<p>The probability density for the Gaussian distribution is</p>
+<div class="math notranslate nohighlight">
+\[p(x) = \frac{1}{\sqrt{ 2 \pi \sigma^2 }}
+e^{ - \frac{ (x - \mu)^2 } {2 \sigma^2} },\]</div>
+<p>where <span class="math notranslate nohighlight">\(\mu\)</span> is the mean and <span class="math notranslate nohighlight">\(\sigma\)</span> the standard
+deviation. The square of the standard deviation, <span class="math notranslate nohighlight">\(\sigma^2\)</span>,
+is called the variance.</p>
+<p>The function has its peak at the mean, and its “spread” increases with
+the standard deviation (the function reaches 0.607 times its maximum at
+<span class="math notranslate nohighlight">\(x + \sigma\)</span> and <span class="math notranslate nohighlight">\(x - \sigma\)</span> <a class="footnote-reference brackets" href="#id5" id="id3" role="doc-noteref"><span class="fn-bracket">[</span>2<span class="fn-bracket">]</span></a>).  This implies that
+normal is more likely to return samples lying close to the mean, rather
+than those far away.</p>
+<p class="rubric">References</p>
+<aside class="footnote-list brackets">
+<aside class="footnote brackets" id="id4" role="note">
+<span class="label"><span class="fn-bracket">[</span>1<span class="fn-bracket">]</span></span>
+<p>Wikipedia, “Normal distribution”,
+<a class="reference external" href="https://en.wikipedia.org/wiki/Normal_distribution">https://en.wikipedia.org/wiki/Normal_distribution</a></p>
+</aside>
+<aside class="footnote brackets" id="id5" role="note">
+<span class="label"><span class="fn-bracket">[</span>2<span class="fn-bracket">]</span></span>
+<span class="backrefs">(<a role="doc-backlink" href="#id1">1</a>,<a role="doc-backlink" href="#id2">2</a>,<a role="doc-backlink" href="#id3">3</a>)</span>
+<p>P. R. Peebles Jr., “Central Limit Theorem” in “Probability,
+Random Variables and Random Signal Principles”, 4th ed., 2001,
+pp. 51, 51, 125.</p>
+</aside>
+</aside>
+<p class="rubric">Examples</p>
+<p>Draw samples from the distribution:</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">mu</span><span class="p">,</span> <span class="n">sigma</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="mf">0.1</span> <span class="c1"># mean and standard deviation</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">s</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">normal</span><span class="p">(</span><span class="n">mu</span><span class="p">,</span> <span class="n">sigma</span><span class="p">,</span> <span class="mi">1000</span><span class="p">)</span>
+</pre></div>
+</div>
+<p>Verify the mean and the variance:</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="nb">abs</span><span class="p">(</span><span class="n">mu</span> <span class="o">-</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">s</span><span class="p">))</span>
+<span class="go">0.0  # may vary</span>
+</pre></div>
+</div>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="nb">abs</span><span class="p">(</span><span class="n">sigma</span> <span class="o">-</span> <span class="n">np</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">s</span><span class="p">,</span> <span class="n">ddof</span><span class="o">=</span><span class="mi">1</span><span class="p">))</span>
+<span class="go">0.1  # may vary</span>
+</pre></div>
+</div>
+<p>Display the histogram of the samples, along with
+the probability density function:</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">count</span><span class="p">,</span> <span class="n">bins</span><span class="p">,</span> <span class="n">ignored</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">s</span><span class="p">,</span> <span class="mi">30</span><span class="p">,</span> <span class="n">density</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">bins</span><span class="p">,</span> <span class="mi">1</span><span class="o">/</span><span class="p">(</span><span class="n">sigma</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="p">))</span> <span class="o">*</span>
+<span class="gp">... </span>               <span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span> <span class="o">-</span> <span class="p">(</span><span class="n">bins</span> <span class="o">-</span> <span class="n">mu</span><span class="p">)</span><span class="o">**</span><span class="mi">2</span> <span class="o">/</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="n">sigma</span><span class="o">**</span><span class="mi">2</span><span class="p">)</span> <span class="p">),</span>
+<span class="gp">... </span>         <span class="n">linewidth</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;r&#39;</span><span class="p">)</span>
+<span class="gp">&gt;&gt;&gt; </span><span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
+</pre></div>
+</div>
+<p>Two-by-four array of samples from the normal distribution with
+mean 3 and standard deviation 2.5:</p>
+<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">normal</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mf">2.5</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
+<span class="go">array([[-4.49401501,  4.00950034, -1.81814867,  7.29718677],   # random</span>
+<span class="go">       [ 0.39924804,  4.68456316,  4.99394529,  4.84057254]])  # random</span>
+</pre></div>
+</div>
+</dd></dl>
+
+<dl class="py function">
+<dt class="sig sig-object py" id="impy.lazy.random.random">
+<span class="sig-prename descclassname"><span class="pre">impy.lazy.random.</span></span><span class="sig-name descname"><span class="pre">random</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/lazy/random.html#random"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.random.random" title="Permalink to this definition">¶</a></dt>
+<dd><p>Return random floats in the half-open interval [0.0, 1.0). Alias for
+<cite>random_sample</cite> to ease forward-porting to the new random API.</p>
+</dd></dl>
+
+<dl class="py function">
+<dt class="sig sig-object py" id="impy.lazy.random.random_uint16">
+<span class="sig-prename descclassname"><span class="pre">impy.lazy.random.</span></span><span class="sig-name descname"><span class="pre">random_uint16</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/random.html#random_uint16"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.random.random_uint16" title="Permalink to this definition">¶</a></dt>
+<dd><p>Return a random uint16 image, ranging 0-65535.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>size</strong> (<em>int</em><em> or </em><em>tuple</em><em> of </em><em>int</em>) – Image shape.</p></li>
+<li><p><strong>name</strong> (<em>str</em><em>, </em><em>optional</em>) – Image name.</p></li>
+<li><p><strong>axes</strong> (<em>str</em><em>, </em><em>optional</em>) – Image axes.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Random Image in dtype <code class="docutils literal notranslate"><span class="pre">np.uint16</span></code>.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+<dl class="py function">
+<dt class="sig sig-object py" id="impy.lazy.random.random_uint8">
+<span class="sig-prename descclassname"><span class="pre">impy.lazy.random.</span></span><span class="sig-name descname"><span class="pre">random_uint8</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray" title="impy.arrays.bases.metaarray.MetaArray"><span class="pre">MetaArray</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'auto'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></span><a class="reference internal" href="../_modules/impy/lazy/random.html#random_uint8"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.lazy.random.random_uint8" title="Permalink to this definition">¶</a></dt>
+<dd><p>Return a random uint8 image, ranging 0-255.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
+<dd class="field-odd"><ul class="simple">
+<li><p><strong>size</strong> (<em>int</em><em> or </em><em>tuple</em><em> of </em><em>int</em>) – Image shape.</p></li>
+<li><p><strong>name</strong> (<em>str</em><em>, </em><em>optional</em>) – Image name.</p></li>
+<li><p><strong>axes</strong> (<em>str</em><em>, </em><em>optional</em>) – Image axes.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Random Image in dtype <code class="docutils literal notranslate"><span class="pre">np.uint8</span></code>.</p>
+</dd>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a></p>
+</dd>
+</dl>
+</dd></dl>
+
+</section>
+<section id="module-impy.lazy">
+<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-impy.lazy" title="Permalink to this heading">¶</a></h2>
+</section>
+</section>
+
+
+           </div>
+          </div>
+          <footer><div class="rst-footer-buttons" role="navigation" aria-label="Footer">
+        <a href="impy.frame.html" class="btn btn-neutral float-left" title="impy.frame package" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left" aria-hidden="true"></span> Previous</a>
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index 4fac026b..48c6ba63 100644
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+++ b/docs/apidoc/impy.utils.html
@@ -1,10 +1,10 @@
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 <html class="writer-html5" lang="en" >
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-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
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   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.utils package &mdash; impy 2.2.0 documentation</title>
+  <title>impy.utils package &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
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+    <link rel="prev" title="impy.lazy package" href="impy.lazy.html" /> 
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+          
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+      <li><a href="../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../api.html">API References</a></li>
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+      <li class="breadcrumb-item active">impy.utils package</li>
       <li class="wy-breadcrumbs-aside">
             <a href="../_sources/apidoc/impy.utils.rst.txt" rel="nofollow"> View page source</a>
       </li>
@@ -75,15 +78,15 @@
            <div itemprop="articleBody">
              
   <section id="impy-utils-package">
-<h1>impy.utils package<a class="headerlink" href="#impy-utils-package" title="Permalink to this headline">¶</a></h1>
+<h1>impy.utils package<a class="headerlink" href="#impy-utils-package" title="Permalink to this heading">¶</a></h1>
 <section id="submodules">
-<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline">¶</a></h2>
+<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this heading">¶</a></h2>
 </section>
 <section id="module-impy.utils.axesop">
-<span id="impy-utils-axesop-module"></span><h2>impy.utils.axesop module<a class="headerlink" href="#module-impy.utils.axesop" title="Permalink to this headline">¶</a></h2>
+<span id="impy-utils-axesop-module"></span><h2>impy.utils.axesop module<a class="headerlink" href="#module-impy.utils.axesop" title="Permalink to this heading">¶</a></h2>
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.utils.axesop.add_axes">
-<span class="sig-prename descclassname"><span class="pre">impy.utils.axesop.</span></span><span class="sig-name descname"><span class="pre">add_axes</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">impy.axes._axes.Axes</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">numpy.ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">key_axes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'yx'</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/utils/axesop.html#add_axes"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.axesop.add_axes" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.utils.axesop.</span></span><span class="sig-name descname"><span class="pre">add_axes</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Axes</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">key_axes</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'yx'</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/utils/axesop.html#add_axes"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.axesop.add_axes" title="Permalink to this definition">¶</a></dt>
 <dd><p>Stack <cite>key</cite> to make its shape key_axes-&gt; axes.</p>
 </dd></dl>
 
@@ -99,7 +102,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.utils.axesop.slice_axes">
-<span class="sig-prename descclassname"><span class="pre">impy.utils.axesop.</span></span><span class="sig-name descname"><span class="pre">slice_axes</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">impy.axes._axes.Axes</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">key</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/utils/axesop.html#slice_axes"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.axesop.slice_axes" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.utils.axesop.</span></span><span class="sig-name descname"><span class="pre">slice_axes</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Axes</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">key</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/utils/axesop.html#slice_axes"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.axesop.slice_axes" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
@@ -109,19 +112,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.utils.deco">
-<span id="impy-utils-deco-module"></span><h2>impy.utils.deco module<a class="headerlink" href="#module-impy.utils.deco" title="Permalink to this headline">¶</a></h2>
+<span id="impy-utils-deco-module"></span><h2>impy.utils.deco module<a class="headerlink" href="#module-impy.utils.deco" title="Permalink to this heading">¶</a></h2>
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.utils.deco.check_input_and_output">
-<span class="sig-prename descclassname"><span class="pre">impy.utils.deco.</span></span><span class="sig-name descname"><span class="pre">check_input_and_output</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="pre">None</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inherit_label_info</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'False'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">only_binary</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'False'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">need_labels</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'False'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="pre">_P</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_R</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="pre">_P</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_R</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/utils/deco.html#check_input_and_output"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.deco.check_input_and_output" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.utils.deco.</span></span><span class="sig-name descname"><span class="pre">check_input_and_output</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="pre">None</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inherit_label_info</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">only_binary</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">need_labels</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="pre">_P</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_R</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="pre">_P</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_R</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/utils/deco.html#check_input_and_output"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.deco.check_input_and_output" title="Permalink to this definition">¶</a></dt>
 <dt class="sig sig-object py">
-<span class="sig-prename descclassname"><span class="pre">impy.utils.deco.</span></span><span class="sig-name descname"><span class="pre">check_input_and_output</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="pre">_P</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_R</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inherit_label_info</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'False'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">only_binary</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'False'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">need_labels</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'False'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="pre">_P</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_R</span><span class="p"><span class="pre">]</span></span></span></span></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.utils.deco.</span></span><span class="sig-name descname"><span class="pre">check_input_and_output</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="pre">_P</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_R</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inherit_label_info</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">only_binary</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">need_labels</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="pre">_P</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_R</span><span class="p"><span class="pre">]</span></span></span></span></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.utils.deco.check_input_and_output_lazy">
-<span class="sig-prename descclassname"><span class="pre">impy.utils.deco.</span></span><span class="sig-name descname"><span class="pre">check_input_and_output_lazy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="pre">_P</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_R</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">only_binary</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'False'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="pre">_P</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_R</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/utils/deco.html#check_input_and_output_lazy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.deco.check_input_and_output_lazy" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.utils.deco.</span></span><span class="sig-name descname"><span class="pre">check_input_and_output_lazy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="pre">_P</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_R</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">only_binary</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="pre">_P</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_R</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/utils/deco.html#check_input_and_output_lazy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.deco.check_input_and_output_lazy" title="Permalink to this definition">¶</a></dt>
 <dt class="sig sig-object py">
-<span class="sig-prename descclassname"><span class="pre">impy.utils.deco.</span></span><span class="sig-name descname"><span class="pre">check_input_and_output_lazy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="pre">None</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">only_binary</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'False'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="pre">_P</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_R</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="pre">_P</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_R</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></span></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.utils.deco.</span></span><span class="sig-name descname"><span class="pre">check_input_and_output_lazy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Literal</span><span class="p"><span class="pre">[</span></span><span class="pre">None</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">only_binary</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="p"><span class="pre">[</span></span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="pre">_P</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_R</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Callable</span><span class="p"><span class="pre">[</span></span><span class="pre">_P</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">_R</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span></span></dt>
 <dd></dd></dl>
 
 <dl class="py function">
@@ -144,7 +147,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dd><p>Decorator to assure output image has the same dtype as the input image.
 This decorator is compatible with both ImgArray and LazyImgArray.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>asfloat</strong> (<em>bool</em><em>, </em><em>optional</em>) – If input image should be converted to float first, by default False</p>
 </dd>
 </dl>
@@ -152,11 +155,11 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.utils.gauss">
-<span id="impy-utils-gauss-module"></span><h2>impy.utils.gauss module<a class="headerlink" href="#module-impy.utils.gauss" title="Permalink to this headline">¶</a></h2>
+<span id="impy-utils-gauss-module"></span><h2>impy.utils.gauss module<a class="headerlink" href="#module-impy.utils.gauss" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.utils.gauss.DiagonalGaussian">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.utils.gauss.</span></span><span class="sig-name descname"><span class="pre">DiagonalGaussian</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/utils/gauss.html#DiagonalGaussian"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.gauss.DiagonalGaussian" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="#impy.utils.gauss.Gaussian" title="impy.utils.gauss.Gaussian"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.utils.gauss.Gaussian</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="#impy.utils.gauss.Gaussian" title="impy.utils.gauss.Gaussian"><code class="xref py py-class docutils literal notranslate"><span class="pre">Gaussian</span></code></a></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.utils.gauss.DiagonalGaussian.asdict">
 <span class="sig-name descname"><span class="pre">asdict</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/utils/gauss.html#DiagonalGaussian.asdict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.gauss.DiagonalGaussian.asdict" title="Permalink to this definition">¶</a></dt>
@@ -164,12 +167,12 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.utils.gauss.DiagonalGaussian.fit">
-<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">np.ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Powell'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">np.ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/utils/gauss.html#DiagonalGaussian.fit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.gauss.DiagonalGaussian.fit" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">fit</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Powell'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/utils/gauss.html#DiagonalGaussian.fit"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.gauss.DiagonalGaussian.fit" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.utils.gauss.DiagonalGaussian.generate">
-<span class="sig-name descname"><span class="pre">generate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">numpy.ndarray</span></span></span><a class="reference internal" href="../_modules/impy/utils/gauss.html#DiagonalGaussian.generate"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.gauss.DiagonalGaussian.generate" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">generate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="reference internal" href="../_modules/impy/utils/gauss.html#DiagonalGaussian.generate"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.gauss.DiagonalGaussian.generate" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py property">
@@ -224,13 +227,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.utils.gauss.GaussianBackground">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.utils.gauss.</span></span><span class="sig-name descname"><span class="pre">GaussianBackground</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/utils/gauss.html#GaussianBackground"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.gauss.GaussianBackground" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="#impy.utils.gauss.DiagonalGaussian" title="impy.utils.gauss.DiagonalGaussian"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.utils.gauss.DiagonalGaussian</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="#impy.utils.gauss.DiagonalGaussian" title="impy.utils.gauss.DiagonalGaussian"><code class="xref py py-class docutils literal notranslate"><span class="pre">DiagonalGaussian</span></code></a></p>
 </dd></dl>
 
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.utils.gauss.GaussianParticle">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.utils.gauss.</span></span><span class="sig-name descname"><span class="pre">GaussianParticle</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">initial_sg</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/utils/gauss.html#GaussianParticle"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.gauss.GaussianParticle" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="#impy.utils.gauss.DiagonalGaussian" title="impy.utils.gauss.DiagonalGaussian"><code class="xref py py-class docutils literal notranslate"><span class="pre">impy.utils.gauss.DiagonalGaussian</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="#impy.utils.gauss.DiagonalGaussian" title="impy.utils.gauss.DiagonalGaussian"><code class="xref py py-class docutils literal notranslate"><span class="pre">DiagonalGaussian</span></code></a></p>
 </dd></dl>
 
 <dl class="py function">
@@ -252,26 +255,26 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.utils.misc">
-<span id="impy-utils-misc-module"></span><h2>impy.utils.misc module<a class="headerlink" href="#module-impy.utils.misc" title="Permalink to this headline">¶</a></h2>
+<span id="impy-utils-misc-module"></span><h2>impy.utils.misc module<a class="headerlink" href="#module-impy.utils.misc" title="Permalink to this heading">¶</a></h2>
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.utils.misc.check_nd">
-<span class="sig-prename descclassname"><span class="pre">impy.utils.misc.</span></span><span class="sig-name descname"><span class="pre">check_nd</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">impy.utils.misc.T</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ndim</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">impy.utils.misc.T</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/utils/misc.html#check_nd"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.misc.check_nd" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.utils.misc.</span></span><span class="sig-name descname"><span class="pre">check_nd</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">T</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ndim</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Sequence</span><span class="p"><span class="pre">[</span></span><span class="pre">T</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/utils/misc.html#check_nd"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.misc.check_nd" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.utils.misc.largest_zeros">
-<span class="sig-prename descclassname"><span class="pre">impy.utils.misc.</span></span><span class="sig-name descname"><span class="pre">largest_zeros</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">numpy.ndarray</span></span></span><a class="reference internal" href="../_modules/impy/utils/misc.html#largest_zeros"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.misc.largest_zeros" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.utils.misc.</span></span><span class="sig-name descname"><span class="pre">largest_zeros</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">shape</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="reference internal" href="../_modules/impy/utils/misc.html#largest_zeros"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.misc.largest_zeros" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 </section>
 <section id="module-impy.utils.slicer">
-<span id="impy-utils-slicer-module"></span><h2>impy.utils.slicer module<a class="headerlink" href="#module-impy.utils.slicer" title="Permalink to this headline">¶</a></h2>
+<span id="impy-utils-slicer-module"></span><h2>impy.utils.slicer module<a class="headerlink" href="#module-impy.utils.slicer" title="Permalink to this heading">¶</a></h2>
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.utils.slicer.axis_targeted_slicing">
-<span class="sig-prename descclassname"><span class="pre">impy.utils.slicer.</span></span><span class="sig-name descname"><span class="pre">axis_targeted_slicing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">string</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">slice</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/utils/slicer.html#axis_targeted_slicing"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.slicer.axis_targeted_slicing" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.utils.slicer.</span></span><span class="sig-name descname"><span class="pre">axis_targeted_slicing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">string</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">slice</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/utils/slicer.html#axis_targeted_slicing"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.slicer.axis_targeted_slicing" title="Permalink to this definition">¶</a></dt>
 <dd><p>Make a conventional slices from an axis-targeted slicing string.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>ndim</strong> (<em>int</em>) – Number of dimension of the array which will be sliced.</p></li>
 <li><p><strong>axes</strong> (<em>str</em>) – Axes of input ndarray.</p></li>
@@ -279,7 +282,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 contained, this function will raise ValueError.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p>slices</p>
 </dd>
 </dl>
@@ -287,7 +290,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.utils.slicer.solve_slicer">
-<span class="sig-prename descclassname"><span class="pre">impy.utils.slicer.</span></span><span class="sig-name descname"><span class="pre">solve_slicer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Any</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">impy.axes._axes.Axes</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">slice</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/utils/slicer.html#solve_slicer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.slicer.solve_slicer" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.utils.slicer.</span></span><span class="sig-name descname"><span class="pre">solve_slicer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">key</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Any</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Axes</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">slice</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">int</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="p"><span class="pre">...</span></span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/utils/slicer.html#solve_slicer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.slicer.solve_slicer" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
@@ -297,7 +300,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.utils.utilcls">
-<span id="impy-utils-utilcls-module"></span><h2>impy.utils.utilcls module<a class="headerlink" href="#module-impy.utils.utilcls" title="Permalink to this headline">¶</a></h2>
+<span id="impy-utils-utilcls-module"></span><h2>impy.utils.utilcls module<a class="headerlink" href="#module-impy.utils.utilcls" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.utils.utilcls.ImportOnRequest">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.utils.utilcls.</span></span><span class="sig-name descname"><span class="pre">ImportOnRequest</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/utils/utilcls.html#ImportOnRequest"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.utils.utilcls.ImportOnRequest" title="Permalink to this definition">¶</a></dt>
@@ -306,7 +309,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.utils">
-<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-impy.utils" title="Permalink to this headline">¶</a></h2>
+<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-impy.utils" title="Permalink to this heading">¶</a></h2>
 </section>
 </section>
 
@@ -314,7 +317,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
            </div>
           </div>
           <footer><div class="rst-footer-buttons" role="navigation" aria-label="Footer">
-        <a href="impy.frame.html" class="btn btn-neutral float-left" title="impy.frame package" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left" aria-hidden="true"></span> Previous</a>
+        <a href="impy.lazy.html" class="btn btn-neutral float-left" title="impy.lazy package" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left" aria-hidden="true"></span> Previous</a>
         <a href="impy.viewer.html" class="btn btn-neutral float-right" title="impy.viewer package" accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right" aria-hidden="true"></span></a>
     </div>
 
diff --git a/docs/apidoc/impy.viewer.html b/docs/apidoc/impy.viewer.html
index ce7b3c1f..c3d109c2 100644
--- a/docs/apidoc/impy.viewer.html
+++ b/docs/apidoc/impy.viewer.html
@@ -1,10 +1,10 @@
 <!DOCTYPE html>
 <html class="writer-html5" lang="en" >
 <head>
-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
+  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy.viewer package &mdash; impy 2.2.0 documentation</title>
+  <title>impy.viewer package &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -12,9 +12,8 @@
   <![endif]-->
   
         <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-        <script src="../_static/jquery.js"></script>
-        <script src="../_static/underscore.js"></script>
         <script src="../_static/doctools.js"></script>
+        <script src="../_static/sphinx_highlight.js"></script>
     <script src="../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
@@ -26,14 +25,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -60,10 +63,10 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="../api.html">API References</a> &raquo;</li>
-          <li><a href="impy.html">impy package</a> &raquo;</li>
-      <li>impy.viewer package</li>
+      <li><a href="../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../api.html">API References</a></li>
+          <li class="breadcrumb-item"><a href="impy.html">impy package</a></li>
+      <li class="breadcrumb-item active">impy.viewer package</li>
       <li class="wy-breadcrumbs-aside">
             <a href="../_sources/apidoc/impy.viewer.rst.txt" rel="nofollow"> View page source</a>
       </li>
@@ -74,26 +77,26 @@
            <div itemprop="articleBody">
              
   <section id="impy-viewer-package">
-<h1>impy.viewer package<a class="headerlink" href="#impy-viewer-package" title="Permalink to this headline">¶</a></h1>
+<h1>impy.viewer package<a class="headerlink" href="#impy-viewer-package" title="Permalink to this heading">¶</a></h1>
 <section id="submodules">
-<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline">¶</a></h2>
+<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this heading">¶</a></h2>
 </section>
 <section id="module-impy.viewer.utils">
-<span id="impy-viewer-utils-module"></span><h2>impy.viewer.utils module<a class="headerlink" href="#module-impy.viewer.utils" title="Permalink to this headline">¶</a></h2>
+<span id="impy-viewer-utils-module"></span><h2>impy.viewer.utils module<a class="headerlink" href="#module-impy.viewer.utils" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.viewer.utils.ComplexArrayView">
-<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">ComplexArrayView</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">impy.viewer.utils._A</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#ComplexArrayView"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.ComplexArrayView" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">ComplexArrayView</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">_A</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#ComplexArrayView"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.ComplexArrayView" title="Permalink to this definition">¶</a></dt>
 <dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
 <p>View a complex array in napari.</p>
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.viewer.utils.ComplexArrayView.data_raw">
-<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">data_raw</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">impy.viewer.utils._A</span></em><a class="headerlink" href="#impy.viewer.utils.ComplexArrayView.data_raw" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">data_raw</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">_A</span></em><a class="headerlink" href="#impy.viewer.utils.ComplexArrayView.data_raw" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return the raw data.</p>
 </dd></dl>
 
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.viewer.utils.ComplexArrayView.dtype">
-<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">dtype</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">numpy.dtype</span></em><a class="headerlink" href="#impy.viewer.utils.ComplexArrayView.dtype" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">dtype</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">dtype</span></em><a class="headerlink" href="#impy.viewer.utils.ComplexArrayView.dtype" title="Permalink to this definition">¶</a></dt>
 <dd><p>Data type of array.</p>
 </dd></dl>
 
@@ -119,18 +122,18 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.viewer.utils.add_dask">
-<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">add_dask</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">napari.viewer.Viewer</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">img</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">impy.arrays.lazy.LazyImgArray</span></a></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#add_dask"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.add_dask" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">add_dask</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Viewer</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">img</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><span class="pre">LazyImgArray</span></a></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#add_dask"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.add_dask" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.viewer.utils.add_labeledarray">
-<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">add_labeledarray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">napari.viewer.Viewer</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">img</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray" title="impy.arrays.labeledarray.LabeledArray"><span class="pre">impy.arrays.labeledarray.LabeledArray</span></a></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#add_labeledarray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.add_labeledarray" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">add_labeledarray</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Viewer</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">img</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray" title="impy.arrays.labeledarray.LabeledArray"><span class="pre">LabeledArray</span></a></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#add_labeledarray"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.add_labeledarray" title="Permalink to this definition">¶</a></dt>
 <dd><p>Add a LabeledArray to the viewer.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.viewer.utils.add_labels">
-<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">add_labels</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">napari.Viewer</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">labels</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">opacity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#add_labels"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.add_labels" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">add_labels</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Viewer</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">labels</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="impy.arrays.html#impy.arrays.label.Label" title="impy.arrays.label.Label"><span class="pre">Label</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">opacity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#add_labels"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.add_labels" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
@@ -155,30 +158,30 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.viewer.utils.front_image">
-<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">front_image</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">napari.viewer.Viewer</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#front_image"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.front_image" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">front_image</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Viewer</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#front_image"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.front_image" title="Permalink to this definition">¶</a></dt>
 <dd><p>From list of image layers return the most front visible image.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.viewer.utils.get_a_selected_layer">
-<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">get_a_selected_layer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">napari.viewer.Viewer</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#get_a_selected_layer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.get_a_selected_layer" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">get_a_selected_layer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Viewer</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#get_a_selected_layer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.get_a_selected_layer" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.viewer.utils.get_viewer_scale">
-<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">get_viewer_scale</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">napari.viewer.Viewer</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#get_viewer_scale"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.get_viewer_scale" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">get_viewer_scale</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Viewer</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#get_viewer_scale"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.get_viewer_scale" title="Permalink to this definition">¶</a></dt>
 <dd><p>Get the scale of the viewer.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.viewer.utils.iter_layer">
-<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">iter_layer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">napari.viewer.Viewer</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">layer_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#iter_layer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.iter_layer" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">iter_layer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Viewer</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">layer_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#iter_layer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.iter_layer" title="Permalink to this definition">¶</a></dt>
 <dd><p>Iterate over layers and yield only certain type of layers.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>layer_type</strong> (<em>str</em><em>, </em><em>{&quot;shape&quot;</em><em>, </em><em>&quot;image&quot;</em><em>, </em><em>&quot;point&quot;}</em>) – Type of layer.</p>
 </dd>
-<dt class="field-even">Yields</dt>
+<dt class="field-even">Yields<span class="colon">:</span></dt>
 <dd class="field-even"><p><em>napari.layers</em> – Layers specified by layer_type</p>
 </dd>
 </dl>
@@ -186,19 +189,19 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.viewer.utils.iter_selected_layer">
-<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">iter_selected_layer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">napari.Viewer</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">layer_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#iter_selected_layer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.iter_selected_layer" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">iter_selected_layer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Viewer</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">layer_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#iter_selected_layer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.iter_selected_layer" title="Permalink to this definition">¶</a></dt>
 <dd><p>Iterate over selected layers and yield only certain type of layers.</p>
 </dd></dl>
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.viewer.utils.layer_to_impy_object">
-<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">layer_to_impy_object</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">napari.viewer.Viewer</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">layer</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#layer_to_impy_object"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.layer_to_impy_object" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">layer_to_impy_object</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Viewer</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">layer</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#layer_to_impy_object"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.layer_to_impy_object" title="Permalink to this definition">¶</a></dt>
 <dd><p>Convert layer to real data.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>layer</strong> (<em>napari.layers.Layer</em>) – Input layer.</p>
 </dd>
-<dt class="field-even">Return type</dt>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
 <dd class="field-even"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a>, <a class="reference internal" href="impy.arrays.html#impy.arrays.label.Label" title="impy.arrays.label.Label">Label</a>, <a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a> or <a class="reference internal" href="impy.frame.html#impy.frame.frames.TrackFrame" title="impy.frame.frames.TrackFrame">TrackFrame</a>, or Shape features.</p>
 </dd>
 </dl>
@@ -217,13 +220,13 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py function">
 <dt class="sig sig-object py" id="impy.viewer.utils.viewer_imread">
-<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">viewer_imread</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">napari.viewer.Viewer</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#viewer_imread"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.viewer_imread" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">impy.viewer.utils.</span></span><span class="sig-name descname"><span class="pre">viewer_imread</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">viewer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Viewer</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/utils.html#viewer_imread"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.utils.viewer_imread" title="Permalink to this definition">¶</a></dt>
 <dd><p>Read an image into the viewer.</p>
 </dd></dl>
 
 </section>
 <section id="module-impy.viewer.viewer">
-<span id="impy-viewer-viewer-module"></span><h2>impy.viewer.viewer module<a class="headerlink" href="#module-impy.viewer.viewer" title="Permalink to this headline">¶</a></h2>
+<span id="impy-viewer-viewer-module"></span><h2>impy.viewer.viewer module<a class="headerlink" href="#module-impy.viewer.viewer" title="Permalink to this heading">¶</a></h2>
 <dl class="py class">
 <dt class="sig sig-object py" id="impy.viewer.viewer.napariViewers">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">impy.viewer.viewer.</span></span><span class="sig-name descname"><span class="pre">napariViewers</span></span><a class="reference internal" href="../_modules/impy/viewer/viewer.html#napariViewers"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.viewer.napariViewers" title="Permalink to this definition">¶</a></dt>
@@ -234,7 +237,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <span class="sig-name descname"><span class="pre">add</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">obj</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ImpyObject</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/impy/viewer/viewer.html#napariViewers.add"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.viewer.napariViewers.add" title="Permalink to this definition">¶</a></dt>
 <dd><p>Add images, points, labels, tracks etc to viewer.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>obj</strong> (<em>ImpyObject</em>) – Object to add.</p>
 </dd>
 </dl>
@@ -282,14 +285,14 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.viewer.viewer.napariViewers.axes">
-<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">axes</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">impy.axes._axes.Axes</span></em><a class="headerlink" href="#impy.viewer.viewer.napariViewers.axes" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">axes</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">Axes</span></em><a class="headerlink" href="#impy.viewer.viewer.napariViewers.axes" title="Permalink to this definition">¶</a></dt>
 <dd><p>Axes information of current viewer.</p>
 <p>Defined to make compatible with <code class="docutils literal notranslate"><span class="pre">ImgArray</span></code>.</p>
 </dd></dl>
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.viewer.viewer.napariViewers.axisof">
-<span class="sig-name descname"><span class="pre">axisof</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">symbol</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">int</span></span></span><a class="reference internal" href="../_modules/impy/viewer/viewer.html#napariViewers.axisof"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.viewer.napariViewers.axisof" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">axisof</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">symbol</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">int</span></span></span><a class="reference internal" href="../_modules/impy/viewer/viewer.html#napariViewers.axisof"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.viewer.napariViewers.axisof" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="py property">
@@ -302,7 +305,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.viewer.viewer.napariViewers.cursor_pos">
-<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">cursor_pos</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">numpy.ndarray</span></em><a class="headerlink" href="#impy.viewer.viewer.napariViewers.cursor_pos" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">cursor_pos</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">ndarray</span></em><a class="headerlink" href="#impy.viewer.viewer.napariViewers.cursor_pos" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return cursor position. Scale is considered.</p>
 </dd></dl>
 
@@ -312,7 +315,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dd><p>With cursor position and a layer as inputs, this function returns the cursor “pixel” coordinates on the given
 layer. This function is useful when you want to get such as pixel value at the cursor position.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>ref</strong> (<em>napari.layers.Image</em><em>, </em><em>int</em><em>, </em><em>str</em><em>, </em><a class="reference internal" href="impy.arrays.html#impy.arrays.labeledarray.LabeledArray" title="impy.arrays.labeledarray.LabeledArray"><em>LabeledArray</em></a><em> or </em><a class="reference internal" href="impy.arrays.html#impy.arrays.lazy.LazyImgArray" title="impy.arrays.lazy.LazyImgArray"><em>LazyImgArray</em></a>) – <p>Reference layer or its identifier. To determine the reference layer, this parameter is interpreted in
 different ways depending on its type:</p>
@@ -326,10 +329,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <li><p><strong>ndim</strong> (<em>int</em><em>, </em><em>optional</em>) – If specified, the last ndim coordinates will be returned.</p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>1-D, int64 array of cursor position along each dimension.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p>np.ndarray</p>
 </dd>
 </dl>
@@ -337,10 +340,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.viewer.viewer.napariViewers.get">
-<span class="sig-name descname"><span class="pre">get</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'image'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">layer_state</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'visible'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">returns</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'last'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ImpyObject</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">ImpyObject</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/viewer/viewer.html#napariViewers.get"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.viewer.napariViewers.get" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">get</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">kind</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'image'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">layer_state</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'visible'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">returns</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'last'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ImpyObject</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">impy.viewer.viewer.ImpyObject</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/impy/viewer/viewer.html#napariViewers.get"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.viewer.napariViewers.get" title="Permalink to this definition">¶</a></dt>
 <dd><p>Simple way to get impy object from viewer.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>kind</strong> (<em>str</em><em>, </em><em>optional</em>) – <p>Kind of layers/shapes to return.</p>
 <blockquote>
@@ -380,10 +383,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 </p></li>
 </ul>
 </dd>
-<dt class="field-even">Returns</dt>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
 <dd class="field-even"><p>impy object(s) that satisfies the options.</p>
 </dd>
-<dt class="field-odd">Return type</dt>
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
 <dd class="field-odd"><p><a class="reference internal" href="impy.arrays.html#impy.arrays.imgarray.ImgArray" title="impy.arrays.imgarray.ImgArray">ImgArray</a>, <a class="reference internal" href="impy.arrays.html#impy.arrays.label.Label" title="impy.arrays.label.Label">Label</a>, <a class="reference internal" href="impy.frame.html#impy.frame.frames.MarkerFrame" title="impy.frame.frames.MarkerFrame">MarkerFrame</a> or <a class="reference internal" href="impy.frame.html#impy.frame.frames.TrackFrame" title="impy.frame.frames.TrackFrame">TrackFrame</a>, np.ndarray, or list of one of them.</p>
 </dd>
 </dl>
@@ -434,14 +437,14 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.viewer.viewer.napariViewers.scale">
-<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">scale</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">impy.axes._axes.ScaleView</span></em><a class="headerlink" href="#impy.viewer.viewer.napariViewers.scale" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">scale</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">ScaleView</span></em><a class="headerlink" href="#impy.viewer.viewer.napariViewers.scale" title="Permalink to this definition">¶</a></dt>
 <dd><p>Scale information of current viewer.</p>
 <p>Defined to make compatible with <code class="docutils literal notranslate"><span class="pre">ImgArray</span></code>.</p>
 </dd></dl>
 
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.viewer.viewer.napariViewers.selection">
-<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">selection</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">list[typing.NewType.&lt;locals&gt;.new_type]</span></em><a class="headerlink" href="#impy.viewer.viewer.napariViewers.selection" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">selection</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">list</span><span class="p"><span class="pre">[</span></span><span class="pre">impy.viewer.viewer.ImpyObject</span><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#impy.viewer.viewer.napariViewers.selection" title="Permalink to this definition">¶</a></dt>
 <dd><p>Return selected layers’ data as a list of impy objects.</p>
 </dd></dl>
 
@@ -453,10 +456,10 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py method">
 <dt class="sig sig-object py" id="impy.viewer.viewer.napariViewers.stepof">
-<span class="sig-name descname"><span class="pre">stepof</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">symbol</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">impy.axes._axis.Axis</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">int</span></span></span><a class="reference internal" href="../_modules/impy/viewer/viewer.html#napariViewers.stepof"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.viewer.napariViewers.stepof" title="Permalink to this definition">¶</a></dt>
+<span class="sig-name descname"><span class="pre">stepof</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">symbol</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">Axis</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">int</span></span></span><a class="reference internal" href="../_modules/impy/viewer/viewer.html#napariViewers.stepof"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#impy.viewer.viewer.napariViewers.stepof" title="Permalink to this definition">¶</a></dt>
 <dd><p>Get the current step of certain axis.</p>
 <dl class="field-list simple">
-<dt class="field-odd">Parameters</dt>
+<dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><p><strong>symbol</strong> (<em>AxisLike</em>) – Axis symbol</p>
 </dd>
 </dl>
@@ -464,7 +467,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 <dl class="py property">
 <dt class="sig sig-object py" id="impy.viewer.viewer.napariViewers.viewer">
-<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">viewer</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">napari.viewer.Viewer</span></em><a class="headerlink" href="#impy.viewer.viewer.napariViewers.viewer" title="Permalink to this definition">¶</a></dt>
+<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">viewer</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">Viewer</span></em><a class="headerlink" href="#impy.viewer.viewer.napariViewers.viewer" title="Permalink to this definition">¶</a></dt>
 <dd><p>The most front viewer you’re using</p>
 </dd></dl>
 
@@ -472,7 +475,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 
 </section>
 <section id="module-impy.viewer">
-<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-impy.viewer" title="Permalink to this headline">¶</a></h2>
+<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-impy.viewer" title="Permalink to this heading">¶</a></h2>
 </section>
 </section>
 
diff --git a/docs/apidoc/modules.html b/docs/apidoc/modules.html
index 66f65e58..6c247c34 100644
--- a/docs/apidoc/modules.html
+++ b/docs/apidoc/modules.html
@@ -1,10 +1,10 @@
 <!DOCTYPE html>
 <html class="writer-html5" lang="en" >
 <head>
-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
+  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy &mdash; impy 2.2.0 documentation</title>
+  <title>impy &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -12,9 +12,8 @@
   <![endif]-->
   
         <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-        <script src="../_static/jquery.js"></script>
-        <script src="../_static/underscore.js"></script>
         <script src="../_static/doctools.js"></script>
+        <script src="../_static/sphinx_highlight.js"></script>
     <script src="../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" /> 
@@ -25,14 +24,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -59,8 +62,8 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../index.html" class="icon icon-home"></a> &raquo;</li>
-      <li>impy</li>
+      <li><a href="../index.html" class="icon icon-home" aria-label="Home"></a></li>
+      <li class="breadcrumb-item active">impy</li>
       <li class="wy-breadcrumbs-aside">
             <a href="../_sources/apidoc/modules.rst.txt" rel="nofollow"> View page source</a>
       </li>
@@ -71,7 +74,7 @@
            <div itemprop="articleBody">
              
   <section id="impy">
-<h1>impy<a class="headerlink" href="#impy" title="Permalink to this headline">¶</a></h1>
+<h1>impy<a class="headerlink" href="#impy" title="Permalink to this heading">¶</a></h1>
 <div class="toctree-wrapper compound">
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="impy.html">impy package</a><ul>
@@ -87,6 +90,7 @@ <h1>impy<a class="headerlink" href="#impy" title="Permalink to this headline">¶
 <li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.lazy">impy.arrays.lazy module</a></li>
 <li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.phasearray">impy.arrays.phasearray module</a></li>
 <li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.specials">impy.arrays.specials module</a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#module-impy.arrays.tiled">impy.arrays.tiled module</a></li>
 <li class="toctree-l4"><a class="reference internal" href="impy.arrays.html#module-impy.arrays">Module contents</a></li>
 </ul>
 </li>
@@ -100,6 +104,13 @@ <h1>impy<a class="headerlink" href="#impy" title="Permalink to this headline">¶
 <li class="toctree-l4"><a class="reference internal" href="impy.frame.html#module-impy.frame">Module contents</a></li>
 </ul>
 </li>
+<li class="toctree-l3"><a class="reference internal" href="impy.lazy.html">impy.lazy package</a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.lazy.html#submodules">Submodules</a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.lazy.html#module-impy.lazy.core">impy.lazy.core module</a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.lazy.html#module-impy.lazy.random">impy.lazy.random module</a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.lazy.html#module-impy.lazy">Module contents</a></li>
+</ul>
+</li>
 <li class="toctree-l3"><a class="reference internal" href="impy.utils.html">impy.utils package</a><ul>
 <li class="toctree-l4"><a class="reference internal" href="impy.utils.html#submodules">Submodules</a></li>
 <li class="toctree-l4"><a class="reference internal" href="impy.utils.html#module-impy.utils.axesop">impy.utils.axesop module</a></li>
@@ -121,14 +132,140 @@ <h1>impy<a class="headerlink" href="#impy" title="Permalink to this headline">¶
 </ul>
 </li>
 <li class="toctree-l2"><a class="reference internal" href="impy.html#submodules">Submodules</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.html#module-impy.array_api">impy.array_api module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.html#module-impy.binder">impy.binder module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.html#module-impy.collections">impy.collections module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.html#module-impy.core">impy.core module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.html#module-impy.correlation">impy.correlation module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.html#module-impy.io">impy.io module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.html#module-impy.random">impy.random module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="impy.html#module-impy.roi">impy.roi module</a></li>
+<li class="toctree-l2"><a class="reference internal" href="impy.html#module-impy.array_api">impy.array_api module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.array_api.XP"><code class="docutils literal notranslate"><span class="pre">XP</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.array_api.XP.setCupy"><code class="docutils literal notranslate"><span class="pre">XP.setCupy()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.array_api.XP.setNumpy"><code class="docutils literal notranslate"><span class="pre">XP.setNumpy()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.array_api.cupy_dispatcher"><code class="docutils literal notranslate"><span class="pre">cupy_dispatcher()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.html#module-impy.binder">impy.binder module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.binder.bind"><code class="docutils literal notranslate"><span class="pre">bind</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.binder.bind.bound"><code class="docutils literal notranslate"><span class="pre">bind.bound</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.binder.bind.last_added"><code class="docutils literal notranslate"><span class="pre">bind.last_added</span></code></a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.html#module-impy.collections">impy.collections module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.collections.DataDict"><code class="docutils literal notranslate"><span class="pre">DataDict</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.collections.DataDict.apply"><code class="docutils literal notranslate"><span class="pre">DataDict.apply()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.collections.DataList"><code class="docutils literal notranslate"><span class="pre">DataList</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.collections.DataList.agg"><code class="docutils literal notranslate"><span class="pre">DataList.agg()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.collections.DataList.apply"><code class="docutils literal notranslate"><span class="pre">DataList.apply()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.collections.DataList.insert"><code class="docutils literal notranslate"><span class="pre">DataList.insert()</span></code></a></li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.html#module-impy.core">impy.core module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.arange"><code class="docutils literal notranslate"><span class="pre">arange()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.array"><code class="docutils literal notranslate"><span class="pre">array()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.asarray"><code class="docutils literal notranslate"><span class="pre">asarray()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.asbigarray"><code class="docutils literal notranslate"><span class="pre">asbigarray()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.aslabel"><code class="docutils literal notranslate"><span class="pre">aslabel()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.aslazy"><code class="docutils literal notranslate"><span class="pre">aslazy()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.big_imread"><code class="docutils literal notranslate"><span class="pre">big_imread()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.broadcast_arrays"><code class="docutils literal notranslate"><span class="pre">broadcast_arrays()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.circular_mask"><code class="docutils literal notranslate"><span class="pre">circular_mask()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.empty"><code class="docutils literal notranslate"><span class="pre">empty()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.full"><code class="docutils literal notranslate"><span class="pre">full()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.gaussian_kernel"><code class="docutils literal notranslate"><span class="pre">gaussian_kernel()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.imread"><code class="docutils literal notranslate"><span class="pre">imread()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.imread_collection"><code class="docutils literal notranslate"><span class="pre">imread_collection()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.indices"><code class="docutils literal notranslate"><span class="pre">indices()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.lazy_imread"><code class="docutils literal notranslate"><span class="pre">lazy_imread()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.ones"><code class="docutils literal notranslate"><span class="pre">ones()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.read_meta"><code class="docutils literal notranslate"><span class="pre">read_meta()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.roiread"><code class="docutils literal notranslate"><span class="pre">roiread()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.sample_image"><code class="docutils literal notranslate"><span class="pre">sample_image()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.core.zeros"><code class="docutils literal notranslate"><span class="pre">zeros()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.html#module-impy.correlation">impy.correlation module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.fourier_ncc"><code class="docutils literal notranslate"><span class="pre">fourier_ncc()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.fourier_shell_correlation"><code class="docutils literal notranslate"><span class="pre">fourier_shell_correlation()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.fourier_zncc"><code class="docutils literal notranslate"><span class="pre">fourier_zncc()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.fsc"><code class="docutils literal notranslate"><span class="pre">fsc()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.ft_pcc_landscape"><code class="docutils literal notranslate"><span class="pre">ft_pcc_landscape()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.ft_pcc_maximum"><code class="docutils literal notranslate"><span class="pre">ft_pcc_maximum()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.ft_pcc_maximum_with_corr"><code class="docutils literal notranslate"><span class="pre">ft_pcc_maximum_with_corr()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.manders_coloc"><code class="docutils literal notranslate"><span class="pre">manders_coloc()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.ncc"><code class="docutils literal notranslate"><span class="pre">ncc()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.nmi"><code class="docutils literal notranslate"><span class="pre">nmi()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.pcc_landscape"><code class="docutils literal notranslate"><span class="pre">pcc_landscape()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.pcc_maximum"><code class="docutils literal notranslate"><span class="pre">pcc_maximum()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.pcc_maximum_with_corr"><code class="docutils literal notranslate"><span class="pre">pcc_maximum_with_corr()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.pearson_coloc"><code class="docutils literal notranslate"><span class="pre">pearson_coloc()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.polar_pcc_maximum"><code class="docutils literal notranslate"><span class="pre">polar_pcc_maximum()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.polar_pcc_maximum_with_corr"><code class="docutils literal notranslate"><span class="pre">polar_pcc_maximum_with_corr()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.zncc"><code class="docutils literal notranslate"><span class="pre">zncc()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.zncc_landscape"><code class="docutils literal notranslate"><span class="pre">zncc_landscape()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.zncc_maximum"><code class="docutils literal notranslate"><span class="pre">zncc_maximum()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.correlation.zncc_maximum_with_corr"><code class="docutils literal notranslate"><span class="pre">zncc_maximum_with_corr()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.html#module-impy.io">impy.io module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.io.imread"><code class="docutils literal notranslate"><span class="pre">imread()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.io.imread_dask"><code class="docutils literal notranslate"><span class="pre">imread_dask()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.io.imsave"><code class="docutils literal notranslate"><span class="pre">imsave()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.io.mark_reader"><code class="docutils literal notranslate"><span class="pre">mark_reader()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.io.mark_writer"><code class="docutils literal notranslate"><span class="pre">mark_writer()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.html#module-impy.random">impy.random module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.random.ImageGenerator"><code class="docutils literal notranslate"><span class="pre">ImageGenerator</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.random.ImageGenerator.normal"><code class="docutils literal notranslate"><span class="pre">ImageGenerator.normal()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.random.ImageGenerator.poisson"><code class="docutils literal notranslate"><span class="pre">ImageGenerator.poisson()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.random.ImageGenerator.random"><code class="docutils literal notranslate"><span class="pre">ImageGenerator.random()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.random.ImageGenerator.random_uint16"><code class="docutils literal notranslate"><span class="pre">ImageGenerator.random_uint16()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.random.ImageGenerator.random_uint8"><code class="docutils literal notranslate"><span class="pre">ImageGenerator.random_uint8()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.random.ImageGenerator.standard_exponential"><code class="docutils literal notranslate"><span class="pre">ImageGenerator.standard_exponential()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.random.ImageGenerator.standard_normal"><code class="docutils literal notranslate"><span class="pre">ImageGenerator.standard_normal()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.random.default_rng"><code class="docutils literal notranslate"><span class="pre">default_rng()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.random.normal"><code class="docutils literal notranslate"><span class="pre">normal()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.random.random"><code class="docutils literal notranslate"><span class="pre">random()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.random.random_uint16"><code class="docutils literal notranslate"><span class="pre">random_uint16()</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.random.random_uint8"><code class="docutils literal notranslate"><span class="pre">random_uint8()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l2"><a class="reference internal" href="impy.html#module-impy.roi">impy.roi module</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.roi.LineRoi"><code class="docutils literal notranslate"><span class="pre">LineRoi</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.roi.PointRoi"><code class="docutils literal notranslate"><span class="pre">PointRoi</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.roi.PolyLineRoi"><code class="docutils literal notranslate"><span class="pre">PolyLineRoi</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.roi.PolygonRoi"><code class="docutils literal notranslate"><span class="pre">PolygonRoi</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.roi.PolygonRoi.get_coordinates"><code class="docutils literal notranslate"><span class="pre">PolygonRoi.get_coordinates()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.roi.RectangleRoi"><code class="docutils literal notranslate"><span class="pre">RectangleRoi</span></code></a></li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.roi.Roi"><code class="docutils literal notranslate"><span class="pre">Roi</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.roi.Roi.axes"><code class="docutils literal notranslate"><span class="pre">Roi.axes</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.roi.Roi.copy"><code class="docutils literal notranslate"><span class="pre">Roi.copy()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.roi.Roi.drop"><code class="docutils literal notranslate"><span class="pre">Roi.drop()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.roi.Roi.from_imagejroi"><code class="docutils literal notranslate"><span class="pre">Roi.from_imagejroi()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.roi.Roi.get_coordinates"><code class="docutils literal notranslate"><span class="pre">Roi.get_coordinates()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.roi.Roi.n_spatial_dims"><code class="docutils literal notranslate"><span class="pre">Roi.n_spatial_dims</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.roi.Roi.ndim"><code class="docutils literal notranslate"><span class="pre">Roi.ndim</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.roi.Roi.plot"><code class="docutils literal notranslate"><span class="pre">Roi.plot()</span></code></a></li>
+</ul>
+</li>
+<li class="toctree-l3"><a class="reference internal" href="impy.html#impy.roi.RoiList"><code class="docutils literal notranslate"><span class="pre">RoiList</span></code></a><ul>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.roi.RoiList.axes"><code class="docutils literal notranslate"><span class="pre">RoiList.axes</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.roi.RoiList.drop"><code class="docutils literal notranslate"><span class="pre">RoiList.drop()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.roi.RoiList.fromfile"><code class="docutils literal notranslate"><span class="pre">RoiList.fromfile()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.roi.RoiList.insert"><code class="docutils literal notranslate"><span class="pre">RoiList.insert()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.roi.RoiList.plot"><code class="docutils literal notranslate"><span class="pre">RoiList.plot()</span></code></a></li>
+<li class="toctree-l4"><a class="reference internal" href="impy.html#impy.roi.RoiList.tofile"><code class="docutils literal notranslate"><span class="pre">RoiList.tofile()</span></code></a></li>
+</ul>
+</li>
+</ul>
+</li>
 <li class="toctree-l2"><a class="reference internal" href="impy.html#module-impy">Module contents</a></li>
 </ul>
 </li>
diff --git a/docs/gallery/drift_correction.html b/docs/gallery/drift_correction.html
index e4cdac51..5dd59bca 100644
--- a/docs/gallery/drift_correction.html
+++ b/docs/gallery/drift_correction.html
@@ -1,10 +1,10 @@
 <!DOCTYPE html>
 <html class="writer-html5" lang="en" >
 <head>
-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
+  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>Drift Correction &mdash; impy 2.2.0 documentation</title>
+  <title>Drift Correction &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -12,9 +12,8 @@
   <![endif]-->
   
         <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-        <script src="../_static/jquery.js"></script>
-        <script src="../_static/underscore.js"></script>
         <script src="../_static/doctools.js"></script>
+        <script src="../_static/sphinx_highlight.js"></script>
     <script src="../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" /> 
@@ -25,14 +24,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -59,8 +62,8 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../index.html" class="icon icon-home"></a> &raquo;</li>
-      <li>Drift Correction</li>
+      <li><a href="../index.html" class="icon icon-home" aria-label="Home"></a></li>
+      <li class="breadcrumb-item active">Drift Correction</li>
       <li class="wy-breadcrumbs-aside">
             <a href="../_sources/gallery/drift_correction.rst.txt" rel="nofollow"> View page source</a>
       </li>
@@ -71,10 +74,10 @@
            <div itemprop="articleBody">
              
   <section id="drift-correction">
-<h1>Drift Correction<a class="headerlink" href="#drift-correction" title="Permalink to this headline">¶</a></h1>
+<h1>Drift Correction<a class="headerlink" href="#drift-correction" title="Permalink to this heading">¶</a></h1>
 <p>Stage shift during image acquisition is a general problem of microscopy.
 Here shows how to correct the shift using <code class="docutils literal notranslate"><span class="pre">drift_correction</span></code> method.</p>
-<div class="contents local topic" id="contents">
+<nav class="contents local" id="contents">
 <p class="topic-title">Contents</p>
 <ul class="simple">
 <li><p><a class="reference internal" href="#simplest-correction" id="id1">Simplest Correction</a></p></li>
@@ -82,9 +85,9 @@ <h1>Drift Correction<a class="headerlink" href="#drift-correction" title="Permal
 <li><p><a class="reference internal" href="#correction-with-reference" id="id3">Correction with Reference</a></p></li>
 <li><p><a class="reference internal" href="#correct-large-images" id="id4">Correct Large Images</a></p></li>
 </ul>
-</div>
+</nav>
 <section id="simplest-correction">
-<h2><a class="toc-backref" href="#id1">Simplest Correction</a><a class="headerlink" href="#simplest-correction" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id1" role="doc-backlink">Simplest Correction</a><a class="headerlink" href="#simplest-correction" title="Permalink to this heading">¶</a></h2>
 <p>We’ll create a sample image stack by applying random shifts to an image using <code class="docutils literal notranslate"><span class="pre">affine</span></code> method
 and Gaussian noise using <code class="docutils literal notranslate"><span class="pre">ip.random.normal</span></code> function.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
@@ -116,7 +119,7 @@ <h2><a class="toc-backref" href="#id1">Simplest Correction</a><a class="headerli
 </div>
 </section>
 <section id="multi-dimensional-correction">
-<h2><a class="toc-backref" href="#id2">Multi-dimensional Correction</a><a class="headerlink" href="#multi-dimensional-correction" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id2" role="doc-backlink">Multi-dimensional Correction</a><a class="headerlink" href="#multi-dimensional-correction" title="Permalink to this heading">¶</a></h2>
 <p>By default, <code class="docutils literal notranslate"><span class="pre">drift_correction</span></code> consider <code class="docutils literal notranslate"><span class="pre">&quot;y&quot;,</span> <span class="pre">&quot;x&quot;</span></code> axes as the spatial dimensions and conduct
 2-D correction unlike many of other methods. This is because image drift usually occurs in XY
 direction. The example below:</p>
@@ -138,7 +141,7 @@ <h2><a class="toc-backref" href="#id2">Multi-dimensional Correction</a><a class=
 </div>
 </section>
 <section id="correction-with-reference">
-<h2><a class="toc-backref" href="#id3">Correction with Reference</a><a class="headerlink" href="#correction-with-reference" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id3" role="doc-backlink">Correction with Reference</a><a class="headerlink" href="#correction-with-reference" title="Permalink to this heading">¶</a></h2>
 <p>Sometimes you may want to supply a “reference” image stack to determine drift, instead of using
 the image itself. There are many occasions that you should think of this.</p>
 <ul class="simple">
@@ -167,7 +170,7 @@ <h2><a class="toc-backref" href="#id3">Correction with Reference</a><a class="he
 </div>
 </section>
 <section id="correct-large-images">
-<h2><a class="toc-backref" href="#id4">Correct Large Images</a><a class="headerlink" href="#correct-large-images" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id4" role="doc-backlink">Correct Large Images</a><a class="headerlink" href="#correct-large-images" title="Permalink to this heading">¶</a></h2>
 <p>TODO</p>
 </section>
 </section>
diff --git a/docs/gallery/filters.html b/docs/gallery/filters.html
index e7dbd102..5f105bd1 100644
--- a/docs/gallery/filters.html
+++ b/docs/gallery/filters.html
@@ -1,10 +1,10 @@
 <!DOCTYPE html>
 <html class="writer-html5" lang="en" >
 <head>
-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
+  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>Image Filters &mdash; impy 2.2.0 documentation</title>
+  <title>Image Filters &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -12,9 +12,8 @@
   <![endif]-->
   
         <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-        <script src="../_static/jquery.js"></script>
-        <script src="../_static/underscore.js"></script>
         <script src="../_static/doctools.js"></script>
+        <script src="../_static/sphinx_highlight.js"></script>
     <script src="../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
@@ -27,14 +26,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -85,9 +88,9 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="index.html">Gallery</a> &raquo;</li>
-      <li>Image Filters</li>
+      <li><a href="../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="index.html">Gallery</a></li>
+      <li class="breadcrumb-item active">Image Filters</li>
       <li class="wy-breadcrumbs-aside">
             <a href="../_sources/gallery/filters.rst.txt" rel="nofollow"> View page source</a>
       </li>
@@ -98,7 +101,7 @@
            <div itemprop="articleBody">
              
   <section id="image-filters">
-<h1>Image Filters<a class="headerlink" href="#image-filters" title="Permalink to this headline">¶</a></h1>
+<h1>Image Filters<a class="headerlink" href="#image-filters" title="Permalink to this heading">¶</a></h1>
 <p>There are several filtering methods implemented in <code class="docutils literal notranslate"><span class="pre">ImgArray</span></code>.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">impy</span> <span class="k">as</span> <span class="nn">ip</span>
 
@@ -115,7 +118,7 @@ <h1>Image Filters<a class="headerlink" href="#image-filters" title="Permalink to
      <span class="n">scale</span>      <span class="p">:</span> <span class="n">ScaleView</span><span class="p">(</span><span class="n">t</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">z</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="mf">1.0</span><span class="p">)</span>
 </pre></div>
 </div>
-<div class="contents local topic" id="contents">
+<nav class="contents local" id="contents">
 <p class="topic-title">Contents</p>
 <ul class="simple">
 <li><p><a class="reference internal" href="#batch-processing" id="id1">Batch Processing</a></p></li>
@@ -140,9 +143,9 @@ <h1>Image Filters<a class="headerlink" href="#image-filters" title="Permalink to
 </ul>
 </li>
 </ul>
-</div>
+</nav>
 <section id="batch-processing">
-<h2><a class="toc-backref" href="#id1">Batch Processing</a><a class="headerlink" href="#batch-processing" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id1" role="doc-backlink">Batch Processing</a><a class="headerlink" href="#batch-processing" title="Permalink to this heading">¶</a></h2>
 <p>By default, <code class="docutils literal notranslate"><span class="pre">ImgArray</span></code> consider <code class="docutils literal notranslate"><span class="pre">[&quot;z&quot;,</span> <span class="pre">&quot;y&quot;,</span> <span class="pre">&quot;x&quot;]</span></code> axes as spatial axes and iterate functions
 along other axes. In this example, 3-D filter will be applied for every <code class="docutils literal notranslate"><span class="pre">&quot;t&quot;</span></code>. If you want
 other iteration options, explicitly specify <code class="docutils literal notranslate"><span class="pre">dims</span></code> keyword argument.</p>
@@ -153,9 +156,9 @@ <h2><a class="toc-backref" href="#id1">Batch Processing</a><a class="headerlink"
 </div>
 </section>
 <section id="denoising">
-<h2><a class="toc-backref" href="#id2">Denoising</a><a class="headerlink" href="#denoising" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id2" role="doc-backlink">Denoising</a><a class="headerlink" href="#denoising" title="Permalink to this heading">¶</a></h2>
 <section id="gaussian-filter">
-<h3><a class="toc-backref" href="#id3">Gaussian filter</a><a class="headerlink" href="#gaussian-filter" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id3" role="doc-backlink">Gaussian filter</a><a class="headerlink" href="#gaussian-filter" title="Permalink to this heading">¶</a></h3>
 <p>Gaussian filter is a widely used denoising filter. It blurs image using Gaussian kernel.
 <code class="docutils literal notranslate"><span class="pre">sigma</span></code> is standard deviation (in pixel) of the kernel.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">img</span><span class="o">.</span><span class="n">gaussian_filter</span><span class="p">()</span>  <span class="c1"># sigma=1.0 by default</span>
@@ -165,7 +168,7 @@ <h3><a class="toc-backref" href="#id3">Gaussian filter</a><a class="headerlink"
 </div>
 </section>
 <section id="median-filter">
-<h3><a class="toc-backref" href="#id4">Median filter</a><a class="headerlink" href="#median-filter" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id4" role="doc-backlink">Median filter</a><a class="headerlink" href="#median-filter" title="Permalink to this heading">¶</a></h3>
 <p>Median filter is a denoising that is considered to be robust against outliers. Kernel shape is
 specified by <code class="docutils literal notranslate"><span class="pre">radius</span></code> argument.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">img</span><span class="o">.</span><span class="n">median_filter</span><span class="p">()</span>  <span class="c1"># radius=1.0 by default</span>
@@ -175,7 +178,7 @@ <h3><a class="toc-backref" href="#id4">Median filter</a><a class="headerlink" hr
 </div>
 </section>
 <section id="mean-filter">
-<h3><a class="toc-backref" href="#id5">Mean filter</a><a class="headerlink" href="#mean-filter" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id5" role="doc-backlink">Mean filter</a><a class="headerlink" href="#mean-filter" title="Permalink to this heading">¶</a></h3>
 <p>Mean filter (uniform filter) is a simple denoising, where image is locally averaged with same
 weight.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">img</span><span class="o">.</span><span class="n">mean_filter</span><span class="p">()</span>  <span class="c1"># radius=1.0 by default</span>
@@ -186,9 +189,9 @@ <h3><a class="toc-backref" href="#id5">Mean filter</a><a class="headerlink" href
 </section>
 </section>
 <section id="use-standard-deviation">
-<h2><a class="toc-backref" href="#id6">Use Standard Deviation</a><a class="headerlink" href="#use-standard-deviation" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id6" role="doc-backlink">Use Standard Deviation</a><a class="headerlink" href="#use-standard-deviation" title="Permalink to this heading">¶</a></h2>
 <section id="standard-deviation-filter">
-<h3><a class="toc-backref" href="#id7">Standard deviation filter</a><a class="headerlink" href="#standard-deviation-filter" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id7" role="doc-backlink">Standard deviation filter</a><a class="headerlink" href="#standard-deviation-filter" title="Permalink to this heading">¶</a></h3>
 <p>Standard deviation filter can detect regions that signal changes a lot.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">img</span><span class="o">.</span><span class="n">std_filter</span><span class="p">()</span>  <span class="c1"># radius=1.0 by default</span>
 <span class="n">img</span><span class="o">.</span><span class="n">std_filter</span><span class="p">(</span><span class="n">radius</span><span class="o">=</span><span class="mf">3.2</span><span class="p">)</span>
@@ -197,7 +200,7 @@ <h3><a class="toc-backref" href="#id7">Standard deviation filter</a><a class="he
 </div>
 </section>
 <section id="coefficient-of-variation-filter">
-<h3><a class="toc-backref" href="#id8">Coefficient of variation filter</a><a class="headerlink" href="#coefficient-of-variation-filter" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id8" role="doc-backlink">Coefficient of variation filter</a><a class="headerlink" href="#coefficient-of-variation-filter" title="Permalink to this heading">¶</a></h3>
 <p>Coefficient of variation is a quantity that is defined by <cite>S.D. / mean</cite>. Coefficient of
 variation filter is similar to standard deviation filter but is not sensitive to mean intensity.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">img</span><span class="o">.</span><span class="n">coef_filter</span><span class="p">()</span>  <span class="c1"># radius=1.0 by default</span>
@@ -208,9 +211,9 @@ <h3><a class="toc-backref" href="#id8">Coefficient of variation filter</a><a cla
 </section>
 </section>
 <section id="feature-detection">
-<h2><a class="toc-backref" href="#id9">Feature Detection</a><a class="headerlink" href="#feature-detection" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id9" role="doc-backlink">Feature Detection</a><a class="headerlink" href="#feature-detection" title="Permalink to this heading">¶</a></h2>
 <section id="edge-detection">
-<h3><a class="toc-backref" href="#id10">Edge detection</a><a class="headerlink" href="#edge-detection" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id10" role="doc-backlink">Edge detection</a><a class="headerlink" href="#edge-detection" title="Permalink to this heading">¶</a></h3>
 <p>Edge detection filters generate images that have large value at the regions that signal change
 largely. You can consider them as scalar differentiation of images. Different edge detection
 filter used slightly different kernel but these kernels always take positive values on one side
@@ -223,7 +226,7 @@ <h3><a class="toc-backref" href="#id10">Edge detection</a><a class="headerlink"
 </div>
 </section>
 <section id="puncta-detection">
-<h3><a class="toc-backref" href="#id11">Puncta detection</a><a class="headerlink" href="#puncta-detection" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id11" role="doc-backlink">Puncta detection</a><a class="headerlink" href="#puncta-detection" title="Permalink to this heading">¶</a></h3>
 <p>Puncta detection filters are useful for automatic molecule detection with images taken by light
 or electron microscope. Note that images must be dark-background.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">img</span><span class="o">.</span><span class="n">dog_filter</span><span class="p">()</span>  <span class="c1"># DoG (Difference of Gaussian)</span>
@@ -233,7 +236,7 @@ <h3><a class="toc-backref" href="#id11">Puncta detection</a><a class="headerlink
 </div>
 </section>
 <section id="filament-detection">
-<h3><a class="toc-backref" href="#id12">Filament detection</a><a class="headerlink" href="#filament-detection" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id12" role="doc-backlink">Filament detection</a><a class="headerlink" href="#filament-detection" title="Permalink to this heading">¶</a></h3>
 <p>A “filament” can be defined by 2nd derivative: convex in one direction and flat in the perpendicular
 direction. This trick can be achieved by inspecting the Hessian of an image.</p>
 <p><code class="docutils literal notranslate"><span class="pre">hessian_eigval</span></code> is composed of two steps. First, apply Gaussain filter to the image. Then,
diff --git a/docs/gallery/index.html b/docs/gallery/index.html
index afe0d54c..3a6cd0e2 100644
--- a/docs/gallery/index.html
+++ b/docs/gallery/index.html
@@ -1,10 +1,10 @@
 <!DOCTYPE html>
 <html class="writer-html5" lang="en" >
 <head>
-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
+  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>Gallery &mdash; impy 2.2.0 documentation</title>
+  <title>Gallery &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -12,9 +12,8 @@
   <![endif]-->
   
         <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-        <script src="../_static/jquery.js"></script>
-        <script src="../_static/underscore.js"></script>
         <script src="../_static/doctools.js"></script>
+        <script src="../_static/sphinx_highlight.js"></script>
     <script src="../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
@@ -27,14 +26,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -65,8 +68,8 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../index.html" class="icon icon-home"></a> &raquo;</li>
-      <li>Gallery</li>
+      <li><a href="../index.html" class="icon icon-home" aria-label="Home"></a></li>
+      <li class="breadcrumb-item active">Gallery</li>
       <li class="wy-breadcrumbs-aside">
             <a href="../_sources/gallery/index.rst.txt" rel="nofollow"> View page source</a>
       </li>
@@ -77,7 +80,7 @@
            <div itemprop="articleBody">
              
   <section id="gallery">
-<h1>Gallery<a class="headerlink" href="#gallery" title="Permalink to this headline">¶</a></h1>
+<h1>Gallery<a class="headerlink" href="#gallery" title="Permalink to this heading">¶</a></h1>
 <div class="toctree-wrapper compound">
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="filters.html">Image Filters</a></li>
diff --git a/docs/gallery/regionprops.html b/docs/gallery/regionprops.html
index a7d94365..593f8b6e 100644
--- a/docs/gallery/regionprops.html
+++ b/docs/gallery/regionprops.html
@@ -1,10 +1,10 @@
 <!DOCTYPE html>
 <html class="writer-html5" lang="en" >
 <head>
-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
+  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>Labeling and Measurement &mdash; impy 2.2.0 documentation</title>
+  <title>Labeling and Measurement &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="../_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -12,9 +12,8 @@
   <![endif]-->
   
         <script data-url_root="../" id="documentation_options" src="../_static/documentation_options.js"></script>
-        <script src="../_static/jquery.js"></script>
-        <script src="../_static/underscore.js"></script>
         <script src="../_static/doctools.js"></script>
+        <script src="../_static/sphinx_highlight.js"></script>
     <script src="../_static/js/theme.js"></script>
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
@@ -27,14 +26,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="../index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="../index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="../search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -71,9 +74,9 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="../index.html" class="icon icon-home"></a> &raquo;</li>
-          <li><a href="index.html">Gallery</a> &raquo;</li>
-      <li>Labeling and Measurement</li>
+      <li><a href="../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="index.html">Gallery</a></li>
+      <li class="breadcrumb-item active">Labeling and Measurement</li>
       <li class="wy-breadcrumbs-aside">
             <a href="../_sources/gallery/regionprops.rst.txt" rel="nofollow"> View page source</a>
       </li>
@@ -84,9 +87,9 @@
            <div itemprop="articleBody">
              
   <section id="labeling-and-measurement">
-<h1>Labeling and Measurement<a class="headerlink" href="#labeling-and-measurement" title="Permalink to this headline">¶</a></h1>
+<h1>Labeling and Measurement<a class="headerlink" href="#labeling-and-measurement" title="Permalink to this heading">¶</a></h1>
 <p>Here we’re going to label a image and measure some features for each label.</p>
-<div class="contents local topic" id="contents">
+<nav class="contents local" id="contents">
 <p class="topic-title">Contents</p>
 <ul class="simple">
 <li><p><a class="reference internal" href="#basics" id="id1">Basics</a></p></li>
@@ -94,9 +97,9 @@ <h1>Labeling and Measurement<a class="headerlink" href="#labeling-and-measuremen
 <li><p><a class="reference internal" href="#measurement" id="id3">Measurement</a></p></li>
 <li><p><a class="reference internal" href="#conditional-labeling" id="id4">Conditional Labeling</a></p></li>
 </ul>
-</div>
+</nav>
 <section id="basics">
-<h2><a class="toc-backref" href="#id1">Basics</a><a class="headerlink" href="#basics" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id1" role="doc-backlink">Basics</a><a class="headerlink" href="#basics" title="Permalink to this heading">¶</a></h2>
 <p>Get the sample image.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">impy</span> <span class="k">as</span> <span class="nn">ip</span>
 <span class="n">img</span> <span class="o">=</span> <span class="n">ip</span><span class="o">.</span><span class="n">sample_image</span><span class="p">(</span><span class="s2">&quot;coins&quot;</span><span class="p">)</span>
@@ -111,7 +114,7 @@ <h2><a class="toc-backref" href="#id1">Basics</a><a class="headerlink" href="#ba
 <p>Both method returns a <code class="docutils literal notranslate"><span class="pre">Label</span></code> array, a subclass of <code class="docutils literal notranslate"><span class="pre">MetaArray</span></code>.</p>
 </section>
 <section id="simple-labeling">
-<h2><a class="toc-backref" href="#id2">Simple labeling</a><a class="headerlink" href="#simple-labeling" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id2" role="doc-backlink">Simple labeling</a><a class="headerlink" href="#simple-labeling" title="Permalink to this heading">¶</a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">img</span><span class="o">.</span><span class="n">label_threshold</span><span class="p">()</span>
 </pre></div>
 </div>
@@ -154,7 +157,7 @@ <h2><a class="toc-backref" href="#id2">Simple labeling</a><a class="headerlink"
 </div>
 </section>
 <section id="measurement">
-<h2><a class="toc-backref" href="#id3">Measurement</a><a class="headerlink" href="#measurement" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id3" role="doc-backlink">Measurement</a><a class="headerlink" href="#measurement" title="Permalink to this heading">¶</a></h2>
 <p>After labeling, <code class="docutils literal notranslate"><span class="pre">regionprops</span></code> method is useful for image measurement. This method runs
 <code class="docutils literal notranslate"><span class="pre">skimage.measure.regionprops</span></code> inside.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">props</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">regionprops</span><span class="p">(</span><span class="n">properties</span><span class="o">=</span><span class="p">(</span><span class="s2">&quot;mean_intensity&quot;</span><span class="p">,</span> <span class="s2">&quot;area&quot;</span><span class="p">,</span> <span class="s2">&quot;major_axis_length&quot;</span><span class="p">))</span>
@@ -207,13 +210,13 @@ <h2><a class="toc-backref" href="#id3">Measurement</a><a class="headerlink" href
 </div>
 </section>
 <section id="conditional-labeling">
-<h2><a class="toc-backref" href="#id4">Conditional Labeling</a><a class="headerlink" href="#conditional-labeling" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id4" role="doc-backlink">Conditional Labeling</a><a class="headerlink" href="#conditional-labeling" title="Permalink to this heading">¶</a></h2>
 <p>Simple labeling based on thresholding always yields in insufficient results.</p>
 <p>The <code class="docutils literal notranslate"><span class="pre">filt</span></code> argument can filter labels based on properties of image and labels.
 Basic usage is following. Filter function must take at least two argument, image itself and
 newly created label region.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">filt</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">lbl</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;Return true if label passes a criterion you set.&quot;&quot;&quot;</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;Return true if label passes a criterion you set.&quot;&quot;&quot;</span>
 
 <span class="n">img</span><span class="o">.</span><span class="n">label_threshold</span><span class="p">(</span><span class="n">filt</span><span class="o">=</span><span class="n">filt</span><span class="p">)</span>
 </pre></div>
diff --git a/docs/genindex.html b/docs/genindex.html
index 0dfc913b..676860b1 100644
--- a/docs/genindex.html
+++ b/docs/genindex.html
@@ -3,7 +3,7 @@
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>Index &mdash; impy 2.2.0 documentation</title>
+  <title>Index &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -11,9 +11,8 @@
   <![endif]-->
   
         <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
-        <script src="_static/jquery.js"></script>
-        <script src="_static/underscore.js"></script>
         <script src="_static/doctools.js"></script>
+        <script src="_static/sphinx_highlight.js"></script>
     <script src="_static/js/theme.js"></script>
     <link rel="index" title="Index" href="#" />
     <link rel="search" title="Search" href="search.html" /> 
@@ -24,14 +23,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -58,8 +61,8 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="index.html" class="icon icon-home"></a> &raquo;</li>
-      <li>Index</li>
+      <li><a href="index.html" class="icon icon-home" aria-label="Home"></a></li>
+      <li class="breadcrumb-item active">Index</li>
       <li class="wy-breadcrumbs-aside">
       </li>
   </ul>
@@ -108,8 +111,12 @@ <h2 id="A">A</h2>
 </li>
       <li><a href="apidoc/impy.viewer.html#impy.viewer.viewer.napariViewers.add_image">add_image() (impy.viewer.viewer.napariViewers method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.add_label">add_label() (impy.arrays.label.Label method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.Label.add_label">add_label() (impy.arrays.Label method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.add_label">(impy.arrays.label.Label method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.viewer.html#impy.viewer.utils.add_labeledarray">add_labeledarray() (in module impy.viewer.utils)</a>
 </li>
       <li><a href="apidoc/impy.viewer.html#impy.viewer.viewer.napariViewers.add_labels">add_labels() (impy.viewer.viewer.napariViewers method)</a>
@@ -146,8 +153,14 @@ <h2 id="A">A</h2>
 
       <ul>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.additional_props">(impy.arrays.lazy.LazyImgArray attribute)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.additional_props">(impy.arrays.LazyImgArray attribute)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.PhaseArray.additional_props">(impy.arrays.PhaseArray attribute)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.additional_props">(impy.arrays.phasearray.PhaseArray attribute)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.PropArray.additional_props">(impy.arrays.PropArray attribute)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.specials.PropArray.additional_props">(impy.arrays.specials.PropArray attribute)</a>
 </li>
@@ -155,15 +168,25 @@ <h2 id="A">A</h2>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.affine">affine() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.affine">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.affine">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.affine">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.affine">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.affine">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.html#impy.collections.DataList.agg">agg() (impy.collections.DataList method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.append_label">append_label() (impy.arrays.labeledarray.LabeledArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.append_label">append_label() (impy.arrays.LabeledArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.append_label">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.collections.DataDict.apply">apply() (impy.collections.DataDict method)</a>
 
       <ul>
@@ -171,43 +194,87 @@ <h2 id="A">A</h2>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.apply_dask_func">apply_dask_func() (impy.arrays.lazy.LazyImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.apply_dask_func">(impy.arrays.LazyImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.core.arange">arange() (in module impy.core)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.lazy.html#impy.lazy.core.arange">(in module impy.lazy.core)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.area_closing">area_closing() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.area_closing">area_closing() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.area_closing">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.area_opening">area_opening() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.area_opening">area_opening() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.area_opening">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.argmax_nd">argmax_nd() (impy.arrays.bases.metaarray.MetaArray method)</a>
 </li>
       <li><a href="apidoc/impy.html#impy.core.array">array() (in module impy.core)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.lazy.html#impy.lazy.core.array">(in module impy.lazy.core)</a>
 </li>
-  </ul></td>
-  <td style="width: 33%; vertical-align: top;"><ul>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.ArrayCovariates">ArrayCovariates (class in impy.arrays.labeledarray)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.as_exp">as_exp() (impy.arrays.phasearray.PhaseArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.PhaseArray.as_exp">as_exp() (impy.arrays.PhaseArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.as_exp">(impy.arrays.phasearray.PhaseArray method)</a>
 </li>
+      </ul></li>
+  </ul></td>
+  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.as_float">as_float() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.as_float">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.as_float">(impy.arrays.LabeledArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.as_float">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.as_float">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.as_float">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.specials.PropArray.as_frame">as_frame() (impy.arrays.specials.PropArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.PropArray.as_frame">as_frame() (impy.arrays.PropArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.specials.PropArray.as_frame">(impy.arrays.specials.PropArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.as_img_type">as_img_type() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.as_img_type">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.as_img_type">(impy.arrays.LabeledArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.as_img_type">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.as_img_type">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.as_img_type">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.as_larger_type">as_larger_type() (impy.arrays.label.Label method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.Label.as_larger_type">as_larger_type() (impy.arrays.Label method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.as_larger_type">(impy.arrays.label.Label method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.frame.html#impy.frame.frames.TrackFrame.as_path">as_path() (impy.frame.frames.TrackFrame method)</a>
 </li>
       <li><a href="apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.as_rgba">as_rgba() (impy.arrays.bases.metaarray.MetaArray method)</a>
@@ -217,21 +284,37 @@ <h2 id="A">A</h2>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.as_uint16">as_uint16() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.as_uint16">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.as_uint16">(impy.arrays.LabeledArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.as_uint16">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.as_uint16">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.as_uint16">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.as_uint8">as_uint8() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.as_uint8">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.as_uint8">(impy.arrays.LabeledArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.as_uint8">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.as_uint8">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.as_uint8">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.html#impy.core.asarray">asarray() (in module impy.core)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.lazy.html#impy.lazy.core.asarray">(in module impy.lazy.core)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.core.asbigarray">asbigarray() (in module impy.core)</a>
 </li>
       <li><a href="apidoc/impy.utils.html#impy.utils.gauss.DiagonalGaussian.asdict">asdict() (impy.utils.gauss.DiagonalGaussian method)</a>
@@ -243,7 +326,11 @@ <h2 id="A">A</h2>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.axesmixin.AxesMixin.axes">axes (impy.arrays.axesmixin.AxesMixin property)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.axes">(impy.arrays.ImgArray attribute)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.axes">(impy.arrays.imgarray.ImgArray attribute)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.axes">(impy.arrays.LabeledArray property)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.axes">(impy.arrays.labeledarray.LabeledArray property)</a>
 </li>
@@ -278,25 +365,43 @@ <h2 id="B">B</h2>
 </li>
       <li><a href="apidoc/impy.html#impy.core.big_imread">big_imread() (in module impy.core)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray">BigImgArray (class in impy.arrays.big)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray">BigImgArray (class in impy.arrays)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray">(class in impy.arrays.big)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.binder.bind">bind (class in impy.binder)</a>
 </li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.binning">binning() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.binning">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.binning">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.binning">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.binning">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.binning">(impy.arrays.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.PhaseArray.binning">(impy.arrays.PhaseArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.binning">(impy.arrays.phasearray.PhaseArray method)</a>
 </li>
       </ul></li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.border">border (impy.arrays.phasearray.PhaseArray attribute)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.PhaseArray.border">border (impy.arrays.PhaseArray attribute)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.border">(impy.arrays.phasearray.PhaseArray attribute)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.binder.bind.bound">bound (impy.binder.bind attribute)</a>
+</li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.tiled.TiledImage.boundary">boundary (impy.arrays.tiled.TiledImage property)</a>
 </li>
       <li><a href="apidoc/impy.html#impy.core.broadcast_arrays">broadcast_arrays() (in module impy.core)</a>
 </li>
@@ -308,8 +413,18 @@ <h2 id="B">B</h2>
 <h2 id="C">C</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.centroid_sm">centroid_sm() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.center_of_mass">center_of_mass() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.center_of_mass">(impy.arrays.imgarray.ImgArray method)</a>
+</li>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.centroid_sm">centroid_sm() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.centroid_sm">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.check_filter_func">check_filter_func() (in module impy.arrays.imgarray)</a>
 </li>
       <li><a href="apidoc/impy.utils.html#impy.utils.deco.check_input_and_output">check_input_and_output() (in module impy.utils.deco)</a>
@@ -319,27 +434,59 @@ <h2 id="C">C</h2>
       <li><a href="apidoc/impy.utils.html#impy.utils.misc.check_nd">check_nd() (in module impy.utils.misc)</a>
 </li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.chunk_info">chunk_info (impy.arrays.lazy.LazyImgArray property)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.chunk_info">(impy.arrays.LazyImgArray property)</a>
+</li>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.tiled.TiledImage.chunks">chunks (impy.arrays.tiled.TiledImage property)</a>
 </li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.chunksize">chunksize (impy.arrays.lazy.LazyImgArray property)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.chunksize">(impy.arrays.LazyImgArray property)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.chunksizeof">chunksizeof() (impy.arrays.lazy.LazyImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.chunksizeof">(impy.arrays.LazyImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.chunksizesof">chunksizesof() (impy.arrays.lazy.LazyImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.chunksizesof">(impy.arrays.LazyImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.core.circular_mask">circular_mask() (in module impy.core)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.clip">clip() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.clip">clip() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.clip">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.closing">closing() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.closing">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.closing">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.closing">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.closing">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.closing">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.coef_filter">coef_filter() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.coef_filter">coef_filter() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.coef_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.frame.html#impy.frame.frames.AxesFrame.col_axes">col_axes (impy.frame.frames.AxesFrame property)</a>
 </li>
       <li><a href="apidoc/impy.utils.html#impy.utils.axesop.complement_axes">complement_axes() (in module impy.utils.axesop)</a>
@@ -347,21 +494,35 @@ <h2 id="C">C</h2>
       <li><a href="apidoc/impy.viewer.html#impy.viewer.utils.ComplexArrayView">ComplexArrayView (class in impy.viewer.utils)</a>
 </li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.compute">compute() (impy.arrays.lazy.LazyImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.compute">(impy.arrays.LazyImgArray method)</a>
 </li>
+      </ul></li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.ArrayCovariates.construct_by_copying">construct_by_copying() (impy.arrays.labeledarray.ArrayCovariates method)</a>
 </li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.ArrayCovariates.construct_by_slicing">construct_by_slicing() (impy.arrays.labeledarray.ArrayCovariates method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.convex_hull">convex_hull() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.convex_hull">convex_hull() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.convex_hull">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.convolve">convolve() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.convolve">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.convolve">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.convolve">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.convolve">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.convolve">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.SupportAxesSlicing.copy">copy() (impy.arrays.labeledarray.SupportAxesSlicing method)</a>
@@ -370,22 +531,46 @@ <h2 id="C">C</h2>
         <li><a href="apidoc/impy.html#impy.roi.Roi.copy">(impy.roi.Roi method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.corner_harris">corner_harris() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.corner_harris">corner_harris() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.corner_harris">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.corner_peaks">corner_peaks() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.corner_peaks">corner_peaks() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.corner_peaks">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.count_neighbors">count_neighbors() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.count_neighbors">count_neighbors() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.count_neighbors">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.covariates">covariates (impy.arrays.labeledarray.LabeledArray property)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.covariates">covariates (impy.arrays.LabeledArray property)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.covariates">(impy.arrays.labeledarray.LabeledArray property)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.crop_center">crop_center() (impy.arrays.labeledarray.LabeledArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.crop_center">crop_center() (impy.arrays.LabeledArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.crop_center">(impy.arrays.labeledarray.LabeledArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.crop_center">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.crop_center">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.crop_kernel">crop_kernel() (impy.arrays.labeledarray.LabeledArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.crop_kernel">crop_kernel() (impy.arrays.LabeledArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.crop_kernel">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.array_api.cupy_dispatcher">cupy_dispatcher() (in module impy.array_api)</a>
 </li>
       <li><a href="apidoc/impy.viewer.html#impy.viewer.viewer.napariViewers.current_slice">current_slice (impy.viewer.viewer.napariViewers property)</a>
@@ -394,8 +579,12 @@ <h2 id="C">C</h2>
 </li>
       <li><a href="apidoc/impy.viewer.html#impy.viewer.viewer.napariViewers.cursor_to_pixel">cursor_to_pixel() (impy.viewer.viewer.napariViewers method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.specials.PropArray.curve_fit">curve_fit() (impy.arrays.specials.PropArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.PropArray.curve_fit">curve_fit() (impy.arrays.PropArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.specials.PropArray.curve_fit">(impy.arrays.specials.PropArray method)</a>
 </li>
+      </ul></li>
   </ul></td>
 </tr></table>
 
@@ -408,44 +597,92 @@ <h2 id="D">D</h2>
 </li>
       <li><a href="apidoc/impy.html#impy.collections.DataList">DataList (class in impy.collections)</a>
 </li>
-      <li><a href="apidoc/impy.html#impy.random.default_rng">default_rng() (in module impy.random)</a>
+      <li><a href="apidoc/impy.lazy.html#impy.lazy.random.default_rng">default_rng() (in module impy.lazy.random)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.html#impy.random.default_rng">(in module impy.random)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.deg2rad">deg2rad() (impy.arrays.phasearray.PhaseArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.PhaseArray.deg2rad">deg2rad() (impy.arrays.PhaseArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.deg2rad">(impy.arrays.phasearray.PhaseArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.delete_label">delete_label() (impy.arrays.label.Label method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.Label.delete_label">delete_label() (impy.arrays.Label method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.delete_label">(impy.arrays.label.Label method)</a>
+</li>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.tiled.TiledImage.depth">depth (impy.arrays.tiled.TiledImage property)</a>
 </li>
       <li><a href="apidoc/impy.utils.html#impy.utils.gauss.diagonal_gaussian">diagonal_gaussian() (in module impy.utils.gauss)</a>
 </li>
       <li><a href="apidoc/impy.utils.html#impy.utils.gauss.DiagonalGaussian">DiagonalGaussian (class in impy.utils.gauss)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.diameter_closing">diameter_closing() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.diameter_closing">diameter_closing() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.diameter_closing">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.diameter_opening">diameter_opening() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.diameter_opening">diameter_opening() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.diameter_opening">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.dilation">dilation() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.dilation">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.dilation">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.dilation">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.dilation">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.dilation">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="apidoc/impy.utils.html#impy.utils.deco.dims_to_spatial_axes">dims_to_spatial_axes() (in module impy.utils.deco)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.distance_map">distance_map() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.distance_map">distance_map() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.distance_map">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.dog_filter">dog_filter() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.dog_filter">dog_filter() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.dog_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.doh_filter">doh_filter() (impy.arrays.imgarray.ImgArray method)</a>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.tiled.TiledImage.dog_filter">(impy.arrays.tiled.TiledImage method)</a>
 </li>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.doh_filter">doh_filter() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.doh_filter">(impy.arrays.imgarray.ImgArray method)</a>
+</li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.drift_correction">drift_correction() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.drift_correction">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.drift_correction">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.drift_correction">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.drift_correction">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.drift_correction">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.html#impy.roi.Roi.drop">drop() (impy.roi.Roi method)</a>
@@ -454,9 +691,13 @@ <h2 id="D">D</h2>
         <li><a href="apidoc/impy.html#impy.roi.RoiList.drop">(impy.roi.RoiList method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.dtype">dtype (impy.arrays.lazy.LazyImgArray property)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.axesmixin.AxesMixin.dtype">dtype (impy.arrays.axesmixin.AxesMixin attribute)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.dtype">(impy.arrays.lazy.LazyImgArray property)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.dtype">(impy.arrays.LazyImgArray property)</a>
+</li>
         <li><a href="apidoc/impy.viewer.html#impy.viewer.utils.ComplexArrayView.dtype">(impy.viewer.utils.ComplexArrayView property)</a>
 </li>
       </ul></li>
@@ -469,37 +710,77 @@ <h2 id="E">E</h2>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.edge_filter">edge_filter() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.edge_filter">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.edge_filter">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.edge_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.edge_filter">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.edge_filter">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.edge_grad">edge_grad() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.edge_grad">edge_grad() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.edge_grad">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.core.empty">empty() (in module impy.core)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.lazy.html#impy.lazy.core.empty">(in module impy.lazy.core)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.frame.html#impy.frame.frames.TrackFrame.emsd">emsd() (impy.frame.frames.TrackFrame method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.enhance_contrast">enhance_contrast() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.enhance_contrast">enhance_contrast() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.enhance_contrast">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.entropy_filter">entropy_filter() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.entropy_filter">entropy_filter() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.entropy_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.erosion">erosion() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.erosion">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.erosion">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.erosion">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.erosion">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.erosion">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.estimate_sigma">estimate_sigma() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.estimate_sigma">estimate_sigma() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.estimate_sigma">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.expand_labels">expand_labels() (impy.arrays.label.Label method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.Label.expand_labels">expand_labels() (impy.arrays.Label method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.expand_labels">(impy.arrays.label.Label method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.extract">extract() (impy.arrays.labeledarray.LabeledArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.extract">extract() (impy.arrays.LabeledArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.extract">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
+      </ul></li>
   </ul></td>
 </tr></table>
 
@@ -509,33 +790,67 @@ <h2 id="F">F</h2>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.fft">fft() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.fft">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.fft">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.fft">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.fft">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.fft">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.fill_hole">fill_hole() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.fill_hole">fill_hole() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.fill_hole">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.frame.html#impy.frame.frames.TrackFrame.filter_stubs">filter_stubs() (impy.frame.frames.TrackFrame method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.find_corners">find_corners() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.find_corners">find_corners() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.find_corners">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.utils.html#impy.utils.axesop.find_first_appeared">find_first_appeared() (in module impy.utils.axesop)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.find_sm">find_sm() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.find_sm">find_sm() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.find_sm">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.utils.html#impy.utils.gauss.DiagonalGaussian.fit">fit() (impy.utils.gauss.DiagonalGaussian method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.flood">flood() (impy.arrays.imgarray.ImgArray method)</a>
-</li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.focus_map">focus_map() (impy.arrays.imgarray.ImgArray method)</a>
-</li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.for_each_channel">for_each_channel() (impy.arrays.labeledarray.LabeledArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.flood">flood() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.flood">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.for_params">for_params() (impy.arrays.labeledarray.LabeledArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.focus_map">focus_map() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.focus_map">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.for_each_channel">for_each_channel() (impy.arrays.LabeledArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.for_each_channel">(impy.arrays.labeledarray.LabeledArray method)</a>
+</li>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.for_params">for_params() (impy.arrays.LabeledArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.for_params">(impy.arrays.labeledarray.LabeledArray method)</a>
+</li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.correlation.fourier_ncc">fourier_ncc() (in module impy.correlation)</a>
 </li>
       <li><a href="apidoc/impy.html#impy.correlation.fourier_shell_correlation">fourier_shell_correlation() (in module impy.correlation)</a>
@@ -557,44 +872,80 @@ <h2 id="F">F</h2>
       <li><a href="apidoc/impy.html#impy.correlation.ft_pcc_maximum_with_corr">ft_pcc_maximum_with_corr() (in module impy.correlation)</a>
 </li>
       <li><a href="apidoc/impy.html#impy.core.full">full() (in module impy.core)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.lazy.html#impy.lazy.core.full">(in module impy.lazy.core)</a>
 </li>
+      </ul></li>
   </ul></td>
 </tr></table>
 
 <h2 id="G">G</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.gabor_angle">gabor_angle() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.gabor_angle">gabor_angle() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.gabor_angle">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.gabor_filter">gabor_filter() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.gabor_filter">gabor_filter() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.gabor_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.gauss_correction">gauss_correction() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.gauss_correction">gauss_correction() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.gauss_correction">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.gauss_sm">gauss_sm() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.gauss_sm">gauss_sm() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.gauss_sm">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.gaussfit">gaussfit() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.gaussfit">gaussfit() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.gaussfit">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.utils.html#impy.utils.gauss.Gaussian">Gaussian (class in impy.utils.gauss)</a>
 </li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.gaussian_filter">gaussian_filter() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.gaussian_filter">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.gaussian_filter">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.gaussian_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.gaussian_filter">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.gaussian_filter">(impy.arrays.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.tiled.TiledImage.gaussian_filter">(impy.arrays.tiled.TiledImage method)</a>
 </li>
       </ul></li>
+  </ul></td>
+  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="apidoc/impy.html#impy.core.gaussian_kernel">gaussian_kernel() (in module impy.core)</a>
 </li>
       <li><a href="apidoc/impy.utils.html#impy.utils.gauss.GaussianBackground">GaussianBackground (class in impy.utils.gauss)</a>
 </li>
       <li><a href="apidoc/impy.utils.html#impy.utils.gauss.GaussianParticle">GaussianParticle (class in impy.utils.gauss)</a>
 </li>
-  </ul></td>
-  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.GB">GB (impy.arrays.lazy.LazyImgArray property)</a>
 </li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.gb">gb (impy.arrays.lazy.LazyImgArray property)</a>
+</li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.GB">GB (impy.arrays.LazyImgArray property)</a>
+</li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.gb">gb (impy.arrays.LazyImgArray property)</a>
 </li>
       <li><a href="apidoc/impy.utils.html#impy.utils.gauss.DiagonalGaussian.generate">generate() (impy.utils.gauss.DiagonalGaussian method)</a>
 </li>
@@ -614,8 +965,12 @@ <h2 id="G">G</h2>
 </li>
       <li><a href="apidoc/impy.viewer.html#impy.viewer.utils.get_viewer_scale">get_viewer_scale() (in module impy.viewer.utils)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.glcm_props">glcm_props() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.glcm_props">glcm_props() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.glcm_props">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.viewer.html#impy.viewer.viewer.napariViewers.goto">goto() (impy.viewer.viewer.napariViewers method)</a>
 </li>
   </ul></td>
@@ -624,19 +979,39 @@ <h2 id="G">G</h2>
 <h2 id="H">H</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.hessian_angle">hessian_angle() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.hessian_angle">hessian_angle() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.hessian_angle">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.hessian_eig">hessian_eig() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.hessian_eig">hessian_eig() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.hessian_eig">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.hessian_eigval">hessian_eigval() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.hessian_eigval">hessian_eigval() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.hessian_eigval">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.highpass_filter">highpass_filter() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.highpass_filter">highpass_filter() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.highpass_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.hist">hist() (impy.arrays.labeledarray.LabeledArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.hist">hist() (impy.arrays.LabeledArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.hist">(impy.arrays.labeledarray.LabeledArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.PropArray.hist">(impy.arrays.PropArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.specials.PropArray.hist">(impy.arrays.specials.PropArray method)</a>
 </li>
       </ul></li>
@@ -649,15 +1024,29 @@ <h2 id="I">I</h2>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.ifft">ifft() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.ifft">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.ifft">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.ifft">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.ifft">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.ifft">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.html#impy.random.ImageGenerator">ImageGenerator (class in impy.random)</a>
+      <li><a href="apidoc/impy.lazy.html#impy.lazy.random.ImageGenerator">ImageGenerator (class in impy.lazy.random)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.html#impy.random.ImageGenerator">(class in impy.random)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray">ImgArray (class in impy.arrays.imgarray)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray">ImgArray (class in impy.arrays)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray">(class in impy.arrays.imgarray)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.implements">implements() (impy.arrays.bases.metaarray.MetaArray class method)</a>
 </li>
       <li><a href="apidoc/impy.utils.html#impy.utils.utilcls.ImportOnRequest">ImportOnRequest (class in impy.utils.utilcls)</a>
@@ -758,6 +1147,13 @@ <h2 id="I">I</h2>
 
       <ul>
         <li><a href="apidoc/impy.arrays.html#module-impy.arrays.specials">module</a>
+</li>
+      </ul></li>
+      <li>
+    impy.arrays.tiled
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#module-impy.arrays.tiled">module</a>
 </li>
       </ul></li>
       <li>
@@ -814,6 +1210,27 @@ <h2 id="I">I</h2>
 
       <ul>
         <li><a href="apidoc/impy.html#module-impy.io">module</a>
+</li>
+      </ul></li>
+      <li>
+    impy.lazy
+
+      <ul>
+        <li><a href="apidoc/impy.lazy.html#module-impy.lazy">module</a>
+</li>
+      </ul></li>
+      <li>
+    impy.lazy.core
+
+      <ul>
+        <li><a href="apidoc/impy.lazy.html#module-impy.lazy.core">module</a>
+</li>
+      </ul></li>
+      <li>
+    impy.lazy.random
+
+      <ul>
+        <li><a href="apidoc/impy.lazy.html#module-impy.lazy.random">module</a>
 </li>
       </ul></li>
   </ul></td>
@@ -906,54 +1323,90 @@ <h2 id="I">I</h2>
 
       <ul>
         <li><a href="apidoc/impy.html#impy.io.imread">(in module impy.io)</a>
+</li>
+        <li><a href="apidoc/impy.lazy.html#impy.lazy.core.imread">(in module impy.lazy.core)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.html#impy.core.imread_collection">imread_collection() (in module impy.core)</a>
 </li>
       <li><a href="apidoc/impy.html#impy.io.imread_dask">imread_dask() (in module impy.io)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.imsave">imsave() (impy.arrays.labeledarray.LabeledArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.imsave">imsave() (impy.arrays.LabeledArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.imsave">(impy.arrays.labeledarray.LabeledArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.imsave">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.imsave">(impy.arrays.LazyImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.html#impy.io.imsave">(in module impy.io)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.frame.html#impy.frame.frames.TrackFrame.imsd">imsd() (impy.frame.frames.TrackFrame method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.imshow">imshow() (impy.arrays.label.Label method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.Label.imshow">imshow() (impy.arrays.Label method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.imshow">(impy.arrays.label.Label method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.imshow">(impy.arrays.LabeledArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.imshow">(impy.arrays.labeledarray.LabeledArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.PhaseArray.imshow">(impy.arrays.PhaseArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.imshow">(impy.arrays.phasearray.PhaseArray method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.increment">increment() (impy.arrays.label.Label method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.Label.increment">increment() (impy.arrays.Label method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.increment">(impy.arrays.label.Label method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.increment_iter">increment_iter() (impy.arrays.label.Label method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.Label.increment_iter">increment_iter() (impy.arrays.Label method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.increment_iter">(impy.arrays.label.Label method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.core.indices">indices() (in module impy.core)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.lazy.html#impy.lazy.core.indices">(in module impy.lazy.core)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.inpaint">inpaint() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.inpaint">inpaint() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.inpaint">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.collections.DataList.insert">insert() (impy.collections.DataList method)</a>
 
       <ul>
         <li><a href="apidoc/impy.html#impy.roi.RoiList.insert">(impy.roi.RoiList method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.iradon">iradon() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.iradon">iradon() (impy.arrays.ImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.iradon">(impy.arrays.imgarray.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.iradon">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.iradon">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.isel">isel() (impy.arrays.bases.metaarray.MetaArray method)</a>
 </li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.itemsize">itemsize (impy.arrays.lazy.LazyImgArray property)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.itemsize">(impy.arrays.LazyImgArray property)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.axesmixin.AxesMixin.iter">iter() (impy.arrays.axesmixin.AxesMixin method)</a>
 
       <ul>
@@ -975,9 +1428,15 @@ <h2 id="K">K</h2>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.kalman_filter">kalman_filter() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.kalman_filter">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.kalman_filter">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.kalman_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.kalman_filter">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.kalman_filter">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
   </ul></td>
@@ -986,24 +1445,54 @@ <h2 id="K">K</h2>
 <h2 id="L">L</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label">Label (class in impy.arrays.label)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.Label">Label (class in impy.arrays)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label">(class in impy.arrays.label)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.label">label() (impy.arrays.labeledarray.LabeledArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.label">label() (impy.arrays.LabeledArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.label">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.label_if">label_if() (impy.arrays.labeledarray.LabeledArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.label_if">label_if() (impy.arrays.LabeledArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.label_if">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.label_threshold">label_threshold() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.label_threshold">label_threshold() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.label_threshold">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray">LabeledArray (class in impy.arrays.labeledarray)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray">LabeledArray (class in impy.arrays)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray">(class in impy.arrays.labeledarray)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.labels">labels (impy.arrays.labeledarray.LabeledArray property)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.labels">labels (impy.arrays.LabeledArray property)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.labels">(impy.arrays.labeledarray.LabeledArray property)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.laplacian_filter">laplacian_filter() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.laplacian_filter">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.laplacian_filter">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.laplacian_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.laplacian_filter">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.laplacian_filter">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.utils.html#impy.utils.misc.largest_zeros">largest_zeros() (in module impy.utils.misc)</a>
@@ -1016,38 +1505,82 @@ <h2 id="L">L</h2>
 </li>
       <li><a href="apidoc/impy.html#impy.core.lazy_imread">lazy_imread() (in module impy.core)</a>
 </li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray">LazyImgArray (class in impy.arrays)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray">(class in impy.arrays.lazy)</a>
+</li>
+      </ul></li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray">LazyImgArray (class in impy.arrays.lazy)</a>
-</li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.lbp">lbp() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.lbp">lbp() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.lbp">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.frame.html#impy.frame.frames.PathFrame.length">length() (impy.frame.frames.PathFrame method)</a>
 </li>
       <li><a href="apidoc/impy.html#impy.roi.LineRoi">LineRoi (class in impy.roi)</a>
 </li>
       <li><a href="apidoc/impy.frame.html#impy.frame.frames.MarkerFrame.link">link() (impy.frame.frames.MarkerFrame method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.local_dft">local_dft() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.local_dft">local_dft() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.local_dft">(impy.arrays.imgarray.ImgArray method)</a>
+</li>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.local_power_spectra">local_power_spectra() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.local_power_spectra">(impy.arrays.imgarray.ImgArray method)</a>
+</li>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.log_filter">log_filter() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.log_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.local_power_spectra">local_power_spectra() (impy.arrays.imgarray.ImgArray method)</a>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.tiled.TiledImage.log_filter">(impy.arrays.tiled.TiledImage method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.log_filter">log_filter() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.lowpass_conv_filter">lowpass_conv_filter() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.lowpass_conv_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.lowpass_conv_filter">lowpass_conv_filter() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.lowpass_filter">lowpass_filter() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.lowpass_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.lowpass_filter">lowpass_filter() (impy.arrays.imgarray.ImgArray method)</a>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.tiled.TiledImage.lowpass_filter">(impy.arrays.tiled.TiledImage method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.lucy">lucy() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.lucy">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.lucy">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.lucy">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.lucy">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.lucy">(impy.arrays.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.tiled.TiledImage.lucy">(impy.arrays.tiled.TiledImage method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.lucy_tv">lucy_tv() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.lucy_tv">lucy_tv() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.lucy_tv">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
   </ul></td>
 </tr></table>
 
@@ -1058,9 +1591,13 @@ <h2 id="M">M</h2>
 </li>
       <li><a href="apidoc/impy.html#impy.correlation.manders_coloc">manders_coloc() (in module impy.correlation)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.map_coordinates">map_coordinates() (impy.arrays.labeledarray.LabeledArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.map_coordinates">map_coordinates() (impy.arrays.LabeledArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.map_coordinates">(impy.arrays.labeledarray.LabeledArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.PhaseArray.map_coordinates">(impy.arrays.PhaseArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.map_coordinates">(impy.arrays.phasearray.PhaseArray method)</a>
 </li>
       </ul></li>
@@ -1076,20 +1613,32 @@ <h2 id="M">M</h2>
 
       <ul>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.max">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.max">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.mean">mean() (impy.arrays.bases.metaarray.MetaArray method)</a>
 
       <ul>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.mean">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.mean">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.mean_filter">mean_filter() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.mean_filter">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.mean_filter">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.mean_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.mean_filter">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.mean_filter">(impy.arrays.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.PhaseArray.mean_filter">(impy.arrays.PhaseArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.mean_filter">(impy.arrays.phasearray.PhaseArray method)</a>
 </li>
@@ -1097,9 +1646,15 @@ <h2 id="M">M</h2>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.median_filter">median_filter() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.median_filter">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.median_filter">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.median_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.median_filter">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.median_filter">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray">MetaArray (class in impy.arrays.bases.metaarray)</a>
@@ -1108,16 +1663,22 @@ <h2 id="M">M</h2>
 
       <ul>
         <li><a href="apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.metadata">(impy.arrays.bases.metaarray.MetaArray property)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.metadata">(impy.arrays.ImgArray attribute)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.metadata">(impy.arrays.imgarray.ImgArray attribute)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.metadata">(impy.arrays.lazy.LazyImgArray property)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.metadata">(impy.arrays.LazyImgArray property)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.min">min() (impy.arrays.bases.metaarray.MetaArray method)</a>
 
       <ul>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.min">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.min">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
       <li>
@@ -1151,6 +1712,8 @@ <h2 id="M">M</h2>
         <li><a href="apidoc/impy.arrays.html#module-impy.arrays.phasearray">impy.arrays.phasearray</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#module-impy.arrays.specials">impy.arrays.specials</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#module-impy.arrays.tiled">impy.arrays.tiled</a>
 </li>
         <li><a href="apidoc/impy.axes.html#module-impy.axes">impy.axes</a>
 </li>
@@ -1167,6 +1730,12 @@ <h2 id="M">M</h2>
         <li><a href="apidoc/impy.frame.html#module-impy.frame.frames">impy.frame.frames</a>
 </li>
         <li><a href="apidoc/impy.html#module-impy.io">impy.io</a>
+</li>
+        <li><a href="apidoc/impy.lazy.html#module-impy.lazy">impy.lazy</a>
+</li>
+        <li><a href="apidoc/impy.lazy.html#module-impy.lazy.core">impy.lazy.core</a>
+</li>
+        <li><a href="apidoc/impy.lazy.html#module-impy.lazy.random">impy.lazy.random</a>
 </li>
         <li><a href="apidoc/impy.html#module-impy.random">impy.random</a>
 </li>
@@ -1213,6 +1782,8 @@ <h2 id="N">N</h2>
 
       <ul>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.name">(impy.arrays.lazy.LazyImgArray property)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.name">(impy.arrays.LazyImgArray property)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.viewer.html#impy.viewer.viewer.napariViewers">napariViewers (class in impy.viewer.viewer)</a>
@@ -1221,12 +1792,18 @@ <h2 id="N">N</h2>
 </li>
       <li><a href="apidoc/impy.html#impy.correlation.ncc">ncc() (in module impy.correlation)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.ncc_filter">ncc_filter() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.ncc_filter">ncc_filter() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.ncc_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.axesmixin.AxesMixin.ndim">ndim (impy.arrays.axesmixin.AxesMixin attribute)</a>
 
       <ul>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.ndim">(impy.arrays.lazy.LazyImgArray property)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.ndim">(impy.arrays.LazyImgArray property)</a>
 </li>
         <li><a href="apidoc/impy.html#impy.roi.Roi.ndim">(impy.roi.Roi property)</a>
 </li>
@@ -1239,9 +1816,13 @@ <h2 id="N">N</h2>
   <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="apidoc/impy.html#impy.correlation.nmi">nmi() (in module impy.correlation)</a>
 </li>
-      <li><a href="apidoc/impy.html#impy.random.ImageGenerator.normal">normal() (impy.random.ImageGenerator method)</a>
+      <li><a href="apidoc/impy.lazy.html#impy.lazy.random.ImageGenerator.normal">normal() (impy.lazy.random.ImageGenerator method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.html#impy.random.ImageGenerator.normal">(impy.random.ImageGenerator method)</a>
+</li>
+        <li><a href="apidoc/impy.lazy.html#impy.lazy.random.normal">(in module impy.lazy.random)</a>
+</li>
         <li><a href="apidoc/impy.html#impy.random.normal">(in module impy.random)</a>
 </li>
       </ul></li>
@@ -1258,73 +1839,123 @@ <h2 id="O">O</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="apidoc/impy.html#impy.core.ones">ones() (in module impy.core)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.lazy.html#impy.lazy.core.ones">(in module impy.lazy.core)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.opening">opening() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.opening">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.opening">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.opening">(impy.arrays.imgarray.ImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.Label.opening">(impy.arrays.Label method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.opening">(impy.arrays.label.Label method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.opening">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.opening">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.optimize">optimize() (impy.arrays.label.Label method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.Label.optimize">optimize() (impy.arrays.Label method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.optimize">(impy.arrays.label.Label method)</a>
 </li>
+      </ul></li>
   </ul></td>
 </tr></table>
 
 <h2 id="P">P</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.pad">pad() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.pad">pad() (impy.arrays.ImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.pad">(impy.arrays.imgarray.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.pad">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.pad">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.pad_defocus">pad_defocus() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.pad_defocus">pad_defocus() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.pad_defocus">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.utils.html#impy.utils.gauss.DiagonalGaussian.params">params (impy.utils.gauss.DiagonalGaussian property)</a>
 </li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.ArrayCovariates.parent">parent (impy.arrays.labeledarray.ArrayCovariates property)</a>
 </li>
       <li><a href="apidoc/impy.frame.html#impy.frame.frames.PathFrame">PathFrame (class in impy.frame.frames)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.pathprops">pathprops() (impy.arrays.labeledarray.LabeledArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.pathprops">pathprops() (impy.arrays.LabeledArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.pathprops">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.correlation.pcc_landscape">pcc_landscape() (in module impy.correlation)</a>
 </li>
       <li><a href="apidoc/impy.html#impy.correlation.pcc_maximum">pcc_maximum() (in module impy.correlation)</a>
 </li>
       <li><a href="apidoc/impy.html#impy.correlation.pcc_maximum_with_corr">pcc_maximum_with_corr() (in module impy.correlation)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.peak_local_max">peak_local_max() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.peak_local_max">peak_local_max() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.peak_local_max">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.correlation.pearson_coloc">pearson_coloc() (in module impy.correlation)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.periodicity">periodicity (impy.arrays.phasearray.PhaseArray property)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.PhaseArray.periodicity">periodicity (impy.arrays.PhaseArray property)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.periodicity">(impy.arrays.phasearray.PhaseArray property)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray">PhaseArray (class in impy.arrays.phasearray)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.PhaseArray">PhaseArray (class in impy.arrays)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray">(class in impy.arrays.phasearray)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.specials.PropArray.plot">plot() (impy.arrays.specials.PropArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.PropArray.plot">plot() (impy.arrays.PropArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.specials.PropArray.plot">(impy.arrays.specials.PropArray method)</a>
+</li>
         <li><a href="apidoc/impy.html#impy.roi.Roi.plot">(impy.roi.Roi method)</a>
 </li>
         <li><a href="apidoc/impy.html#impy.roi.RoiList.plot">(impy.roi.RoiList method)</a>
+</li>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.pointprops">pointprops() (impy.arrays.LabeledArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.pointprops">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
       </ul></li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.pointprops">pointprops() (impy.arrays.labeledarray.LabeledArray method)</a>
-</li>
       <li><a href="apidoc/impy.html#impy.roi.PointRoi">PointRoi (class in impy.roi)</a>
 </li>
-      <li><a href="apidoc/impy.html#impy.random.ImageGenerator.poisson">poisson() (impy.random.ImageGenerator method)</a>
+      <li><a href="apidoc/impy.lazy.html#impy.lazy.random.ImageGenerator.poisson">poisson() (impy.lazy.random.ImageGenerator method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.html#impy.random.ImageGenerator.poisson">(impy.random.ImageGenerator method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.correlation.polar_pcc_maximum">polar_pcc_maximum() (in module impy.correlation)</a>
 </li>
       <li><a href="apidoc/impy.html#impy.correlation.polar_pcc_maximum_with_corr">polar_pcc_maximum_with_corr() (in module impy.correlation)</a>
@@ -1336,127 +1967,249 @@ <h2 id="P">P</h2>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.power_spectra">power_spectra() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.power_spectra">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.power_spectra">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.power_spectra">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.power_spectra">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.power_spectra">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.proj">proj() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.proj">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.proj">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.proj">(impy.arrays.imgarray.ImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.Label.proj">(impy.arrays.Label method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.proj">(impy.arrays.label.Label method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.proj">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.proj">(impy.arrays.LazyImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.frame.html#impy.frame.frames.AxesFrame.proj">(impy.frame.frames.AxesFrame method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.proj_labels">proj_labels() (impy.arrays.labeledarray.LabeledArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.proj_labels">proj_labels() (impy.arrays.LabeledArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.proj_labels">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.specials.PropArray">PropArray (class in impy.arrays.specials)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.PropArray">PropArray (class in impy.arrays)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.specials.PropArray">(class in impy.arrays.specials)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.specials.PropArray.propname">propname (impy.arrays.specials.PropArray attribute)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.PropArray.propname">propname (impy.arrays.PropArray attribute)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.specials.PropArray.propname">(impy.arrays.specials.PropArray attribute)</a>
 </li>
+      </ul></li>
   </ul></td>
 </tr></table>
 
 <h2 id="R">R</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.rad2deg">rad2deg() (impy.arrays.phasearray.PhaseArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.PhaseArray.rad2deg">rad2deg() (impy.arrays.PhaseArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.rad2deg">(impy.arrays.phasearray.PhaseArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.radial_profile">radial_profile() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.radial_profile">radial_profile() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.radial_profile">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.radon">radon() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.radon">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.radon">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.radon">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.radon">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.radon">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.html#impy.random.ImageGenerator.random">random() (impy.random.ImageGenerator method)</a>
+      <li><a href="apidoc/impy.lazy.html#impy.lazy.random.ImageGenerator.random">random() (impy.lazy.random.ImageGenerator method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.html#impy.random.ImageGenerator.random">(impy.random.ImageGenerator method)</a>
+</li>
+        <li><a href="apidoc/impy.lazy.html#impy.lazy.random.random">(in module impy.lazy.random)</a>
+</li>
         <li><a href="apidoc/impy.html#impy.random.random">(in module impy.random)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.html#impy.random.ImageGenerator.random_uint16">random_uint16() (impy.random.ImageGenerator method)</a>
+      <li><a href="apidoc/impy.lazy.html#impy.lazy.random.ImageGenerator.random_uint16">random_uint16() (impy.lazy.random.ImageGenerator method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.html#impy.random.ImageGenerator.random_uint16">(impy.random.ImageGenerator method)</a>
+</li>
+        <li><a href="apidoc/impy.lazy.html#impy.lazy.random.random_uint16">(in module impy.lazy.random)</a>
+</li>
         <li><a href="apidoc/impy.html#impy.random.random_uint16">(in module impy.random)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.html#impy.random.ImageGenerator.random_uint8">random_uint8() (impy.random.ImageGenerator method)</a>
+      <li><a href="apidoc/impy.lazy.html#impy.lazy.random.ImageGenerator.random_uint8">random_uint8() (impy.lazy.random.ImageGenerator method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.html#impy.random.ImageGenerator.random_uint8">(impy.random.ImageGenerator method)</a>
+</li>
+        <li><a href="apidoc/impy.lazy.html#impy.lazy.random.random_uint8">(in module impy.lazy.random)</a>
+</li>
         <li><a href="apidoc/impy.html#impy.random.random_uint8">(in module impy.random)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.random_walker">random_walker() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.random_walker">random_walker() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.random_walker">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.range">range (impy.arrays.labeledarray.LabeledArray property)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.range">range (impy.arrays.LabeledArray property)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.range">(impy.arrays.labeledarray.LabeledArray property)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.core.read_meta">read_meta() (in module impy.core)</a>
 </li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.rechunk">rechunk() (impy.arrays.lazy.LazyImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.rechunk">(impy.arrays.LazyImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.roi.RectangleRoi">RectangleRoi (class in impy.roi)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.regionprops">regionprops() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.regionprops">regionprops() (impy.arrays.ImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.regionprops">(impy.arrays.imgarray.ImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.PhaseArray.regionprops">(impy.arrays.PhaseArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.regionprops">(impy.arrays.phasearray.PhaseArray method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.relabel">relabel() (impy.arrays.label.Label method)</a>
-</li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.Label.relabel">relabel() (impy.arrays.Label method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.label.Label.relabel">(impy.arrays.label.Label method)</a>
+</li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.release">release() (impy.arrays.lazy.LazyImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.release">(impy.arrays.LazyImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.remove_edges">remove_edges() (impy.arrays.labeledarray.LabeledArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.remove_edges">remove_edges() (impy.arrays.LabeledArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.remove_edges">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.remove_fine_objects">remove_fine_objects() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.remove_fine_objects">remove_fine_objects() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.remove_fine_objects">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.remove_large_objects">remove_large_objects() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.remove_large_objects">remove_large_objects() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.remove_large_objects">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.remove_skeleton_structure">remove_skeleton_structure() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.remove_skeleton_structure">remove_skeleton_structure() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.remove_skeleton_structure">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.rescale">rescale() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.rescale">rescale() (impy.arrays.ImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.rescale">(impy.arrays.imgarray.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.utils.html#impy.utils.gauss.DiagonalGaussian.rescale">(impy.utils.gauss.DiagonalGaussian method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.rescale_intensity">rescale_intensity() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.rescale_intensity">rescale_intensity() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.rescale_intensity">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.reshape">reshape() (impy.arrays.bases.metaarray.MetaArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.reslice">reslice() (impy.arrays.labeledarray.LabeledArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.reslice">reslice() (impy.arrays.LabeledArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.reslice">(impy.arrays.labeledarray.LabeledArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.PhaseArray.reslice">(impy.arrays.PhaseArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.reslice">(impy.arrays.phasearray.PhaseArray method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.rof_filter">rof_filter() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.rof_filter">rof_filter() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.rof_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.roi.Roi">Roi (class in impy.roi)</a>
 </li>
       <li><a href="apidoc/impy.html#impy.roi.RoiList">RoiList (class in impy.roi)</a>
 </li>
       <li><a href="apidoc/impy.html#impy.core.roiread">roiread() (in module impy.core)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.rois">rois (impy.arrays.labeledarray.LabeledArray property)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.rois">rois (impy.arrays.LabeledArray property)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.rois">(impy.arrays.labeledarray.LabeledArray property)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.rolling_ball">rolling_ball() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.rolling_ball">rolling_ball() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.rolling_ball">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.rotate">rotate() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.rotate">rotate() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.rotate">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.rotated_crop">rotated_crop() (impy.arrays.labeledarray.LabeledArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.rotated_crop">rotated_crop() (impy.arrays.LabeledArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.rotated_crop">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
+      </ul></li>
   </ul></td>
 </tr></table>
 
@@ -1472,6 +2225,8 @@ <h2 id="S">S</h2>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.axesmixin.AxesMixin.scale">scale (impy.arrays.axesmixin.AxesMixin property)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.scale">(impy.arrays.ImgArray attribute)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.scale">(impy.arrays.imgarray.ImgArray attribute)</a>
 </li>
         <li><a href="apidoc/impy.frame.html#impy.frame.frames.AxesFrame.scale">(impy.frame.frames.AxesFrame property)</a>
@@ -1491,11 +2246,17 @@ <h2 id="S">S</h2>
 </li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.axesmixin.AxesMixin.set_axis_label">set_axis_label() (impy.arrays.axesmixin.AxesMixin method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.set_border">set_border() (impy.arrays.phasearray.PhaseArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.PhaseArray.set_border">set_border() (impy.arrays.PhaseArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.set_border">(impy.arrays.phasearray.PhaseArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.axesmixin.AxesMixin.set_scale">set_scale() (impy.arrays.axesmixin.AxesMixin method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.set_scale">(impy.arrays.LabeledArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.set_scale">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
         <li><a href="apidoc/impy.frame.html#impy.frame.frames.AxesFrame.set_scale">(impy.frame.frames.AxesFrame method)</a>
@@ -1515,6 +2276,8 @@ <h2 id="S">S</h2>
         <li><a href="apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.shape">(impy.arrays.bases.metaarray.MetaArray property)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.shape">(impy.arrays.lazy.LazyImgArray property)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.shape">(impy.arrays.LazyImgArray property)</a>
 </li>
         <li><a href="apidoc/impy.viewer.html#impy.viewer.utils.ComplexArrayView.shape">(impy.viewer.utils.ComplexArrayView property)</a>
 </li>
@@ -1524,19 +2287,29 @@ <h2 id="S">S</h2>
       <li><a href="apidoc/impy.utils.html#impy.utils.gauss.DiagonalGaussian.shift">shift() (impy.utils.gauss.DiagonalGaussian method)</a>
 </li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.size">size (impy.arrays.lazy.LazyImgArray property)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.size">(impy.arrays.LazyImgArray property)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.axesmixin.AxesMixin.sizeof">sizeof() (impy.arrays.axesmixin.AxesMixin method)</a>
 </li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.axesmixin.AxesMixin.sizesof">sizesof() (impy.arrays.axesmixin.AxesMixin method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.skeletonize">skeletonize() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.skeletonize">skeletonize() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.skeletonize">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.utils.html#impy.utils.axesop.slice_axes">slice_axes() (in module impy.utils.axesop)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.smooth_mask">smooth_mask() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.smooth_mask">smooth_mask() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.smooth_mask">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-  </ul></td>
-  <td style="width: 33%; vertical-align: top;"><ul>
+      </ul></li>
       <li><a href="apidoc/impy.utils.html#impy.utils.slicer.solve_slicer">solve_slicer() (in module impy.utils.slicer)</a>
 </li>
       <li><a href="apidoc/impy.frame.html#impy.frame.frames.AxesFrame.sort">sort() (impy.frame.frames.AxesFrame method)</a>
@@ -1545,70 +2318,126 @@ <h2 id="S">S</h2>
 
       <ul>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.sort_axes">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.sort_axes">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
+  </ul></td>
+  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.source">source (impy.arrays.bases.metaarray.MetaArray property)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.source">(impy.arrays.ImgArray attribute)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.source">(impy.arrays.imgarray.ImgArray attribute)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.source">(impy.arrays.lazy.LazyImgArray property)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.source">(impy.arrays.LazyImgArray property)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.axesmixin.AxesMixin.spatial_shape">spatial_shape (impy.arrays.axesmixin.AxesMixin property)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.specify">specify() (impy.arrays.labeledarray.LabeledArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.specify">specify() (impy.arrays.LabeledArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.specify">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.spline_filter">spline_filter() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.spline_filter">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.spline_filter">(impy.arrays.LabeledArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.spline_filter">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.spline_filter">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.spline_filter">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.split">split() (impy.arrays.bases.metaarray.MetaArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.split">(impy.arrays.LabeledArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.split">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
         <li><a href="apidoc/impy.frame.html#impy.frame.frames.AxesFrame.split">(impy.frame.frames.AxesFrame method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.split_pixel_unit">split_pixel_unit() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.split_pixel_unit">split_pixel_unit() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.split_pixel_unit">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.utils.html#impy.utils.gauss.square">square() (in module impy.utils.gauss)</a>
 </li>
-      <li><a href="apidoc/impy.html#impy.random.ImageGenerator.standard_exponential">standard_exponential() (impy.random.ImageGenerator method)</a>
+      <li><a href="apidoc/impy.lazy.html#impy.lazy.random.ImageGenerator.standard_exponential">standard_exponential() (impy.lazy.random.ImageGenerator method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.html#impy.random.ImageGenerator.standard_exponential">(impy.random.ImageGenerator method)</a>
 </li>
-      <li><a href="apidoc/impy.html#impy.random.ImageGenerator.standard_normal">standard_normal() (impy.random.ImageGenerator method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.lazy.html#impy.lazy.random.ImageGenerator.standard_normal">standard_normal() (impy.lazy.random.ImageGenerator method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.html#impy.random.ImageGenerator.standard_normal">(impy.random.ImageGenerator method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.viewer.html#impy.viewer.viewer.napariViewers.start">start() (impy.viewer.viewer.napariViewers method)</a>
 </li>
       <li><a href="apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.std">std() (impy.arrays.bases.metaarray.MetaArray method)</a>
 
       <ul>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.std">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.std">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.std_filter">std_filter() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.std_filter">std_filter() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.std_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.viewer.html#impy.viewer.viewer.napariViewers.stepof">stepof() (impy.viewer.viewer.napariViewers method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.stokes">stokes() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.stokes">stokes() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.stokes">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.utils.html#impy.utils.slicer.str_to_slice">str_to_slice() (in module impy.utils.slicer)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.stretch">stretch() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.stretch">stretch() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.stretch">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.structure_tensor_eig">structure_tensor_eig() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.structure_tensor_eig">structure_tensor_eig() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.structure_tensor_eig">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.structure_tensor_eigval">structure_tensor_eigval() (impy.arrays.imgarray.ImgArray method)</a>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.structure_tensor_eigval">structure_tensor_eigval() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.structure_tensor_eigval">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.sum">sum() (impy.arrays.bases.metaarray.MetaArray method)</a>
 
       <ul>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.sum">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.sum">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.SupportAxesSlicing">SupportAxesSlicing (class in impy.arrays.labeledarray)</a>
@@ -1623,50 +2452,100 @@ <h2 id="T">T</h2>
   <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.T">T (impy.arrays.bases.metaarray.MetaArray property)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.threshold">threshold() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.threshold">threshold() (impy.arrays.ImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.threshold">(impy.arrays.imgarray.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.threshold">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.threshold">(impy.arrays.LazyImgArray method)</a>
+</li>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.LabeledArray.tile">tile() (impy.arrays.LabeledArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.tile">(impy.arrays.labeledarray.LabeledArray method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.labeledarray.LabeledArray.tile">tile() (impy.arrays.labeledarray.LabeledArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.tiled">tiled (impy.arrays.ImgArray attribute)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.tiled">(impy.arrays.imgarray.ImgArray attribute)</a>
 </li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.tiled">(impy.arrays.lazy.LazyImgArray attribute)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.tiled">(impy.arrays.LazyImgArray attribute)</a>
+</li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.tiled_lowpass_filter">tiled_lowpass_filter() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.tiled_lowpass_filter">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.tiled_lowpass_filter">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.tiled_lowpass_filter">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.tiled_lowpass_filter">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.tiled_lowpass_filter">(impy.arrays.LazyImgArray method)</a>
+</li>
+      </ul></li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.tiled_lucy">tiled_lucy() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.tiled_lucy">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
       </ul></li>
+  </ul></td>
+  <td style="width: 33%; vertical-align: top;"><ul>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.tiled.TiledAccessor">TiledAccessor (class in impy.arrays.tiled)</a>
+</li>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.tiled.TiledImage">TiledImage (class in impy.arrays.tiled)</a>
+</li>
       <li><a href="apidoc/impy.viewer.html#impy.viewer.utils.to_labels">to_labels() (in module impy.viewer.utils)</a>
 </li>
       <li><a href="apidoc/impy.html#impy.roi.RoiList.tofile">tofile() (impy.roi.RoiList method)</a>
 </li>
-  </ul></td>
-  <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.tophat">tophat() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.tophat">tophat() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.tophat">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.frame.html#impy.frame.frames.tp_no_verbose">tp_no_verbose() (in module impy.frame.frames)</a>
 </li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.track_drift">track_drift() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.track_drift">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.track_drift">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.track_drift">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.track_drift">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.track_drift">(impy.arrays.LazyImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.frame.html#impy.frame.frames.TrackFrame.track_drift">(impy.frame.frames.TrackFrame method)</a>
 </li>
       </ul></li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.track_template">track_template() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.track_template">track_template() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.track_template">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.frame.html#impy.frame.frames.TrackFrame">TrackFrame (class in impy.frame.frames)</a>
 </li>
       <li><a href="apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.transpose">transpose() (impy.arrays.bases.metaarray.MetaArray method)</a>
 
       <ul>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.transpose">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.transpose">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
   </ul></td>
@@ -1675,12 +2554,20 @@ <h2 id="T">T</h2>
 <h2 id="U">U</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.unit">unit (impy.arrays.phasearray.PhaseArray attribute)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.PhaseArray.unit">unit (impy.arrays.PhaseArray attribute)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.phasearray.PhaseArray.unit">(impy.arrays.phasearray.PhaseArray attribute)</a>
 </li>
+      </ul></li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.unmix">unmix() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.unmix">unmix() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.unmix">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
   </ul></td>
 </tr></table>
 
@@ -1692,9 +2579,7 @@ <h2 id="V">V</h2>
       <ul>
         <li><a href="apidoc/impy.arrays.bases.html#impy.arrays.bases.metaarray.MetaArray.value">(impy.arrays.bases.metaarray.MetaArray property)</a>
 </li>
-        <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.value">(impy.arrays.big.BigImgArray attribute)</a>
-</li>
-        <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.value">(impy.arrays.lazy.LazyImgArray attribute)</a>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.value">(impy.arrays.LazyImgArray attribute)</a>
 </li>
       </ul></li>
   </ul></td>
@@ -1703,30 +2588,48 @@ <h2 id="V">V</h2>
 </li>
       <li><a href="apidoc/impy.viewer.html#impy.viewer.utils.viewer_imread">viewer_imread() (in module impy.viewer.utils)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.voronoi">voronoi() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.voronoi">voronoi() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.voronoi">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
   </ul></td>
 </tr></table>
 
 <h2 id="W">W</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.watershed">watershed() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.watershed">watershed() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.watershed">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.wave_num">wave_num() (in module impy.arrays.imgarray)</a>
 </li>
-      <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.wavelet_denoising">wavelet_denoising() (impy.arrays.imgarray.ImgArray method)</a>
+      <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.wavelet_denoising">wavelet_denoising() (impy.arrays.ImgArray method)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.wavelet_denoising">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
-  </ul></td>
-  <td style="width: 33%; vertical-align: top;"><ul>
+      </ul></li>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.BigImgArray.wiener">wiener() (impy.arrays.big.BigImgArray method)</a>
 
       <ul>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.BigImgArray.wiener">(impy.arrays.BigImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.ImgArray.wiener">(impy.arrays.ImgArray method)</a>
+</li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.imgarray.ImgArray.wiener">(impy.arrays.imgarray.ImgArray method)</a>
 </li>
         <li><a href="apidoc/impy.arrays.html#impy.arrays.lazy.LazyImgArray.wiener">(impy.arrays.lazy.LazyImgArray method)</a>
+</li>
+        <li><a href="apidoc/impy.arrays.html#impy.arrays.LazyImgArray.wiener">(impy.arrays.LazyImgArray method)</a>
 </li>
       </ul></li>
+  </ul></td>
+  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="apidoc/impy.arrays.html#impy.arrays.big.wrap_method">wrap_method() (in module impy.arrays.big)</a>
 </li>
   </ul></td>
@@ -1744,7 +2647,11 @@ <h2 id="Z">Z</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="apidoc/impy.html#impy.core.zeros">zeros() (in module impy.core)</a>
+
+      <ul>
+        <li><a href="apidoc/impy.lazy.html#impy.lazy.core.zeros">(in module impy.lazy.core)</a>
 </li>
+      </ul></li>
       <li><a href="apidoc/impy.html#impy.correlation.zncc">zncc() (in module impy.correlation)</a>
 </li>
   </ul></td>
diff --git a/docs/index.html b/docs/index.html
index 1ea1faae..8c01bb37 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -1,10 +1,10 @@
 <!DOCTYPE html>
 <html class="writer-html5" lang="en" >
 <head>
-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
+  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>impy &mdash; impy 2.2.0 documentation</title>
+  <title>impy &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -12,9 +12,8 @@
   <![endif]-->
   
         <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
-        <script src="_static/jquery.js"></script>
-        <script src="_static/underscore.js"></script>
         <script src="_static/doctools.js"></script>
+        <script src="_static/sphinx_highlight.js"></script>
     <script src="_static/js/theme.js"></script>
     <link rel="index" title="Index" href="genindex.html" />
     <link rel="search" title="Search" href="search.html" />
@@ -26,14 +25,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="#" class="icon icon-home"> impy
+
+          
+          
+          <a href="#" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -60,8 +63,8 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="#" class="icon icon-home"></a> &raquo;</li>
-      <li>impy</li>
+      <li><a href="#" class="icon icon-home" aria-label="Home"></a></li>
+      <li class="breadcrumb-item active">impy</li>
       <li class="wy-breadcrumbs-aside">
             <a href="_sources/index.rst.txt" rel="nofollow"> View page source</a>
       </li>
@@ -72,12 +75,12 @@
            <div itemprop="articleBody">
              
   <section id="impy">
-<h1>impy<a class="headerlink" href="#impy" title="Permalink to this headline">¶</a></h1>
+<h1>impy<a class="headerlink" href="#impy" title="Permalink to this heading">¶</a></h1>
 <p><code class="docutils literal notranslate"><span class="pre">impy</span></code> is an all-in-one image analysis library, equipped with parallel processing, GPU support, GUI based tools and
 so on.</p>
 <p><a class="reference external" href="https://github.com/hanjinliu/impy">Source code</a></p>
 <section id="highlights">
-<h2>Highlights<a class="headerlink" href="#highlights" title="Permalink to this headline">¶</a></h2>
+<h2>Highlights<a class="headerlink" href="#highlights" title="Permalink to this heading">¶</a></h2>
 <ul class="simple">
 <li><p>Automatic parallel batch processing using <code class="docutils literal notranslate"><span class="pre">dask</span></code>.</p></li>
 <li><p>You don’t have to care about <code class="docutils literal notranslate"><span class="pre">numpy</span></code> / <code class="docutils literal notranslate"><span class="pre">scipy</span></code> on CPU, or <code class="docutils literal notranslate"><span class="pre">cupy</span></code> on GPU. Same code works for both processors.</p></li>
@@ -87,17 +90,17 @@ <h2>Highlights<a class="headerlink" href="#highlights" title="Permalink to this
 </ul>
 </section>
 <section id="installation">
-<h2>Installation<a class="headerlink" href="#installation" title="Permalink to this headline">¶</a></h2>
-<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>pip install git+https://github.com/hanjinliu/impy
+<h2>Installation<a class="headerlink" href="#installation" title="Permalink to this heading">¶</a></h2>
+<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>pip<span class="w"> </span>install<span class="w"> </span>git+https://github.com/hanjinliu/impy
 </pre></div>
 </div>
 <p>or</p>
-<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>git clone https://github.com/hanjinliu/impy
+<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>git<span class="w"> </span>clone<span class="w"> </span>https://github.com/hanjinliu/impy
 </pre></div>
 </div>
 </section>
 <section id="contents">
-<h2>Contents<a class="headerlink" href="#contents" title="Permalink to this headline">¶</a></h2>
+<h2>Contents<a class="headerlink" href="#contents" title="Permalink to this heading">¶</a></h2>
 <div class="toctree-wrapper compound">
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="tutorial.html">Tutorial</a></li>
@@ -109,9 +112,9 @@ <h2>Contents<a class="headerlink" href="#contents" title="Permalink to this head
 </div>
 </section>
 <section id="major-classes">
-<h2>Major Classes<a class="headerlink" href="#major-classes" title="Permalink to this headline">¶</a></h2>
+<h2>Major Classes<a class="headerlink" href="#major-classes" title="Permalink to this heading">¶</a></h2>
 <section id="array">
-<h3>Array<a class="headerlink" href="#array" title="Permalink to this headline">¶</a></h3>
+<h3>Array<a class="headerlink" href="#array" title="Permalink to this heading">¶</a></h3>
 <div class="align-default"><svg height="360" viewBox="0 0 832 360" width="832" xmlns="http://www.w3.org/2000/svg" xmlns:inkspace="http://www.inkscape.org/namespaces/inkscape" xmlns:xlink="http://www.w3.org/1999/xlink">
   <defs id="defs_block">
     <filter height="1.504" id="filter_blur" inkspace:collect="always" width="1.1575" x="-0.07875" y="-0.252">
@@ -177,7 +180,7 @@ <h3>Array<a class="headerlink" href="#array" title="Permalink to this headline">
 </ul>
 </section>
 <section id="array-like">
-<h3>Array-like<a class="headerlink" href="#array-like" title="Permalink to this headline">¶</a></h3>
+<h3>Array-like<a class="headerlink" href="#array-like" title="Permalink to this heading">¶</a></h3>
 <div class="align-default"><svg height="280" viewBox="0 0 256 280" width="256" xmlns="http://www.w3.org/2000/svg" xmlns:inkspace="http://www.inkscape.org/namespaces/inkscape" xmlns:xlink="http://www.w3.org/1999/xlink">
   <defs id="defs_block">
     <filter height="1.504" id="filter_blur" inkspace:collect="always" width="1.1575" x="-0.07875" y="-0.252">
@@ -207,7 +210,7 @@ <h3>Array-like<a class="headerlink" href="#array-like" title="Permalink to this
 </ul>
 </section>
 <section id="data-frame">
-<h3>Data Frame<a class="headerlink" href="#data-frame" title="Permalink to this headline">¶</a></h3>
+<h3>Data Frame<a class="headerlink" href="#data-frame" title="Permalink to this heading">¶</a></h3>
 <div class="align-default"><svg height="280" viewBox="0 0 640 280" width="640" xmlns="http://www.w3.org/2000/svg" xmlns:inkspace="http://www.inkscape.org/namespaces/inkscape" xmlns:xlink="http://www.w3.org/1999/xlink">
   <defs id="defs_block">
     <filter height="1.504" id="filter_blur" inkspace:collect="always" width="1.1575" x="-0.07875" y="-0.252">
@@ -255,7 +258,7 @@ <h3>Data Frame<a class="headerlink" href="#data-frame" title="Permalink to this
 </section>
 </section>
 <section id="indices-and-tables">
-<h1>Indices and tables<a class="headerlink" href="#indices-and-tables" title="Permalink to this headline">¶</a></h1>
+<h1>Indices and tables<a class="headerlink" href="#indices-and-tables" title="Permalink to this heading">¶</a></h1>
 <ul class="simple">
 <li><p><a class="reference internal" href="genindex.html"><span class="std std-ref">Index</span></a></p></li>
 <li><p><a class="reference internal" href="py-modindex.html"><span class="std std-ref">Module Index</span></a></p></li>
diff --git a/docs/objects.inv b/docs/objects.inv
index 9a7a7240..0ecc5e97 100644
Binary files a/docs/objects.inv and b/docs/objects.inv differ
diff --git a/docs/py-modindex.html b/docs/py-modindex.html
index 8f4a5ad3..5db8b77d 100644
--- a/docs/py-modindex.html
+++ b/docs/py-modindex.html
@@ -3,7 +3,7 @@
 <head>
   <meta charset="utf-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>Python Module Index &mdash; impy 2.2.0 documentation</title>
+  <title>Python Module Index &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -11,9 +11,8 @@
   <![endif]-->
   
         <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
-        <script src="_static/jquery.js"></script>
-        <script src="_static/underscore.js"></script>
         <script src="_static/doctools.js"></script>
+        <script src="_static/sphinx_highlight.js"></script>
     <script src="_static/js/theme.js"></script>
     <link rel="index" title="Index" href="genindex.html" />
     <link rel="search" title="Search" href="search.html" />
@@ -27,14 +26,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -61,8 +64,8 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="index.html" class="icon icon-home"></a> &raquo;</li>
-      <li>Python Module Index</li>
+      <li><a href="index.html" class="icon icon-home" aria-label="Home"></a></li>
+      <li class="breadcrumb-item active">Python Module Index</li>
       <li class="wy-breadcrumbs-aside">
       </li>
   </ul>
@@ -153,6 +156,11 @@ <h1>Python Module Index</h1>
        <td>&#160;&#160;&#160;
        <a href="apidoc/impy.arrays.html#module-impy.arrays.specials"><code class="xref">impy.arrays.specials</code></a></td><td>
        <em></em></td></tr>
+     <tr class="cg-1">
+       <td></td>
+       <td>&#160;&#160;&#160;
+       <a href="apidoc/impy.arrays.html#module-impy.arrays.tiled"><code class="xref">impy.arrays.tiled</code></a></td><td>
+       <em></em></td></tr>
      <tr class="cg-1">
        <td></td>
        <td>&#160;&#160;&#160;
@@ -193,6 +201,21 @@ <h1>Python Module Index</h1>
        <td>&#160;&#160;&#160;
        <a href="apidoc/impy.html#module-impy.io"><code class="xref">impy.io</code></a></td><td>
        <em></em></td></tr>
+     <tr class="cg-1">
+       <td></td>
+       <td>&#160;&#160;&#160;
+       <a href="apidoc/impy.lazy.html#module-impy.lazy"><code class="xref">impy.lazy</code></a></td><td>
+       <em></em></td></tr>
+     <tr class="cg-1">
+       <td></td>
+       <td>&#160;&#160;&#160;
+       <a href="apidoc/impy.lazy.html#module-impy.lazy.core"><code class="xref">impy.lazy.core</code></a></td><td>
+       <em></em></td></tr>
+     <tr class="cg-1">
+       <td></td>
+       <td>&#160;&#160;&#160;
+       <a href="apidoc/impy.lazy.html#module-impy.lazy.random"><code class="xref">impy.lazy.random</code></a></td><td>
+       <em></em></td></tr>
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index 7c75595e..6705035f 100644
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   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
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+  <title>Search &mdash; impy 2.3.0 documentation</title>
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+          
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+            impy
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+                2.3.0
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-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
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@@ -61,8 +64,8 @@
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-      <li><a href="index.html" class="icon icon-home"></a> &raquo;</li>
-      <li>Search</li>
+      <li><a href="index.html" class="icon icon-home" aria-label="Home"></a></li>
+      <li class="breadcrumb-item active">Search</li>
       <li class="wy-breadcrumbs-aside">
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diff --git a/docs/searchindex.js b/docs/searchindex.js
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(impy.viewer.utils.complexarrayview property)": [[8, "impy.viewer.utils.ComplexArrayView.nbytes"]], "ndim (impy.viewer.utils.complexarrayview property)": [[8, "impy.viewer.utils.ComplexArrayView.ndim"]], "scale (impy.viewer.viewer.napariviewers property)": [[8, "impy.viewer.viewer.napariViewers.scale"]], "selection (impy.viewer.viewer.napariviewers property)": [[8, "impy.viewer.viewer.napariViewers.selection"]], "shape (impy.viewer.utils.complexarrayview property)": [[8, "impy.viewer.utils.ComplexArrayView.shape"]], "start() (impy.viewer.viewer.napariviewers method)": [[8, "impy.viewer.viewer.napariViewers.start"]], "stepof() (impy.viewer.viewer.napariviewers method)": [[8, "impy.viewer.viewer.napariViewers.stepof"]], "to_labels() (in module impy.viewer.utils)": [[8, "impy.viewer.utils.to_labels"]], "viewer (impy.viewer.viewer.napariviewers property)": [[8, "impy.viewer.viewer.napariViewers.viewer"]], "viewer_imread() (in module impy.viewer.utils)": [[8, "impy.viewer.utils.viewer_imread"]]}})
\ No newline at end of file
diff --git a/docs/tutorial.html b/docs/tutorial.html
index 5791a37f..fed88d38 100644
--- a/docs/tutorial.html
+++ b/docs/tutorial.html
@@ -1,10 +1,10 @@
 <!DOCTYPE html>
 <html class="writer-html5" lang="en" >
 <head>
-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
+  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>Tutorial &mdash; impy 2.2.0 documentation</title>
+  <title>Tutorial &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -12,9 +12,8 @@
   <![endif]-->
   
         <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
-        <script src="_static/jquery.js"></script>
-        <script src="_static/underscore.js"></script>
         <script src="_static/doctools.js"></script>
+        <script src="_static/sphinx_highlight.js"></script>
     <script src="_static/js/theme.js"></script>
     <link rel="index" title="Index" href="genindex.html" />
     <link rel="search" title="Search" href="search.html" />
@@ -27,14 +26,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -83,8 +86,8 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="index.html" class="icon icon-home"></a> &raquo;</li>
-      <li>Tutorial</li>
+      <li><a href="index.html" class="icon icon-home" aria-label="Home"></a></li>
+      <li class="breadcrumb-item active">Tutorial</li>
       <li class="wy-breadcrumbs-aside">
             <a href="_sources/tutorial.rst.txt" rel="nofollow"> View page source</a>
       </li>
@@ -95,8 +98,8 @@
            <div itemprop="articleBody">
              
   <section id="tutorial">
-<h1>Tutorial<a class="headerlink" href="#tutorial" title="Permalink to this headline">¶</a></h1>
-<div class="contents local topic" id="contents-of-tutorial">
+<h1>Tutorial<a class="headerlink" href="#tutorial" title="Permalink to this heading">¶</a></h1>
+<nav class="contents local" id="contents-of-tutorial">
 <p class="topic-title">Contents of Tutorial</p>
 <ul class="simple">
 <li><p><a class="reference internal" href="#basics" id="id1">Basics</a></p></li>
@@ -123,9 +126,9 @@ <h1>Tutorial<a class="headerlink" href="#tutorial" title="Permalink to this head
 </ul>
 </li>
 </ul>
-</div>
+</nav>
 <section id="basics">
-<h2><a class="toc-backref" href="#id1">Basics</a><a class="headerlink" href="#basics" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id1" role="doc-backlink">Basics</a><a class="headerlink" href="#basics" title="Permalink to this heading">¶</a></h2>
 <p><code class="docutils literal notranslate"><span class="pre">impy</span></code>’s concept is to make image analysis on Python much more user friendly. The core array object,
 <code class="docutils literal notranslate"><span class="pre">ImgArray</span></code>, retains all the features of <code class="docutils literal notranslate"><span class="pre">numpy.ndarray</span></code> while implemented with variety of function
 that minimize your effort of image processing.</p>
@@ -168,7 +171,7 @@ <h2><a class="toc-backref" href="#id1">Basics</a><a class="headerlink" href="#ba
 <p>and wait until viewer window opens.</p>
 </section>
 <section id="axes-targeted-slicing">
-<h2><a class="toc-backref" href="#id2">Axes Targeted Slicing</a><a class="headerlink" href="#axes-targeted-slicing" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id2" role="doc-backlink">Axes Targeted Slicing</a><a class="headerlink" href="#axes-targeted-slicing" title="Permalink to this heading">¶</a></h2>
 <p>You may want to get slice(s) of an image with a format like “t=3:10” but generally you always have to
 care about which is t-axis. Most arrays in <code class="docutils literal notranslate"><span class="pre">impy</span></code> have extended <code class="docutils literal notranslate"><span class="pre">numpy.ndarray</span></code> to enable the
 “axis-targeted slicing”. You can use following grammar:</p>
@@ -195,9 +198,9 @@ <h2><a class="toc-backref" href="#id2">Axes Targeted Slicing</a><a class="header
 </div>
 </section>
 <section id="batch-processing">
-<h2><a class="toc-backref" href="#id3">Batch Processing</a><a class="headerlink" href="#batch-processing" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id3" role="doc-backlink">Batch Processing</a><a class="headerlink" href="#batch-processing" title="Permalink to this heading">¶</a></h2>
 <section id="image-stacks">
-<h3><a class="toc-backref" href="#id4">Image Stacks</a><a class="headerlink" href="#image-stacks" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id4" role="doc-backlink">Image Stacks</a><a class="headerlink" href="#image-stacks" title="Permalink to this heading">¶</a></h3>
 <p>Owing to the axes information, impy can automatically execute functions for every image slice properly.
 As in the first example, with a <cite>tzyx</cite> image, instead of running</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">out</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">empty_like</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>
@@ -218,7 +221,7 @@ <h3><a class="toc-backref" href="#id4">Image Stacks</a><a class="headerlink" hre
 </div>
 </section>
 <section id="running-function-with-different-parameters">
-<h3><a class="toc-backref" href="#id5">Running Function with Different Parameters</a><a class="headerlink" href="#running-function-with-different-parameters" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id5" role="doc-backlink">Running Function with Different Parameters</a><a class="headerlink" href="#running-function-with-different-parameters" title="Permalink to this heading">¶</a></h3>
 <ol class="arabic simple">
 <li><p>Apply a function to whole image with different parameters</p></li>
 </ol>
@@ -235,7 +238,7 @@ <h3><a class="toc-backref" href="#id5">Running Function with Different Parameter
 </div>
 </section>
 <section id="images-with-different-shapes">
-<h3><a class="toc-backref" href="#id6">Images with Different Shapes</a><a class="headerlink" href="#images-with-different-shapes" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id6" role="doc-backlink">Images with Different Shapes</a><a class="headerlink" href="#images-with-different-shapes" title="Permalink to this heading">¶</a></h3>
 <p>For images with different shapes, they cannot be stacked into a single array. In this case, you can use <code class="docutils literal notranslate"><span class="pre">DataList</span></code>, an
 extension of Python <code class="docutils literal notranslate"><span class="pre">list</span></code>. <code class="docutils literal notranslate"><span class="pre">DataList</span></code> recognizes any member functions of its components and call the function for all
 the components. Here’s an example:</p>
@@ -263,7 +266,7 @@ <h3><a class="toc-backref" href="#id6">Images with Different Shapes</a><a class=
 </section>
 </section>
 <section id="extended-numpy-functions">
-<h2><a class="toc-backref" href="#id7">Extended Numpy functions</a><a class="headerlink" href="#extended-numpy-functions" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id7" role="doc-backlink">Extended Numpy functions</a><a class="headerlink" href="#extended-numpy-functions" title="Permalink to this heading">¶</a></h2>
 <p>In almost all the <code class="docutils literal notranslate"><span class="pre">numpy</span></code> functions, the keyword argument <code class="docutils literal notranslate"><span class="pre">axis</span></code> can be given as the symbol of axis if the argument(s) are <code class="docutils literal notranslate"><span class="pre">ImgArray</span></code>
 or other arrays that belong to subclass of <code class="docutils literal notranslate"><span class="pre">MetaArray</span></code>.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="s2">&quot;z&quot;</span><span class="p">)</span>           <span class="c1"># Z-projection, although ImgArray provides more flexible function &quot;proj()&quot;</span>
@@ -280,7 +283,7 @@ <h2><a class="toc-backref" href="#id7">Extended Numpy functions</a><a class="hea
 </div>
 </section>
 <section id="use-gpu">
-<h2><a class="toc-backref" href="#id8">Use GPU</a><a class="headerlink" href="#use-gpu" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id8" role="doc-backlink">Use GPU</a><a class="headerlink" href="#use-gpu" title="Permalink to this heading">¶</a></h2>
 <p><code class="docutils literal notranslate"><span class="pre">impy</span></code> can automatically switch between <code class="docutils literal notranslate"><span class="pre">numpy</span></code> and <code class="docutils literal notranslate"><span class="pre">cupy</span></code>. Using GPU can largely boost
 your image analysis especially when it relies on Fourier transformation or linear algebra.
 You can setup GPU calculation within a context using</p>
@@ -294,33 +297,33 @@ <h2><a class="toc-backref" href="#id8">Use GPU</a><a class="headerlink" href="#u
 </div>
 </section>
 <section id="advanced-reading-options">
-<h2><a class="toc-backref" href="#id9">Advanced Reading Options</a><a class="headerlink" href="#advanced-reading-options" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id9" role="doc-backlink">Advanced Reading Options</a><a class="headerlink" href="#advanced-reading-options" title="Permalink to this heading">¶</a></h2>
 <section id="read-separate-images-as-an-image-stack">
-<h3><a class="toc-backref" href="#id10">Read Separate Images as an Image Stack</a><a class="headerlink" href="#read-separate-images-as-an-image-stack" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id10" role="doc-backlink">Read Separate Images as an Image Stack</a><a class="headerlink" href="#read-separate-images-as-an-image-stack" title="Permalink to this heading">¶</a></h3>
 <p>If images are saved as separate tif files in a directory, you can read them as an image stack by:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">img</span> <span class="o">=</span> <span class="n">ip</span><span class="o">.</span><span class="n">imread</span><span class="p">(</span><span class="s2">&quot;path/to/image/*.tif&quot;</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
 <section id="read-separate-images-as-an-datalist">
-<h3><a class="toc-backref" href="#id11">Read Separate Images as an DataList</a><a class="headerlink" href="#read-separate-images-as-an-datalist" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id11" role="doc-backlink">Read Separate Images as an DataList</a><a class="headerlink" href="#read-separate-images-as-an-datalist" title="Permalink to this heading">¶</a></h3>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">img</span> <span class="o">=</span> <span class="n">ip</span><span class="o">.</span><span class="n">imread_collection</span><span class="p">(</span><span class="s2">&quot;path/to/image/*.tif&quot;</span><span class="p">)</span>
 </pre></div>
 </div>
 </section>
 </section>
 <section id="large-images">
-<h2><a class="toc-backref" href="#id12">Large Images</a><a class="headerlink" href="#large-images" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id12" role="doc-backlink">Large Images</a><a class="headerlink" href="#large-images" title="Permalink to this heading">¶</a></h2>
 <p>There are two ways to handle large images.</p>
 <section id="lazyimgarray">
-<h3><a class="toc-backref" href="#id13">LazyImgArray</a><a class="headerlink" href="#lazyimgarray" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id13" role="doc-backlink">LazyImgArray</a><a class="headerlink" href="#lazyimgarray" title="Permalink to this heading">¶</a></h3>
 <p>If you deal with very large images that exceeds PC memory, you can use <code class="docutils literal notranslate"><span class="pre">LazyImgArray</span></code>. This object retains
 memory map of the image file that is split into smaller chunks, and passes it to <code class="docutils literal notranslate"><span class="pre">dask</span></code> array as “ready to
 read” state. The image data is therefore loaded only when it is needed. Many useful functions in <code class="docutils literal notranslate"><span class="pre">ImgArray</span></code>
 are also implemented in <code class="docutils literal notranslate"><span class="pre">LazyImgArray</span></code> so that you can easily handle large datasets.</p>
-<p>To read large images as <code class="docutils literal notranslate"><span class="pre">LazyImgArray</span></code>, call <code class="docutils literal notranslate"><span class="pre">lazy_imread</span></code> instead. You can specify its chunk size using
+<p>To read large images as <code class="docutils literal notranslate"><span class="pre">LazyImgArray</span></code>, call <code class="docutils literal notranslate"><span class="pre">impy.lazy.imread</span></code> instead. You can specify its chunk size using
 <code class="docutils literal notranslate"><span class="pre">chunks</span></code> parameter.</p>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">img</span> <span class="o">=</span> <span class="n">ip</span><span class="o">.</span><span class="n">lazy_imread</span><span class="p">(</span><span class="s2">&quot;path/to/image.tif&quot;</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="s2">&quot;auto&quot;</span><span class="p">,</span> <span class="s2">&quot;auto&quot;</span><span class="p">,</span> <span class="s2">&quot;auto&quot;</span><span class="p">))</span>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">img</span> <span class="o">=</span> <span class="n">ip</span><span class="o">.</span><span class="n">lazy</span><span class="o">.</span><span class="n">imread</span><span class="p">(</span><span class="s2">&quot;path/to/image.tif&quot;</span><span class="p">,</span> <span class="n">chunks</span><span class="o">=</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="s2">&quot;auto&quot;</span><span class="p">,</span> <span class="s2">&quot;auto&quot;</span><span class="p">,</span> <span class="s2">&quot;auto&quot;</span><span class="p">))</span>
 <span class="n">img</span>
 </pre></div>
 </div>
@@ -346,7 +349,7 @@ <h3><a class="toc-backref" href="#id13">LazyImgArray</a><a class="headerlink" hr
 </div>
 </section>
 <section id="bigimgarray">
-<h3><a class="toc-backref" href="#id14">BigImgArray</a><a class="headerlink" href="#bigimgarray" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id14" role="doc-backlink">BigImgArray</a><a class="headerlink" href="#bigimgarray" title="Permalink to this heading">¶</a></h3>
 <p><code class="docutils literal notranslate"><span class="pre">LazyImgArray</span></code> is useful to process large images. However, it is not suitable for interactive analysis
 because calculation starts from the beginning for every operation. <code class="docutils literal notranslate"><span class="pre">BigImgArray</span></code> is a subclass of
 <code class="docutils literal notranslate"><span class="pre">LazyImgArray</span></code> but it stores the cashed data in a temporary file.</p>
diff --git a/docs/tutorial_axes.html b/docs/tutorial_axes.html
index c347fa7f..0aa20711 100644
--- a/docs/tutorial_axes.html
+++ b/docs/tutorial_axes.html
@@ -1,10 +1,10 @@
 <!DOCTYPE html>
 <html class="writer-html5" lang="en" >
 <head>
-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
+  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>Axes in impy &mdash; impy 2.2.0 documentation</title>
+  <title>Axes in impy &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -12,9 +12,8 @@
   <![endif]-->
   
         <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
-        <script src="_static/jquery.js"></script>
-        <script src="_static/underscore.js"></script>
         <script src="_static/doctools.js"></script>
+        <script src="_static/sphinx_highlight.js"></script>
     <script src="_static/js/theme.js"></script>
     <link rel="index" title="Index" href="genindex.html" />
     <link rel="search" title="Search" href="search.html" />
@@ -27,14 +26,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -79,8 +82,8 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="index.html" class="icon icon-home"></a> &raquo;</li>
-      <li>Axes in impy</li>
+      <li><a href="index.html" class="icon icon-home" aria-label="Home"></a></li>
+      <li class="breadcrumb-item active">Axes in impy</li>
       <li class="wy-breadcrumbs-aside">
             <a href="_sources/tutorial_axes.rst.txt" rel="nofollow"> View page source</a>
       </li>
@@ -91,8 +94,8 @@
            <div itemprop="articleBody">
              
   <section id="axes-in-impy">
-<h1>Axes in impy<a class="headerlink" href="#axes-in-impy" title="Permalink to this headline">¶</a></h1>
-<div class="contents local topic" id="contents-of-tutorial">
+<h1>Axes in impy<a class="headerlink" href="#axes-in-impy" title="Permalink to this heading">¶</a></h1>
+<nav class="contents local" id="contents-of-tutorial">
 <p class="topic-title">Contents of Tutorial</p>
 <ul class="simple">
 <li><p><a class="reference internal" href="#basics" id="id1">Basics</a></p></li>
@@ -110,9 +113,9 @@ <h1>Axes in impy<a class="headerlink" href="#axes-in-impy" title="Permalink to t
 </ul>
 </li>
 </ul>
-</div>
+</nav>
 <section id="basics">
-<h2><a class="toc-backref" href="#id1">Basics</a><a class="headerlink" href="#basics" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id1" role="doc-backlink">Basics</a><a class="headerlink" href="#basics" title="Permalink to this heading">¶</a></h2>
 <p>Understanding the concept of axes is important to use multi-dimensional arrays.</p>
 <p>Each dimension of an array has its own meaning. A 3-D array can be composed of
 three spatial axes or two spatial axes and a time axis.</p>
@@ -144,7 +147,7 @@ <h2><a class="toc-backref" href="#id1">Basics</a><a class="headerlink" href="#ba
 </div>
 </section>
 <section id="undefined-axis">
-<h2><a class="toc-backref" href="#id2">Undefined Axis</a><a class="headerlink" href="#undefined-axis" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id2" role="doc-backlink">Undefined Axis</a><a class="headerlink" href="#undefined-axis" title="Permalink to this heading">¶</a></h2>
 <p>Some functions and operations, such as <code class="xref py py-meth docutils literal notranslate"><span class="pre">ravel()</span></code> and <code class="xref py py-meth docutils literal notranslate"><span class="pre">reshape()</span></code>, creates arrays
 with unknown axes. In this case, <code class="docutils literal notranslate"><span class="pre">UndefAxis</span></code> objects are used for these axes and are
 represented by <code class="docutils literal notranslate"><span class="pre">&quot;#&quot;</span></code>.</p>
@@ -158,7 +161,7 @@ <h2><a class="toc-backref" href="#id2">Undefined Axis</a><a class="headerlink" h
 </div>
 </section>
 <section id="axis-metadata">
-<h2><a class="toc-backref" href="#id3">Axis Metadata</a><a class="headerlink" href="#axis-metadata" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id3" role="doc-backlink">Axis Metadata</a><a class="headerlink" href="#axis-metadata" title="Permalink to this heading">¶</a></h2>
 <p>Each axis could be tagged with some metadata. The major ones are physical scale,
 physical scale unit and labels.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">img</span><span class="o">.</span><span class="n">axes</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">scale</span>  <span class="c1"># scale of the first axis</span>
@@ -169,7 +172,7 @@ <h2><a class="toc-backref" href="#id3">Axis Metadata</a><a class="headerlink" hr
 </pre></div>
 </div>
 <section id="physical-scale">
-<h3><a class="toc-backref" href="#id4">Physical scale</a><a class="headerlink" href="#physical-scale" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id4" role="doc-backlink">Physical scale</a><a class="headerlink" href="#physical-scale" title="Permalink to this heading">¶</a></h3>
 <p>Physical scale is the length of value between <code class="docutils literal notranslate"><span class="pre">a[i]</span></code> and <code class="docutils literal notranslate"><span class="pre">a[i+1]</span></code>. In image analysis,
 this value is usually represented as “µm/pixel” or “nm/pixel” for spatial axes and “sec” for
 time axis.</p>
@@ -199,7 +202,7 @@ <h3><a class="toc-backref" href="#id4">Physical scale</a><a class="headerlink" h
 </div>
 </section>
 <section id="axis-labels">
-<h3><a class="toc-backref" href="#id5">Axis Labels</a><a class="headerlink" href="#axis-labels" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id5" role="doc-backlink">Axis Labels</a><a class="headerlink" href="#axis-labels" title="Permalink to this heading">¶</a></h3>
 <p>Sometimes an axis is tagged with “labels” that explains what each slice means. <code class="docutils literal notranslate"><span class="pre">Axis</span></code> object
 retains labels information and can be referred to as a tuple.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">assert</span> <span class="n">img</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="s2">&quot;t&quot;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">4</span>  <span class="c1"># say the length of t-axis is 4</span>
@@ -222,12 +225,12 @@ <h3><a class="toc-backref" href="#id5">Axis Labels</a><a class="headerlink" href
 </section>
 </section>
 <section id="practical-usage-of-axes">
-<h2><a class="toc-backref" href="#id6">Practical Usage of Axes</a><a class="headerlink" href="#practical-usage-of-axes" title="Permalink to this headline">¶</a></h2>
+<h2><a class="toc-backref" href="#id6" role="doc-backlink">Practical Usage of Axes</a><a class="headerlink" href="#practical-usage-of-axes" title="Permalink to this heading">¶</a></h2>
 <section id="slicing-and-formatting">
-<h3><a class="toc-backref" href="#id7">Slicing and Formatting</a><a class="headerlink" href="#slicing-and-formatting" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id7" role="doc-backlink">Slicing and Formatting</a><a class="headerlink" href="#slicing-and-formatting" title="Permalink to this heading">¶</a></h3>
 <p>Axes object is very useful in slicing multi-dimensional arrays.</p>
 <section id="axis-targeted-slicing">
-<h4>Axis-targeted slicing<a class="headerlink" href="#axis-targeted-slicing" title="Permalink to this headline">¶</a></h4>
+<h4>Axis-targeted slicing<a class="headerlink" href="#axis-targeted-slicing" title="Permalink to this heading">¶</a></h4>
 <p>As shown in tutorial, the easiest way to slice an array is to use axis axis-targeted slicing.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">img</span><span class="p">[</span><span class="s2">&quot;t=1&quot;</span><span class="p">]</span>
 <span class="n">img</span><span class="p">[</span><span class="s2">&quot;t=3:5&quot;</span><span class="p">]</span>
@@ -253,7 +256,7 @@ <h4>Axis-targeted slicing<a class="headerlink" href="#axis-targeted-slicing" tit
 </div>
 </section>
 <section id="slice-formatting">
-<h4>Slice Formatting<a class="headerlink" href="#slice-formatting" title="Permalink to this headline">¶</a></h4>
+<h4>Slice Formatting<a class="headerlink" href="#slice-formatting" title="Permalink to this heading">¶</a></h4>
 <p>Sometimes you would slice many times at the same axes.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">img</span><span class="p">[</span><span class="n">ip</span><span class="o">.</span><span class="n">slicer</span><span class="o">.</span><span class="n">z</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">t</span><span class="p">[</span><span class="mi">2</span><span class="p">]]</span><span class="o">.</span><span class="n">gaussian_filter</span><span class="p">(</span><span class="mf">1.0</span><span class="p">)</span>
 <span class="n">img</span><span class="p">[</span><span class="n">ip</span><span class="o">.</span><span class="n">slicer</span><span class="o">.</span><span class="n">z</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">t</span><span class="p">[</span><span class="mi">1</span><span class="p">]]</span><span class="o">.</span><span class="n">gaussian_filter</span><span class="p">(</span><span class="mf">1.5</span><span class="p">)</span>
@@ -287,7 +290,7 @@ <h4>Slice Formatting<a class="headerlink" href="#slice-formatting" title="Permal
 </section>
 </section>
 <section id="broadcasting">
-<h3><a class="toc-backref" href="#id8">Broadcasting</a><a class="headerlink" href="#broadcasting" title="Permalink to this headline">¶</a></h3>
+<h3><a class="toc-backref" href="#id8" role="doc-backlink">Broadcasting</a><a class="headerlink" href="#broadcasting" title="Permalink to this heading">¶</a></h3>
 <p>By using axes information, arrays can be broadcasted in a more flexible but strict way.</p>
 <ul>
 <li><p>Examples</p>
diff --git a/docs/tutorial_cmd.html b/docs/tutorial_cmd.html
index 1d80739c..815597ed 100644
--- a/docs/tutorial_cmd.html
+++ b/docs/tutorial_cmd.html
@@ -1,10 +1,10 @@
 <!DOCTYPE html>
 <html class="writer-html5" lang="en" >
 <head>
-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.17.1: http://docutils.sourceforge.net/" />
+  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>Command Line Usage &mdash; impy 2.2.0 documentation</title>
+  <title>Command Line Usage &mdash; impy 2.3.0 documentation</title>
       <link rel="stylesheet" href="_static/pygments.css" type="text/css" />
       <link rel="stylesheet" href="_static/css/theme.css" type="text/css" />
   <!--[if lt IE 9]>
@@ -12,9 +12,8 @@
   <![endif]-->
   
         <script data-url_root="./" id="documentation_options" src="_static/documentation_options.js"></script>
-        <script src="_static/jquery.js"></script>
-        <script src="_static/underscore.js"></script>
         <script src="_static/doctools.js"></script>
+        <script src="_static/sphinx_highlight.js"></script>
     <script src="_static/js/theme.js"></script>
     <link rel="index" title="Index" href="genindex.html" />
     <link rel="search" title="Search" href="search.html" />
@@ -27,14 +26,18 @@
     <nav data-toggle="wy-nav-shift" class="wy-nav-side">
       <div class="wy-side-scroll">
         <div class="wy-side-nav-search" >
-            <a href="index.html" class="icon icon-home"> impy
+
+          
+          
+          <a href="index.html" class="icon icon-home">
+            impy
           </a>
               <div class="version">
-                2.2.0
+                2.3.0
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="search.html" method="get">
-    <input type="text" name="q" placeholder="Search docs" />
+    <input type="text" name="q" placeholder="Search docs" aria-label="Search docs" />
     <input type="hidden" name="check_keywords" value="yes" />
     <input type="hidden" name="area" value="default" />
   </form>
@@ -65,8 +68,8 @@
         <div class="rst-content">
           <div role="navigation" aria-label="Page navigation">
   <ul class="wy-breadcrumbs">
-      <li><a href="index.html" class="icon icon-home"></a> &raquo;</li>
-      <li>Command Line Usage</li>
+      <li><a href="index.html" class="icon icon-home" aria-label="Home"></a></li>
+      <li class="breadcrumb-item active">Command Line Usage</li>
       <li class="wy-breadcrumbs-aside">
             <a href="_sources/tutorial_cmd.rst.txt" rel="nofollow"> View page source</a>
       </li>
@@ -77,18 +80,18 @@
            <div itemprop="articleBody">
              
   <section id="command-line-usage">
-<h1>Command Line Usage<a class="headerlink" href="#command-line-usage" title="Permalink to this headline">¶</a></h1>
+<h1>Command Line Usage<a class="headerlink" href="#command-line-usage" title="Permalink to this heading">¶</a></h1>
 <p>Image analysis usually relies on different softwares in different platform.
 The traditional command line based interface is still useful in this purpose.</p>
 <p><code class="docutils literal notranslate"><span class="pre">impy</span></code> also supports command line usage.</p>
 <section id="basic-usage">
-<h2>Basic Usage<a class="headerlink" href="#basic-usage" title="Permalink to this headline">¶</a></h2>
+<h2>Basic Usage<a class="headerlink" href="#basic-usage" title="Permalink to this heading">¶</a></h2>
 <p>The most basic one is:</p>
-<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>impy --input path/to/image.tif --output path/to/output.tif --method gaussian_filter --sigma <span class="m">2</span>
+<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>impy<span class="w"> </span>--input<span class="w"> </span>path/to/image.tif<span class="w"> </span>--output<span class="w"> </span>path/to/output.tif<span class="w"> </span>--method<span class="w"> </span>gaussian_filter<span class="w"> </span>--sigma<span class="w"> </span><span class="m">2</span>
 </pre></div>
 </div>
 <p>or <code class="docutils literal notranslate"><span class="pre">--input</span></code> and <code class="docutils literal notranslate"><span class="pre">--output</span></code> can be omitted like:</p>
-<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>impy path/to/image.tif path/to/output.tif --method gaussian_filter --sigma <span class="m">2</span>
+<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>impy<span class="w"> </span>path/to/image.tif<span class="w"> </span>path/to/output.tif<span class="w"> </span>--method<span class="w"> </span>gaussian_filter<span class="w"> </span>--sigma<span class="w"> </span><span class="m">2</span>
 </pre></div>
 </div>
 <p>You have to specify <code class="docutils literal notranslate"><span class="pre">--method</span></code> or <code class="docutils literal notranslate"><span class="pre">-m</span></code> to let <code class="docutils literal notranslate"><span class="pre">impy</span></code> know what method you’d like to run.
@@ -103,13 +106,13 @@ <h2>Basic Usage<a class="headerlink" href="#basic-usage" title="Permalink to thi
 </div>
 </section>
 <section id="advanced-usage">
-<h2>Advanced Usage<a class="headerlink" href="#advanced-usage" title="Permalink to this headline">¶</a></h2>
+<h2>Advanced Usage<a class="headerlink" href="#advanced-usage" title="Permalink to this heading">¶</a></h2>
 <p>Sometimes you may want to apply multiple filters in tandem to an image. Classically it was
 usually done by saving intermediate files, but here we should take advantage of IPython.</p>
 <p>Instead of parsing <code class="docutils literal notranslate"><span class="pre">--output</span></code>, you can use <code class="docutils literal notranslate"><span class="pre">-i</span></code> flag to launch IPython interpreter with
 namespace <code class="docutils literal notranslate"><span class="pre">ip</span></code> and <code class="docutils literal notranslate"><span class="pre">img</span></code>. <code class="docutils literal notranslate"><span class="pre">ip</span></code> is an alias of <code class="docutils literal notranslate"><span class="pre">impy</span></code> as usual, and <code class="docutils literal notranslate"><span class="pre">img</span></code> is an
 <code class="docutils literal notranslate"><span class="pre">ImgArray</span></code> object that is created by reading the <code class="docutils literal notranslate"><span class="pre">--input</span></code> argument.</p>
-<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>impy path/to/image.tif -i
+<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>impy<span class="w"> </span>path/to/image.tif<span class="w"> </span>-i
 </pre></div>
 </div>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">arr</span> <span class="o">=</span> <span class="n">ip</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">random</span><span class="p">((</span><span class="mi">100</span><span class="p">,</span> <span class="mi">120</span><span class="p">))</span>  <span class="c1"># &quot;ip&quot; is already available</span>
@@ -119,7 +122,7 @@ <h2>Advanced Usage<a class="headerlink" href="#advanced-usage" title="Permalink
 </div>
 <p>Another option is <code class="docutils literal notranslate"><span class="pre">-n</span></code>, which send namespace including input image to <code class="docutils literal notranslate"><span class="pre">napari</span></code> viewer
 and console.</p>
-<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>impy path/to/image.tif -n
+<div class="highlight-shell notranslate"><div class="highlight"><pre><span></span>impy<span class="w"> </span>path/to/image.tif<span class="w"> </span>-n
 </pre></div>
 </div>
 </section>
diff --git a/rst/apidoc/impy.arrays.rst b/rst/apidoc/impy.arrays.rst
index c73408d9..94f0d34f 100644
--- a/rst/apidoc/impy.arrays.rst
+++ b/rst/apidoc/impy.arrays.rst
@@ -76,6 +76,14 @@ impy.arrays.specials module
    :undoc-members:
    :show-inheritance:
 
+impy.arrays.tiled module
+------------------------
+
+.. automodule:: impy.arrays.tiled
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
 Module contents
 ---------------
 
diff --git a/rst/apidoc/impy.lazy.rst b/rst/apidoc/impy.lazy.rst
new file mode 100644
index 00000000..84629d5f
--- /dev/null
+++ b/rst/apidoc/impy.lazy.rst
@@ -0,0 +1,29 @@
+impy.lazy package
+=================
+
+Submodules
+----------
+
+impy.lazy.core module
+---------------------
+
+.. automodule:: impy.lazy.core
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+impy.lazy.random module
+-----------------------
+
+.. automodule:: impy.lazy.random
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+Module contents
+---------------
+
+.. automodule:: impy.lazy
+   :members:
+   :undoc-members:
+   :show-inheritance:
diff --git a/rst/apidoc/impy.rst b/rst/apidoc/impy.rst
index 2dee1ab1..dad37dc5 100644
--- a/rst/apidoc/impy.rst
+++ b/rst/apidoc/impy.rst
@@ -10,6 +10,7 @@ Subpackages
    impy.arrays
    impy.axes
    impy.frame
+   impy.lazy
    impy.utils
    impy.viewer