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guiwitz · Apr 5, 2022 · a85b543 · a85b543
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diff --git a/README.html b/README.html
@@ -350,10 +350,14 @@ <h1>microfilm<a class="headerlink" href="#microfilm" title="Permalink to this he
 <p>Following the model of <a class="reference external" href="https://seaborn.pydata.org/index.html">seaborn</a>, <code class="docutils literal notranslate"><span class="pre">microfilm</span></code> is entirely based on <a class="reference external" href="https://matplotlib.org/">Matplotlib</a> and tries to provide good defaults to produce good microcopy figures <em>out-of-the-box</em>. It however also offers complete access to the Matplotlib structures like axis and figures underlying the <code class="docutils literal notranslate"><span class="pre">microfilm</span></code> objects, allowing thus for the creation of arbitrarily complex plots.</p>
 <div class="section" id="installation">
 <h2>Installation<a class="headerlink" href="#installation" title="Permalink to this headline">¶</a></h2>
-<p>You can install this package directly from Github using:</p>
+<p>You can install this package directly with pip using:</p>
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">pip</span> <span class="n">install</span> <span class="n">microfilm</span>
 </pre></div>
 </div>
+<p>To get the latest stage of the package with yet unreleased features use:</p>
+<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">pip</span> <span class="n">install</span> <span class="n">git</span><span class="o">+</span><span class="n">https</span><span class="p">:</span><span class="o">//</span><span class="n">github</span><span class="o">.</span><span class="n">com</span><span class="o">/</span><span class="n">guiwitz</span><span class="o">/</span><span class="n">microfilm</span><span class="o">.</span><span class="n">git</span>
+</pre></div>
+</div>
 <p>To test the package via the Jupyter interface and the notebooks available <span class="xref myst">here</span> you can create a conda environment using the <span class="xref myst">environment.yml</span> file:</p>
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">conda</span> <span class="n">env</span> <span class="n">create</span> <span class="o">-</span><span class="n">f</span> <span class="n">environment</span><span class="o">.</span><span class="n">yml</span>
 </pre></div>

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diff --git a/_sources/README.md b/_sources/README.md
@@ -12,12 +12,18 @@ Following the model of [seaborn](https://seaborn.pydata.org/index.html), ```micr
 
 ## Installation
 
-You can install this package directly from Github using: 
+You can install this package directly with pip using: 
 
 ```
 pip install microfilm
 ```
 
+To get the latest stage of the package with yet unreleased features use:
+
+```
+pip install git+https://github.com/guiwitz/microfilm.git
+```
+
 To test the package via the Jupyter interface and the notebooks available [here](notebooks) you can create a conda environment using the [environment.yml](binder/environment.yml) file:
 
 ```

diff --git a/_sources/docs/first_plot.ipynb b/_sources/docs/first_plot.ipynb
diff --git a/_sources/notebooks/create_plots.ipynb b/_sources/notebooks/create_plots.ipynb
diff --git a/_static/__pycache__/__init__.cpython-39.pyc b/_static/__pycache__/__init__.cpython-39.pyc
diff --git a/docs/source/microfilm.html b/docs/source/microfilm.html
@@ -390,8 +390,8 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dl class="field-list simple">
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
-<li><p><strong>cmap_name</strong> (<em>str</em>) – Matplotlib colormap or ‘pure_red’, ‘pure_green’, ‘pure_blue’
-‘pure_magenta’, ‘pure_cyan’, ‘pure_yellow’</p></li>
+<li><p><strong>cmap_name</strong> (<em>str</em>) – {‘pure_red’, ‘pure_green’, ‘pure_blue’, ‘pure_magenta’,
+‘pure_cyan’, ‘pure_yellow’} or Matplotlib colormap</p></li>
 <li><p><strong>num_colors</strong> (<em>int</em>) – number of steps in color scale</p></li>
 <li><p><strong>flip_map</strong> (<em>bool</em>) – invert colormap</p></li>
 </ul>
@@ -444,7 +444,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>image</strong> (<em>2d array</em>) – image to convert to RGB</p></li>
-<li><p><strong>cmap_name</strong> (<em>str</em>) – Matplotlib colormap or ‘pure_red’, ‘pure_green’, ‘pure_blue’</p></li>
+<li><p><strong>cmap_hex</strong> (<em>str</em>) – hex string defining color, default ‘#ff6600’</p></li>
 <li><p><strong>flip_map</strong> (<em>bool</em>) – invert colormap</p></li>
 <li><p><strong>rescale_type</strong> (<em>str</em>) – ‘min_max’: between extrema values of image
 ‘dtype’: full range of image dtype
@@ -473,7 +473,8 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 <dt class="field-odd">Parameters</dt>
 <dd class="field-odd"><ul class="simple">
 <li><p><strong>image</strong> (<em>2d array</em>) – image to convert to RGB</p></li>
-<li><p><strong>cmap_name</strong> (<em>str</em>) – Matplotlib colormap or ‘pure_red’, ‘pure_green’, ‘pure_blue’</p></li>
+<li><p><strong>cmap_name</strong> (<em>str</em>) – {‘pure_red’, ‘pure_green’, ‘pure_blue’, ‘pure_magenta’,
+‘pure_cyan’, ‘pure_yellow’} or Matplotlib colormap</p></li>
 <li><p><strong>flip_map</strong> (<em>bool</em>) – invert colormap</p></li>
 <li><p><strong>rescale_type</strong> (<em>str</em>) – ‘min_max’: between extrema values of image
 ‘dtype’: full range of image dtype

diff --git a/notebooks/create_plots.html b/notebooks/create_plots.html
@@ -589,7 +589,7 @@ <h3>Load images<a class="headerlink" href="#load-images" title="Permalink to thi
 </div>
 <div class="section" id="creating-a-default-plot">
 <h3>Creating a default plot<a class="headerlink" href="#creating-a-default-plot" title="Permalink to this headline">¶</a></h3>
-<p>We can use the <code class="docutils literal notranslate"><span class="pre">microshow</span></code> function to plot our multi-channel image. If no options are passed, by default the image will be represented using the RGB color scheme:</p>
+<p>We can use the <code class="docutils literal notranslate"><span class="pre">microshow</span></code> function to plot our multi-channel image. If no options are passed, by default the image will be represented using the the color-blind friendly magenta-cyan-yellow color combination:</p>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
 <div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">microim</span> <span class="o">=</span> <span class="n">microplot</span><span class="o">.</span><span class="n">microshow</span><span class="p">(</span><span class="n">images</span><span class="o">=</span><span class="n">multi_channel</span><span class="p">)</span>

diff --git a/searchindex.js b/searchindex.js