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neuropsychology · Mar 24, 2024 · df70890 · df70890
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diff --git a/.doctrees/environment.pickle b/.doctrees/environment.pickle
diff --git a/.doctrees/examples/bio_custom/bio_custom.doctree b/.doctrees/examples/bio_custom/bio_custom.doctree
diff --git a/.doctrees/examples/bio_eventrelated/bio_eventrelated.doctree b/.doctrees/examples/bio_eventrelated/bio_eventrelated.doctree
diff --git a/.doctrees/examples/ecg_generate_12leads/ecg_generate_12leads.doctree b/.doctrees/examples/ecg_generate_12leads/ecg_generate_12leads.doctree
diff --git a/.doctrees/examples/ecg_heartbeats/ecg_heartbeats.doctree b/.doctrees/examples/ecg_heartbeats/ecg_heartbeats.doctree
diff --git a/.doctrees/examples/eda_peaks/eda_peaks.doctree b/.doctrees/examples/eda_peaks/eda_peaks.doctree
diff --git a/.doctrees/examples/eeg_complexity/eeg_complexity.doctree b/.doctrees/examples/eeg_complexity/eeg_complexity.doctree
diff --git a/.doctrees/examples/eeg_microstates/eeg_microstates.doctree b/.doctrees/examples/eeg_microstates/eeg_microstates.doctree
diff --git a/.doctrees/examples/eeg_power/eeg_power.doctree b/.doctrees/examples/eeg_power/eeg_power.doctree
diff --git a/.doctrees/examples/eog_analyze/eog_analyze.doctree b/.doctrees/examples/eog_analyze/eog_analyze.doctree
diff --git a/.doctrees/examples/misc_fit_function/misc_fit_function.doctree b/.doctrees/examples/misc_fit_function/misc_fit_function.doctree
diff --git a/.doctrees/examples/signal_simulation/signal_simulation.doctree b/.doctrees/examples/signal_simulation/signal_simulation.doctree
diff --git a/.doctrees/functions/benchmark.doctree b/.doctrees/functions/benchmark.doctree
diff --git a/.doctrees/functions/bio.doctree b/.doctrees/functions/bio.doctree
diff --git a/.doctrees/functions/complexity.doctree b/.doctrees/functions/complexity.doctree
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diff --git a/_modules/neurokit2/data/read_acqknowledge.html b/_modules/neurokit2/data/read_acqknowledge.html
@@ -378,6 +378,8 @@ <h1>Source code for neurokit2.data.read_acqknowledge</h1><div class="highlight">
 <span></span><span class="c1"># -*- coding: utf-8 -*-</span>
 <span class="kn">import</span> <span class="nn">os</span>
 
+<span class="kn">from</span> <span class="nn">collections</span> <span class="kn">import</span> <span class="n">Counter</span>
+
 <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
 <span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
 
@@ -386,9 +388,7 @@ <h1>Source code for neurokit2.data.read_acqknowledge</h1><div class="highlight">
 
 <div class="viewcode-block" id="read_acqknowledge">
 <a class="viewcode-back" href="../../../functions/data.html#neurokit2.data.read_acqknowledge">[docs]</a>
-<span class="k">def</span> <span class="nf">read_acqknowledge</span><span class="p">(</span>
-    <span class="n">filename</span><span class="p">,</span> <span class="n">sampling_rate</span><span class="o">=</span><span class="s2">&quot;max&quot;</span><span class="p">,</span> <span class="n">resample_method</span><span class="o">=</span><span class="s2">&quot;interpolation&quot;</span><span class="p">,</span> <span class="n">impute_missing</span><span class="o">=</span><span class="kc">True</span>
-<span class="p">):</span>
+<span class="k">def</span> <span class="nf">read_acqknowledge</span><span class="p">(</span><span class="n">filename</span><span class="p">,</span> <span class="n">sampling_rate</span><span class="o">=</span><span class="s2">&quot;max&quot;</span><span class="p">,</span> <span class="n">resample_method</span><span class="o">=</span><span class="s2">&quot;interpolation&quot;</span><span class="p">,</span> <span class="n">impute_missing</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
 <span class="w">    </span><span class="sd">&quot;&quot;&quot;**Read and format a BIOPAC&#39;s AcqKnowledge file into a pandas&#39; dataframe**</span>
 
 <span class="sd">    The function outputs both the dataframe and the sampling rate (retrieved from the</span>
@@ -448,10 +448,7 @@ <h1>Source code for neurokit2.data.read_acqknowledge</h1><div class="highlight">
         <span class="n">filename</span> <span class="o">+=</span> <span class="s2">&quot;.acq&quot;</span>
 
     <span class="k">if</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">filename</span><span class="p">)</span> <span class="ow">is</span> <span class="kc">False</span><span class="p">:</span>
-        <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
-            <span class="s2">&quot;NeuroKit error: read_acqknowledge(): couldn&#39;t&quot;</span>
-            <span class="s2">&quot; find the following file: &quot;</span> <span class="o">+</span> <span class="n">filename</span>
-        <span class="p">)</span>
+        <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;NeuroKit error: read_acqknowledge(): couldn&#39;t&quot;</span> <span class="s2">&quot; find the following file: &quot;</span> <span class="o">+</span> <span class="n">filename</span><span class="p">)</span>
 
     <span class="c1"># Read file</span>
     <span class="n">file</span> <span class="o">=</span> <span class="n">bioread</span><span class="o">.</span><span class="n">read</span><span class="p">(</span><span class="n">filename</span><span class="p">)</span>
@@ -463,24 +460,34 @@ <h1>Source code for neurokit2.data.read_acqknowledge</h1><div class="highlight">
             <span class="n">freq_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">file</span><span class="o">.</span><span class="n">named_channels</span><span class="p">[</span><span class="n">channel</span><span class="p">]</span><span class="o">.</span><span class="n">samples_per_second</span><span class="p">)</span>
         <span class="n">sampling_rate</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">freq_list</span><span class="p">)</span>
 
+    <span class="c1"># Counter for checking duplicate channel names</span>
+    <span class="n">channel_counter</span> <span class="o">=</span> <span class="n">Counter</span><span class="p">()</span>
+
     <span class="c1"># Loop through channels</span>
     <span class="n">data</span> <span class="o">=</span> <span class="p">{}</span>
-    <span class="k">for</span> <span class="n">channel</span> <span class="ow">in</span> <span class="n">file</span><span class="o">.</span><span class="n">named_channels</span><span class="p">:</span>
-        <span class="n">signal</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">file</span><span class="o">.</span><span class="n">named_channels</span><span class="p">[</span><span class="n">channel</span><span class="p">]</span><span class="o">.</span><span class="n">data</span><span class="p">)</span>
+    <span class="k">for</span> <span class="n">channel_num</span><span class="p">,</span> <span class="n">channel</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">file</span><span class="o">.</span><span class="n">channels</span><span class="p">):</span>
+        <span class="n">signal</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">file</span><span class="o">.</span><span class="n">channels</span><span class="p">[</span><span class="n">channel_num</span><span class="p">]</span><span class="o">.</span><span class="n">data</span><span class="p">)</span>
 
         <span class="c1"># Fill signal interruptions</span>
         <span class="k">if</span> <span class="n">impute_missing</span> <span class="ow">is</span> <span class="kc">True</span> <span class="ow">and</span> <span class="n">np</span><span class="o">.</span><span class="n">isnan</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">signal</span><span class="p">)):</span>
             <span class="n">signal</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">(</span><span class="n">signal</span><span class="p">)</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">method</span><span class="o">=</span><span class="s2">&quot;pad&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">values</span>
 
         <span class="c1"># Resample if necessary</span>
-        <span class="k">if</span> <span class="n">file</span><span class="o">.</span><span class="n">named_channels</span><span class="p">[</span><span class="n">channel</span><span class="p">]</span><span class="o">.</span><span class="n">samples_per_second</span> <span class="o">!=</span> <span class="n">sampling_rate</span><span class="p">:</span>
+        <span class="k">if</span> <span class="n">file</span><span class="o">.</span><span class="n">channels</span><span class="p">[</span><span class="n">channel_num</span><span class="p">]</span><span class="o">.</span><span class="n">samples_per_second</span> <span class="o">!=</span> <span class="n">sampling_rate</span><span class="p">:</span>
             <span class="n">signal</span> <span class="o">=</span> <span class="n">signal_resample</span><span class="p">(</span>
                 <span class="n">signal</span><span class="p">,</span>
-                <span class="n">sampling_rate</span><span class="o">=</span><span class="n">file</span><span class="o">.</span><span class="n">named_channels</span><span class="p">[</span><span class="n">channel</span><span class="p">]</span><span class="o">.</span><span class="n">samples_per_second</span><span class="p">,</span>
+                <span class="n">sampling_rate</span><span class="o">=</span><span class="n">file</span><span class="o">.</span><span class="n">channels</span><span class="p">[</span><span class="n">channel_num</span><span class="p">]</span><span class="o">.</span><span class="n">samples_per_second</span><span class="p">,</span>
                 <span class="n">desired_sampling_rate</span><span class="o">=</span><span class="n">sampling_rate</span><span class="p">,</span>
                 <span class="n">method</span><span class="o">=</span><span class="n">resample_method</span><span class="p">,</span>
             <span class="p">)</span>
-        <span class="n">data</span><span class="p">[</span><span class="n">channel</span><span class="p">]</span> <span class="o">=</span> <span class="n">signal</span>
+
+        <span class="c1"># If there is a duplicate channel name, append a number</span>
+        <span class="k">if</span> <span class="n">channel_counter</span><span class="p">[</span><span class="n">channel</span><span class="o">.</span><span class="n">name</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
+            <span class="n">data</span><span class="p">[</span><span class="n">channel</span><span class="o">.</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">signal</span>
+        <span class="k">else</span><span class="p">:</span>
+            <span class="n">data</span><span class="p">[</span><span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">channel</span><span class="o">.</span><span class="n">name</span><span class="si">}</span><span class="s2"> (</span><span class="si">{</span><span class="n">channel_counter</span><span class="p">[</span><span class="n">channel</span><span class="o">.</span><span class="n">name</span><span class="p">]</span><span class="si">}</span><span class="s2">)&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">signal</span>
+
+        <span class="n">channel_counter</span><span class="p">[</span><span class="n">channel</span><span class="o">.</span><span class="n">name</span><span class="p">]</span> <span class="o">+=</span> <span class="mi">1</span>
 
     <span class="c1"># Sanitize lengths</span>
     <span class="n">lengths</span> <span class="o">=</span> <span class="p">[]</span>

diff --git a/examples/bio_custom/bio_custom.html b/examples/bio_custom/bio_custom.html
@@ -466,6 +466,11 @@ <h1>Customize your Processing Pipeline<a class="headerlink" href="#customize-you
 </pre></div>
 </div>
 </div>
+<div class="cell_output docutils container">
+<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Matplotlib is building the font cache; this may take a moment.
+</pre></div>
+</div>
+</div>
 </div>
 <div class="cell tag_remove-input docutils container">
 </div>
@@ -487,7 +492,7 @@ <h2>The Default NeuroKit processing pipeline<a class="headerlink" href="#the-def
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../../_images/6981a23e80822a84d85e1917eeea785c9455beb3220b527b3c74ae0ebb39da95.png" src="../../_images/6981a23e80822a84d85e1917eeea785c9455beb3220b527b3c74ae0ebb39da95.png" />
+<img alt="../../_images/dc469ba48ff87380cb3ebf306a2a26772a99f14e1d812432750132b9e03d8144.png" src="../../_images/dc469ba48ff87380cb3ebf306a2a26772a99f14e1d812432750132b9e03d8144.png" />
 </div>
 </div>
 </section>
@@ -535,7 +540,7 @@ <h2>Building your own <code class="docutils literal notranslate"><span class="pr
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../../_images/116ae1c7b99c1a4d2d2850898d8304bb90673ccf471701fa521fe34895db61dc.png" src="../../_images/116ae1c7b99c1a4d2d2850898d8304bb90673ccf471701fa521fe34895db61dc.png" />
+<img alt="../../_images/1318a7ecac4573b3293cfc8afd2c32f7ce1f67a3b5c457e5bad2a2c7e635ef66.png" src="../../_images/1318a7ecac4573b3293cfc8afd2c32f7ce1f67a3b5c457e5bad2a2c7e635ef66.png" />
 </div>
 </div>
 </section>
@@ -627,7 +632,7 @@ <h2>Customize even more!<a class="headerlink" href="#customize-even-more" title=
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../../_images/c3c0f87face04686ab23eab979ea9338f76197d59bb8b8ea7d65f18479f5431f.png" src="../../_images/c3c0f87face04686ab23eab979ea9338f76197d59bb8b8ea7d65f18479f5431f.png" />
+<img alt="../../_images/269bc5f6c9c50e281340b2f6e22874b017a7fc5b7dcd81106689d911f017907e.png" src="../../_images/269bc5f6c9c50e281340b2f6e22874b017a7fc5b7dcd81106689d911f017907e.png" />
 </div>
 </div>
 <p>This doesn’t look bad :) <strong>Can you do better?</strong></p>

diff --git a/examples/bio_eventrelated/bio_eventrelated.html b/examples/bio_eventrelated/bio_eventrelated.html
@@ -527,7 +527,7 @@ <h2>Find Events<a class="headerlink" href="#find-events" title="Link to this hea
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../../_images/304768ca7c098318e5961c3db53c993bf59fc330501fbaf485041bb34e25352a.png" src="../../_images/304768ca7c098318e5961c3db53c993bf59fc330501fbaf485041bb34e25352a.png" />
+<img alt="../../_images/7d9439d1b96f51b14941572097febcea255b0e23ac04101fac7f21d576f3b417.png" src="../../_images/7d9439d1b96f51b14941572097febcea255b0e23ac04101fac7f21d576f3b417.png" />
 </div>
 </div>
 <p>The output of <a class="reference external" href="https://neuropsychology.github.io/NeuroKit/functions/functions_events.html#events-plot">events_plot()</a> shows the corresponding events in the signal, with the blue dashed line representing a Negative event and red dashed line representing a Neutral event.</p>
@@ -638,11 +638,11 @@ <h2>Manually Extract Event Related Features<a class="headerlink" href="#manually
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>C:\Users\runneradmin\AppData\Local\Temp\ipykernel_5580\4246861920.py:12: FutureWarning: The behavior of obj[i:j] with a float-dtype index is deprecated. In a future version, this will be treated as positional instead of label-based. For label-based slicing, use obj.loc[i:j] instead
+<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>C:\Users\runneradmin\AppData\Local\Temp\ipykernel_928\4246861920.py:12: FutureWarning: The behavior of obj[i:j] with a float-dtype index is deprecated. In a future version, this will be treated as positional instead of label-based. For label-based slicing, use obj.loc[i:j] instead
   ecg_mean = epoch[&quot;ECG_Rate&quot;][0:4].mean()  # Mean heart rate in the 0-4 seconds
-C:\Users\runneradmin\AppData\Local\Temp\ipykernel_5580\4246861920.py:18: FutureWarning: The behavior of obj[i:j] with a float-dtype index is deprecated. In a future version, this will be treated as positional instead of label-based. For label-based slicing, use obj.loc[i:j] instead
+C:\Users\runneradmin\AppData\Local\Temp\ipykernel_928\4246861920.py:18: FutureWarning: The behavior of obj[i:j] with a float-dtype index is deprecated. In a future version, this will be treated as positional instead of label-based. For label-based slicing, use obj.loc[i:j] instead
   rsp_rate = epoch[&quot;RSP_Rate&quot;][0:6].mean()  # Longer window for RSP that has a slower dynamic
-C:\Users\runneradmin\AppData\Local\Temp\ipykernel_5580\4246861920.py:24: FutureWarning: The behavior of obj[i:j] with a float-dtype index is deprecated. In a future version, this will be treated as positional instead of label-based. For label-based slicing, use obj.loc[i:j] instead
+C:\Users\runneradmin\AppData\Local\Temp\ipykernel_928\4246861920.py:24: FutureWarning: The behavior of obj[i:j] with a float-dtype index is deprecated. In a future version, this will be treated as positional instead of label-based. For label-based slicing, use obj.loc[i:j] instead
   scr_max = epoch[&quot;SCR_Amplitude&quot;][0:6].max()  # Maximum SCR peak
 </pre></div>
 </div>

diff --git a/examples/ecg_generate_12leads/ecg_generate_12leads.html b/examples/ecg_generate_12leads/ecg_generate_12leads.html
@@ -478,7 +478,7 @@ <h2>Normal Multi-lead ECG<a class="headerlink" href="#normal-multi-lead-ecg" tit
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../../_images/8e15013448c5dcb4063bc0ebbc7127ff0b409f44a5ea651888b7258e411c24aa.png" src="../../_images/8e15013448c5dcb4063bc0ebbc7127ff0b409f44a5ea651888b7258e411c24aa.png" />
+<img alt="../../_images/0b915b2fd7b77910421a016b9327f196d8041a2c51d67ac309217d858f8598cc.png" src="../../_images/0b915b2fd7b77910421a016b9327f196d8041a2c51d67ac309217d858f8598cc.png" />
 </div>
 </div>
 </section>
@@ -510,7 +510,7 @@ <h2>Abnormal Multi-lead ECG<a class="headerlink" href="#abnormal-multi-lead-ecg"
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../../_images/b9d5357557bca8eb76426cbabc6093d838d7e457b27036663ade8ca8c137c9dd.png" src="../../_images/b9d5357557bca8eb76426cbabc6093d838d7e457b27036663ade8ca8c137c9dd.png" />
+<img alt="../../_images/bf10339b9e6df1812fadc30f613eaf1add40f674a655e2519385af06d7a09269.png" src="../../_images/bf10339b9e6df1812fadc30f613eaf1add40f674a655e2519385af06d7a09269.png" />
 </div>
 </div>
 </section>