CircleCI update of dev docs (141).

Author: Circle CI

.nojekyll

@@ -37,10 +37,10 @@ Example using Skorch for crop decoding
     0 bad epochs dropped
       epoch    train_loss    train_trial_accuracy    valid_loss    valid_trial_accuracy     dur
     -------  ------------  ----------------------  ------------  ----------------------  ------
-          1        [36m1.3460[0m                  [32m0.8250[0m        [35m0.7710[0m                  [31m0.6333[0m  1.1264
-          2        [36m0.6829[0m                  [32m0.8750[0m        [35m0.5806[0m                  [31m0.6667[0m  0.6228
-          3        [36m0.4439[0m                  [32m0.9500[0m        [35m0.5148[0m                  [31m0.7667[0m  0.6124
-          4        [36m0.3396[0m                  [32m0.9750[0m        [35m0.5103[0m                  0.7333  0.6796
+          1        [36m1.3460[0m                  [32m0.8250[0m        [35m0.7710[0m                  [31m0.6333[0m  1.1377
+          2        [36m0.6829[0m                  [32m0.8750[0m        [35m0.5806[0m                  [31m0.6667[0m  0.6176
+          3        [36m0.4439[0m                  [32m0.9500[0m        [35m0.5148[0m                  [31m0.7667[0m  0.5901
+          4        [36m0.3396[0m                  [32m0.9750[0m        [35m0.5103[0m                  0.7333  0.6511
 
     array([[[-0.72593135, -0.70480764, -0.6929935 , -0.6789333 ,
              -0.6795268 , -0.6565    , -0.62472534, -0.59308964,
@@ -377,9 +377,9 @@ Example using Skorch for crop decoding
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  4.820 seconds)
+   **Total running time of the script:** ( 0 minutes  4.649 seconds)
 
-**Estimated memory usage:**  579 MB
+**Estimated memory usage:**  574 MB
 
 
 .. _sphx_glr_download_auto_examples_plot_skorch_crop_decoding.py:

_downloads/a21695eab6dbdfc1b8a516b90e3cd65e/auto_examples_python.zip

@@ -39,10 +39,10 @@ Example using Skorch - How do you think?
     0 bad epochs dropped
       epoch    train_acc    train_f1    train_loss    valid_loss     dur
     -------  -----------  ----------  ------------  ------------  ------
-          1       [36m0.8000[0m      [32m0.7778[0m        [35m1.1775[0m        [31m0.6880[0m  0.6333
-          2       [36m0.8250[0m      [32m0.8205[0m        [35m0.5595[0m        [31m0.6071[0m  0.6065
-          3       [36m0.8750[0m      [32m0.8718[0m        0.6315        [31m0.5475[0m  0.5867
-          4       [36m0.9250[0m      [32m0.9268[0m        [35m0.4493[0m        [31m0.4362[0m  0.5290
+          1       [36m0.8000[0m      [32m0.7778[0m        [35m1.1775[0m        [31m0.6880[0m  0.6750
+          2       [36m0.8250[0m      [32m0.8205[0m        [35m0.5595[0m        [31m0.6071[0m  0.5330
+          3       [36m0.8750[0m      [32m0.8718[0m        0.6315        [31m0.5475[0m  0.5894
+          4       [36m0.9250[0m      [32m0.9268[0m        [35m0.4493[0m        [31m0.4362[0m  0.5836
 
     0.6666666666666665
 
@@ -214,9 +214,9 @@ Example using Skorch - How do you think?
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  5.108 seconds)
+   **Total running time of the script:** ( 0 minutes  4.659 seconds)
 
-**Estimated memory usage:**  1096 MB
+**Estimated memory usage:**  1099 MB
 
 
 .. _sphx_glr_download_auto_examples_plot_skorch_trial_decoding.py:

_downloads/dd2d38fd333ad9ede30d30d420e9db7f/auto_examples_jupyter.zip

@@ -5,12 +5,12 @@
 
 Computation times
 =================
-**00:09.928** total execution time for **auto_examples** files:
+**00:09.308** total execution time for **auto_examples** files:
 
 +-------------------------------------------------------------------------------------------------+-----------+-----------+
-| :ref:`sphx_glr_auto_examples_plot_skorch_trial_decoding.py` (``plot_skorch_trial_decoding.py``) | 00:05.108 | 1096.0 MB |
+| :ref:`sphx_glr_auto_examples_plot_skorch_trial_decoding.py` (``plot_skorch_trial_decoding.py``) | 00:04.659 | 1099.2 MB |
 +-------------------------------------------------------------------------------------------------+-----------+-----------+
-| :ref:`sphx_glr_auto_examples_plot_skorch_crop_decoding.py` (``plot_skorch_crop_decoding.py``)   | 00:04.820 | 579.4 MB  |
+| :ref:`sphx_glr_auto_examples_plot_skorch_crop_decoding.py` (``plot_skorch_crop_decoding.py``)   | 00:04.649 | 574.0 MB  |
 +-------------------------------------------------------------------------------------------------+-----------+-----------+
 | :ref:`sphx_glr_auto_examples_perturbation.py` (``perturbation.py``)                             | 00:00.000 | 0.0 MB    |
 +-------------------------------------------------------------------------------------------------+-----------+-----------+

_sources/auto_examples/plot_skorch_crop_decoding.rst.txt

@@ -183,10 +183,10 @@
 0 bad epochs dropped
   epoch    train_loss    train_trial_accuracy    valid_loss    valid_trial_accuracy     dur
 -------  ------------  ----------------------  ------------  ----------------------  ------
-      1        [36m1.3460[0m                  [32m0.8250[0m        [35m0.7710[0m                  [31m0.6333[0m  1.1264
-      2        [36m0.6829[0m                  [32m0.8750[0m        [35m0.5806[0m                  [31m0.6667[0m  0.6228
-      3        [36m0.4439[0m                  [32m0.9500[0m        [35m0.5148[0m                  [31m0.7667[0m  0.6124
-      4        [36m0.3396[0m                  [32m0.9750[0m        [35m0.5103[0m                  0.7333  0.6796
+      1        [36m1.3460[0m                  [32m0.8250[0m        [35m0.7710[0m                  [31m0.6333[0m  1.1377
+      2        [36m0.6829[0m                  [32m0.8750[0m        [35m0.5806[0m                  [31m0.6667[0m  0.6176
+      3        [36m0.4439[0m                  [32m0.9500[0m        [35m0.5148[0m                  [31m0.7667[0m  0.5901
+      4        [36m0.3396[0m                  [32m0.9750[0m        [35m0.5103[0m                  0.7333  0.6511
 
 array([[[-0.72593135, -0.70480764, -0.6929935 , -0.6789333 ,
          -0.6795268 , -0.6565    , -0.62472534, -0.59308964,
@@ -515,8 +515,8 @@
 <span class="n">clf</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">test_set</span><span class="p">)</span>
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes  4.820 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  579 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes  4.649 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  574 MB</p>
 <div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-skorch-crop-decoding-py">
 <div class="sphx-glr-download docutils container">
 <p><a class="reference download internal" download="" href="../_downloads/670da2e3c15b098b126fadb9f3097635/plot_skorch_crop_decoding.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_skorch_crop_decoding.py</span></code></a></p>

_sources/auto_examples/plot_skorch_trial_decoding.rst.txt

@@ -185,10 +185,10 @@
 0 bad epochs dropped
   epoch    train_acc    train_f1    train_loss    valid_loss     dur
 -------  -----------  ----------  ------------  ------------  ------
-      1       [36m0.8000[0m      [32m0.7778[0m        [35m1.1775[0m        [31m0.6880[0m  0.6333
-      2       [36m0.8250[0m      [32m0.8205[0m        [35m0.5595[0m        [31m0.6071[0m  0.6065
-      3       [36m0.8750[0m      [32m0.8718[0m        0.6315        [31m0.5475[0m  0.5867
-      4       [36m0.9250[0m      [32m0.9268[0m        [35m0.4493[0m        [31m0.4362[0m  0.5290
+      1       [36m0.8000[0m      [32m0.7778[0m        [35m1.1775[0m        [31m0.6880[0m  0.6750
+      2       [36m0.8250[0m      [32m0.8205[0m        [35m0.5595[0m        [31m0.6071[0m  0.5330
+      3       [36m0.8750[0m      [32m0.8718[0m        0.6315        [31m0.5475[0m  0.5894
+      4       [36m0.9250[0m      [32m0.9268[0m        [35m0.4493[0m        [31m0.4362[0m  0.5836
 
 0.6666666666666665
 </pre></div>
@@ -352,8 +352,8 @@
 <a href="https://scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html#sklearn.metrics.f1_score" title="sklearn.metrics.f1_score" class="sphx-glr-backref-module-sklearn-metrics sphx-glr-backref-type-py-function"><span class="n">f1_score</span></a><span class="p">(</span><a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">y_true</span></a><span class="p">,</span> <a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">preds</span></a><span class="p">)</span>
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes  5.108 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  1096 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes  4.659 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  1099 MB</p>
 <div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-skorch-trial-decoding-py">
 <div class="sphx-glr-download docutils container">
 <p><a class="reference download internal" download="" href="../_downloads/bcae24c39d32e42533e9fad57dd2a90d/plot_skorch_trial_decoding.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_skorch_trial_decoding.py</span></code></a></p>

_sources/auto_examples/sg_execution_times.rst.txt

@@ -154,7 +154,7 @@
 
   <div class="section" id="computation-times">
 <span id="sphx-glr-auto-examples-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline">¶</a></h1>
-<p><strong>00:09.928</strong> total execution time for <strong>auto_examples</strong> files:</p>
+<p><strong>00:09.308</strong> total execution time for <strong>auto_examples</strong> files:</p>
 <table class="docutils align-default">
 <colgroup>
 <col style="width: 82%" />
@@ -163,12 +163,12 @@
 </colgroup>
 <tbody>
 <tr class="row-odd"><td><p><a class="reference internal" href="plot_skorch_trial_decoding.html#sphx-glr-auto-examples-plot-skorch-trial-decoding-py"><span class="std std-ref">Skorch Trialwise Decoding</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_skorch_trial_decoding.py</span></code>)</p></td>
-<td><p>00:05.108</p></td>
-<td><p>1096.0 MB</p></td>
+<td><p>00:04.659</p></td>
+<td><p>1099.2 MB</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="plot_skorch_crop_decoding.html#sphx-glr-auto-examples-plot-skorch-crop-decoding-py"><span class="std std-ref">Skorch Crop Decoding</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_skorch_crop_decoding.py</span></code>)</p></td>
-<td><p>00:04.820</p></td>
-<td><p>579.4 MB</p></td>
+<td><p>00:04.649</p></td>
+<td><p>574.0 MB</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="perturbation.html#sphx-glr-auto-examples-perturbation-py"><span class="std std-ref">Amplitude Perturbation Visualization</span></a> (<code class="docutils literal notranslate"><span class="pre">perturbation.py</span></code>)</p></td>
 <td><p>00:00.000</p></td>