deploy: braindecode/braindecode@a4c896d

braindecode · Sep 14, 2023 · 914dd31 · 914dd31
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diff --git a/dev/.buildinfo b/dev/.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: 7e0dba6c62bd4c8953e7f5b07fb1f024
+config: 4fbaa04548315a8ff6a67c8a0ecd0345
 tags: 645f666f9bcd5a90fca523b33c5a78b7
diff --git a/dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip b/dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip
diff --git a/dev/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip b/dev/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip
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diff --git a/dev/_images/sphx_glr_plot_sleep_staging_eldele2021_001.png b/dev/_images/sphx_glr_plot_sleep_staging_eldele2021_001.png
diff --git a/dev/_images/sphx_glr_plot_sleep_staging_eldele2021_002.png b/dev/_images/sphx_glr_plot_sleep_staging_eldele2021_002.png
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diff --git a/dev/_images/sphx_glr_plot_sleep_staging_eldele2021_thumb.png b/dev/_images/sphx_glr_plot_sleep_staging_eldele2021_thumb.png
diff --git a/dev/auto_examples/advanced_training/plot_bcic_iv_4_ecog_cropped.html b/dev/auto_examples/advanced_training/plot_bcic_iv_4_ecog_cropped.html
@@ -562,7 +562,7 @@ <h3>Preprocessing<a class="headerlink" href="#preprocessing" title="Link to this
 <a href="../../generated/braindecode.preprocessing.preprocess.html#braindecode.preprocessing.preprocess" title="braindecode.preprocessing.preprocess" class="sphx-glr-backref-module-braindecode-preprocessing sphx-glr-backref-type-py-function"><span class="n">preprocess</span></a><span class="p">(</span><a href="../../generated/braindecode.datasets.BaseConcatDataset.html#braindecode.datasets.BaseConcatDataset" title="braindecode.datasets.BaseConcatDataset" class="sphx-glr-backref-module-braindecode-datasets sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">test_set</span></a><span class="p">,</span> <span class="p">[</span><a href="../../generated/braindecode.preprocessing.Preprocessor.html#braindecode.preprocessing.Preprocessor" title="braindecode.preprocessing.Preprocessor" class="sphx-glr-backref-module-braindecode-preprocessing sphx-glr-backref-type-py-class"><span class="n">Preprocessor</span></a><span class="p">(</span><span class="s1">&#39;crop&#39;</span><span class="p">,</span> <span class="n">tmin</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">tmax</span><span class="o">=</span><span class="mi">24</span><span class="p">)],</span> <span class="n">n_jobs</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span>
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-<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;braindecode.datasets.base.BaseConcatDataset object at 0x7fcd4f8f6590&gt;
+<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f3e756a9d50&gt;
 </pre></div>
 </div>
 <p>In time series targets setup, targets variables are stored in mne.Raw object as channels
@@ -787,14 +787,14 @@ <h2>Training<a class="headerlink" href="#training" title="Link to this heading">
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>  epoch    r2_train    r2_valid    train_loss    valid_loss      lr     dur
 -------  ----------  ----------  ------------  ------------  ------  ------
-      1    -16.9029     -8.3094        2.5378       20.7336  0.0006  0.9189
-      2    -13.7521     -7.1261        1.9596       18.0756  0.0006  0.8176
-      3    -12.7751     -6.7418        1.6787       17.1905  0.0005  0.7472
-      4    -11.7951     -6.3922        1.5638       16.4438  0.0004  0.8314
-      5    -11.2694     -6.1849        1.4237       16.0117  0.0002  0.8151
-      6    -10.5718     -5.9210        1.3549       15.4452  0.0001  0.8145
-      7     -9.8213     -5.6187        1.3132       14.7814  0.0000  0.8244
-      8     -9.0630     -5.3052        1.3316       14.0897  0.0000  0.8003
+      1    -16.9036     -8.3098        2.5378       20.7346  0.0006  0.7752
+      2    -13.7536     -7.1257        1.9596       18.0738  0.0006  0.6932
+      3    -12.7769     -6.7413        1.6787       17.1885  0.0005  0.6387
+      4    -11.7973     -6.3917        1.5638       16.4416  0.0004  0.6577
+      5    -11.2718     -6.1846        1.4237       16.0097  0.0002  0.6656
+      6    -10.5742     -5.9208        1.3549       15.4435  0.0001  0.6529
+      7     -9.8235     -5.6185        1.3132       14.7799  0.0000  0.6666
+      8     -9.0649     -5.3051        1.3316       14.0883  0.0000  0.6176
 </pre></div>
 </div>
 <p>Obtaining predictions and targets for the test, train, and validation dataset</p>
@@ -909,8 +909,8 @@ <h2>Plot Results<a class="headerlink" href="#plot-results" title="Link to this h
 <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.tight_layout.html#matplotlib.pyplot.tight_layout" title="matplotlib.pyplot.tight_layout" class="sphx-glr-backref-module-matplotlib-pyplot sphx-glr-backref-type-py-function"><span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span></a><span class="p">()</span>
 </pre></div>
 </div>
-<img src="../../_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_002.png" srcset="../../_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_002.png" alt="plot bcic iv 4 ecog cropped" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 23.521 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  790 MB</p>
+<img src="../../_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_002.png" srcset="../../_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_002.png" alt="plot bcic iv 4 ecog cropped" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 20.447 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  829 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-advanced-training-plot-bcic-iv-4-ecog-cropped-py">
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diff --git a/dev/auto_examples/advanced_training/plot_data_augmentation.html b/dev/auto_examples/advanced_training/plot_data_augmentation.html
@@ -549,7 +549,7 @@ <h3><a class="toc-backref" href="#id3" role="doc-backlink">Preprocessing</a><a c
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/home/runner/work/braindecode/braindecode/braindecode/preprocessing/preprocess.py:55: UserWarning: Preprocessing choices with lambda functions cannot be saved.
   warn(&#39;Preprocessing choices with lambda functions cannot be saved.&#39;)
 
-&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7fcd4f8734c0&gt;
+&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f3e6cc44250&gt;
 </pre></div>
 </div>
 </section>
@@ -745,10 +745,10 @@ <h3><a class="toc-backref" href="#id10" role="doc-backlink">Create an EEGClassif
 </div>
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>  epoch    train_accuracy    train_loss    valid_accuracy    valid_loss      lr     dur
 -------  ----------------  ------------  ----------------  ------------  ------  ------
-      1            0.2535        1.6458            0.2535        5.1252  0.0006  3.2541
-      2            0.2639        1.3297            0.2500        5.7606  0.0005  2.9900
-      3            0.2639        1.1539            0.2500        5.1230  0.0002  2.9194
-      4            0.2708        1.1567            0.2535        4.2554  0.0000  2.9887
+      1            0.2535        1.6458            0.2535        5.1251  0.0006  2.9583
+      2            0.2639        1.3297            0.2500        5.7606  0.0005  2.5712
+      3            0.2639        1.1539            0.2500        5.1230  0.0002  2.6512
+      4            0.2708        1.1567            0.2535        4.2554  0.0000  2.7674
 
 &lt;class &#39;braindecode.classifier.EEGClassifier&#39;&gt;[initialized](
   module_=============================================================================================================================================
@@ -801,8 +801,8 @@ <h3><a class="toc-backref" href="#id12" role="doc-backlink">Setting the data aug
 <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><a href="../../generated/braindecode.datasets.BaseConcatDataset.html#braindecode.datasets.BaseConcatDataset" title="braindecode.datasets.BaseConcatDataset" class="sphx-glr-backref-module-braindecode-datasets sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">train_set</span></a><span class="o">.</span><a href="../../generated/braindecode.augmentation.FrequencyShift.html#braindecode.augmentation.FrequencyShift" title="braindecode.augmentation.FrequencyShift" class="sphx-glr-backref-module-braindecode-augmentation sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">transform</span></a> <span class="o">=</span> <a href="../../generated/braindecode.augmentation.Compose.html#braindecode.augmentation.Compose" title="braindecode.augmentation.Compose" class="sphx-glr-backref-module-braindecode-augmentation sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">composed_transforms</span></a>
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-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 27.533 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  137 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 24.567 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  56 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-advanced-training-plot-data-augmentation-py">
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 <p><a class="reference download internal" download="" href="../../_downloads/e3845395de44913c970dbf26671a7cba/plot_data_augmentation.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_data_augmentation.py</span></code></a></p>

diff --git a/dev/auto_examples/advanced_training/plot_data_augmentation_search.html b/dev/auto_examples/advanced_training/plot_data_augmentation_search.html
@@ -570,7 +570,7 @@ <h3><a class="toc-backref" href="#id10" role="doc-backlink">Preprocessing</a><a
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>/home/runner/work/braindecode/braindecode/braindecode/preprocessing/preprocess.py:55: UserWarning: Preprocessing choices with lambda functions cannot be saved.
   warn(&#39;Preprocessing choices with lambda functions cannot be saved.&#39;)
 
-&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7fcd4f724e20&gt;
+&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f3e6edea5f0&gt;
 </pre></div>
 </div>
 </section>
@@ -918,8 +918,8 @@ <h3><a class="toc-backref" href="#id19" role="doc-backlink">References</a><a cla
 Journal of Neural Engineering, 18(4), 046020.</p>
 </aside>
 </aside>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (1 minutes 6.976 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  106 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 59.261 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  68 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-advanced-training-plot-data-augmentation-search-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/0f763ae384277e558103757157e170fb/plot_data_augmentation_search.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_data_augmentation_search.py</span></code></a></p>