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Expand Up @@ -599,7 +599,7 @@ <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="s2">&quot;crop&quot;</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>
</pre></div>
</div>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;braindecode.datasets.base.BaseConcatDataset object at 0x7f27a32f55d0&gt;
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>&lt;braindecode.datasets.base.BaseConcatDataset object at 0x7fe24a8a8640&gt;
</pre></div>
</div>
<p>In time series targets setup, targets variables are stored in mne.Raw object as channels
Expand Down Expand Up @@ -836,14 +836,14 @@ <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 -16.9037 -8.3086 2.5378 20.7324 0.0006 0.4711
2 -13.7539 -7.1244 1.9596 18.0720 0.0006 0.4451
3 -12.7768 -6.7402 1.6787 17.1870 0.0005 0.4086
4 -11.7970 -6.3910 1.5638 16.4409 0.0004 0.4163
5 -11.2712 -6.1840 1.4237 16.0095 0.0002 0.4089
6 -10.5735 -5.9203 1.3549 15.4436 0.0001 0.4128
7 -9.8228 -5.6181 1.3132 14.7799 0.0000 0.4082
8 -9.0643 -5.3047 1.3316 14.0884 0.0000 0.4110
1 -16.9037 -8.3086 2.5378 20.7324 0.0006 0.5100
2 -13.7539 -7.1244 1.9596 18.0720 0.0006 0.4214
3 -12.7768 -6.7402 1.6787 17.1870 0.0005 0.4431
4 -11.7970 -6.3910 1.5638 16.4409 0.0004 0.4088
5 -11.2712 -6.1840 1.4237 16.0095 0.0002 0.4161
6 -10.5735 -5.9203 1.3549 15.4436 0.0001 0.4098
7 -9.8228 -5.6181 1.3132 14.7799 0.0000 0.4127
8 -9.0643 -5.3047 1.3316 14.0884 0.0000 0.4095
</pre></div>
</div>
<p>Obtaining predictions and targets for the test, train, and validation dataset</p>
Expand Down Expand Up @@ -964,8 +964,8 @@ <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> (1 minutes 28.314 seconds)</p>
<p><strong>Estimated memory usage:</strong> 845 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> (2 minutes 23.158 seconds)</p>
<p><strong>Estimated memory usage:</strong> 727 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">
<div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/10fc813a8f78253f4bf301264950f5c1/plot_bcic_iv_4_ecog_cropped.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">plot_bcic_iv_4_ecog_cropped.ipynb</span></code></a></p>
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12 changes: 6 additions & 6 deletions dev/auto_examples/advanced_training/plot_data_augmentation.html
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Expand Up @@ -593,7 +593,7 @@ <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:69: UserWarning: Preprocessing choices with lambda functions cannot be saved.
warn(&quot;Preprocessing choices with lambda functions cannot be saved.&quot;)

&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f28611277f0&gt;
&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7fe31917f7f0&gt;
</pre></div>
</div>
</section>
Expand Down Expand Up @@ -789,10 +789,10 @@ <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_acc valid_accuracy valid_loss lr dur
------- ---------------- ------------ ----------- ---------------- ------------ ------ ------
1 0.2535 1.6458 0.2535 0.2535 5.1252 0.0006 1.7128
2 0.2639 1.3297 0.2500 0.2500 5.7607 0.0005 1.5511
1 0.2535 1.6458 0.2535 0.2535 5.1252 0.0006 1.7214
2 0.2639 1.3297 0.2500 0.2500 5.7607 0.0005 1.5493
3 0.2639 1.1539 0.2500 0.2500 5.1231 0.0002 1.5485
4 0.2708 1.1567 0.2535 0.2535 4.2555 0.0000 1.5301
4 0.2708 1.1567 0.2535 0.2535 4.2555 0.0000 1.5377

&lt;class &#39;braindecode.classifier.EEGClassifier&#39;&gt;[initialized](
module_=============================================================================================================================================
Expand Down Expand Up @@ -846,8 +846,8 @@ <h3><a class="toc-backref" href="#id12" role="doc-backlink">Setting the data aug
<div class="highlight-Python 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>
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 17.265 seconds)</p>
<p><strong>Estimated memory usage:</strong> 316 MB</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 17.647 seconds)</p>
<p><strong>Estimated memory usage:</strong> 506 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">
<div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/1d879df548fa18be8c23d9ca0dc008d4/plot_data_augmentation.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">plot_data_augmentation.ipynb</span></code></a></p>
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Expand Up @@ -614,7 +614,7 @@ <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:69: UserWarning: Preprocessing choices with lambda functions cannot be saved.
warn(&quot;Preprocessing choices with lambda functions cannot be saved.&quot;)

&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7f27a037da80&gt;
&lt;braindecode.datasets.moabb.MOABBDataset object at 0x7fe2417186a0&gt;
</pre></div>
</div>
</section>
Expand Down Expand Up @@ -1385,8 +1385,8 @@ <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> (0 minutes 32.152 seconds)</p>
<p><strong>Estimated memory usage:</strong> 67 MB</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 32.158 seconds)</p>
<p><strong>Estimated memory usage:</strong> 394 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-jupyter docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/2466f8ec5c733d0bd65e187b45d875cc/plot_data_augmentation_search.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">plot_data_augmentation_search.ipynb</span></code></a></p>
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