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<section id="moabb-analysis-plotting-summary-plot">
<h1>moabb.analysis.plotting.summary_plot<a class="headerlink" href="#moabb-analysis-plotting-summary-plot" title="Link to this heading">#</a></h1>
<dl class="py function">
<dt class="sig sig-object py" id="moabb.analysis.plotting.summary_plot">
<span class="sig-prename descclassname"><span class="pre">moabb.analysis.plotting.</span></span><span class="sig-name descname"><span class="pre">summary_plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sig_df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">effect_df</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p_threshold</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">simplify</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/NeuroTechX/moabb/blob/develop/moabb/analysis/plotting.py#L1039-L1101"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#moabb.analysis.plotting.summary_plot" title="Link to this definition">#</a></dt>
<dd><p>Significance matrix to compare pipelines.</p>
<p>Visualize significances as a heatmap with green/grey/red for significantly
higher/significantly lower.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>sig_df</strong> (<a class="reference external" href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.4)"><code class="xref py py-class docutils literal notranslate"><span class="pre">pandas.DataFrame</span></code></a>) – DataFrame of pipeline x pipeline where each value is a p-value,</p></li>
<li><p><strong>effect_df</strong> (<a class="reference external" href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v3.0.4)"><code class="xref py py-class docutils literal notranslate"><span class="pre">pandas.DataFrame</span></code></a>) – DataFrame where each value is an effect size</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>fig</strong> – Pyplot handle</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference external" href="https://matplotlib.org/stable/api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure" title="(in Matplotlib v3.11.0)"><code class="xref py py-class docutils literal notranslate"><span class="pre">matplotlib.figure.Figure</span></code></a></p>
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<section id="examples-using-moabb-analysis-plotting-summary-plot">
<h2>Examples using <code class="docutils literal notranslate"><span class="pre">moabb.analysis.plotting.summary_plot</span></code><a class="headerlink" href="#examples-using-moabb-analysis-plotting-summary-plot" title="Link to this heading">#</a></h2>
<div class="sphx-glr-thumbnails"><div class="sphx-glr-thumbcontainer" tooltip="This example shows how to use machine learning pipeline based on MNE Epochs instead of Numpy arrays. This is useful to make the most of the MNE code base and to embed EEG specific code inside sklearn pipelines."><img alt="" src="../_images/sphx_glr_plot_mne_and_scikit_estimators_thumb.png" />
<p><a class="reference internal" href="../auto_examples/advanced_examples/plot_mne_and_scikit_estimators.html"><span class="doc">MNE Epochs-based pipelines</span></a></p>
<div class="sphx-glr-thumbnail-title">MNE Epochs-based pipelines</div>
</div><div class="sphx-glr-thumbcontainer" tooltip="The MOABB codebase comes with convenience plotting utilities and some statistical testing. This tutorial focuses on what those exactly are and how they can be used."><img alt="" src="../_images/sphx_glr_plot_statistical_analysis_thumb.png" />
<p><a class="reference internal" href="../auto_examples/advanced_examples/plot_statistical_analysis.html"><span class="doc">Statistical Analysis and Chance Level Assessment</span></a></p>
<div class="sphx-glr-thumbnail-title">Statistical Analysis and Chance Level Assessment</div>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#moabb.analysis.plotting.summary_plot"><code class="docutils literal notranslate"><span class="pre">summary_plot()</span></code></a></li>
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