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to download the full example code or to run this example in your browser via JupyterLite or Binder</p>
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<section class="sphx-glr-example-title" id="a-demo-of-the-spectral-co-clustering-algorithm">
<span id="sphx-glr-auto-examples-bicluster-plot-spectral-coclustering-py"></span><h1>A demo of the Spectral Co-Clustering algorithm<a class="headerlink" href="#a-demo-of-the-spectral-co-clustering-algorithm" title="Link to this heading">¶</a></h1>
<p>This example demonstrates how to generate a dataset and bicluster it
using the Spectral Co-Clustering algorithm.</p>
<p>The dataset is generated using the <code class="docutils literal notranslate"><span class="pre">make_biclusters</span></code> function, which
creates a matrix of small values and implants bicluster with large
values. The rows and columns are then shuffled and passed to the
Spectral Co-Clustering algorithm. Rearranging the shuffled matrix to
make biclusters contiguous shows how accurately the algorithm found
the biclusters.</p>
<ul class="sphx-glr-horizontal">
<li><img src="../../_images/sphx_glr_plot_spectral_coclustering_001.png" srcset="../../_images/sphx_glr_plot_spectral_coclustering_001.png" alt="Original dataset" class = "sphx-glr-multi-img"/></li>
<li><img src="../../_images/sphx_glr_plot_spectral_coclustering_002.png" srcset="../../_images/sphx_glr_plot_spectral_coclustering_002.png" alt="Shuffled dataset" class = "sphx-glr-multi-img"/></li>
<li><img src="../../_images/sphx_glr_plot_spectral_coclustering_003.png" srcset="../../_images/sphx_glr_plot_spectral_coclustering_003.png" alt="After biclustering; rearranged to show biclusters" class = "sphx-glr-multi-img"/></li>
</ul>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>consensus score: 1.000
</pre></div>
</div>
<div class="line-block">
<div class="line"><br /></div>
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<div class="highlight-Python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Author: Kemal Eren <[email protected]></span>
<span class="c1"># License: BSD 3 clause</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">matplotlib</span> <span class="kn">import</span> <span class="n">pyplot</span> <span class="k">as</span> <span class="n">plt</span>
<span class="kn">from</span> <span class="nn">sklearn.cluster</span> <span class="kn">import</span> <a href="../../modules/generated/sklearn.cluster.SpectralCoclustering.html#sklearn.cluster.SpectralCoclustering" title="sklearn.cluster.SpectralCoclustering" class="sphx-glr-backref-module-sklearn-cluster sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">SpectralCoclustering</span></a>
<span class="kn">from</span> <span class="nn">sklearn.datasets</span> <span class="kn">import</span> <a href="../../modules/generated/sklearn.datasets.make_biclusters.html#sklearn.datasets.make_biclusters" title="sklearn.datasets.make_biclusters" class="sphx-glr-backref-module-sklearn-datasets sphx-glr-backref-type-py-function"><span class="n">make_biclusters</span></a>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="kn">import</span> <a href="../../modules/generated/sklearn.metrics.consensus_score.html#sklearn.metrics.consensus_score" title="sklearn.metrics.consensus_score" class="sphx-glr-backref-module-sklearn-metrics sphx-glr-backref-type-py-function"><span class="n">consensus_score</span></a>
<span class="n">data</span><span class="p">,</span> <span class="n">rows</span><span class="p">,</span> <span class="n">columns</span> <span class="o">=</span> <a href="../../modules/generated/sklearn.datasets.make_biclusters.html#sklearn.datasets.make_biclusters" title="sklearn.datasets.make_biclusters" class="sphx-glr-backref-module-sklearn-datasets sphx-glr-backref-type-py-function"><span class="n">make_biclusters</span></a><span class="p">(</span>
<span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="mi">300</span><span class="p">,</span> <span class="mi">300</span><span class="p">),</span> <span class="n">n_clusters</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">noise</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">0</span>
<span class="p">)</span>
<a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.matshow.html#matplotlib.pyplot.matshow" title="matplotlib.pyplot.matshow" 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">matshow</span></a><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">cm</span><span class="o">.</span><span class="n">Blues</span><span class="p">)</span>
<a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.title.html#matplotlib.pyplot.title" title="matplotlib.pyplot.title" 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">title</span></a><span class="p">(</span><span class="s2">"Original dataset"</span><span class="p">)</span>
<span class="c1"># shuffle clusters</span>
<span class="n">rng</span> <span class="o">=</span> <a href="https://numpy.org/doc/stable/reference/random/legacy.html#numpy.random.RandomState" title="numpy.random.RandomState" class="sphx-glr-backref-module-numpy-random sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">RandomState</span></a><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
<span class="n">row_idx</span> <span class="o">=</span> <span class="n">rng</span><span class="o">.</span><span class="n">permutation</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
<span class="n">col_idx</span> <span class="o">=</span> <span class="n">rng</span><span class="o">.</span><span class="n">permutation</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">row_idx</span><span class="p">][:,</span> <span class="n">col_idx</span><span class="p">]</span>
<a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.matshow.html#matplotlib.pyplot.matshow" title="matplotlib.pyplot.matshow" 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">matshow</span></a><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">cm</span><span class="o">.</span><span class="n">Blues</span><span class="p">)</span>
<a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.title.html#matplotlib.pyplot.title" title="matplotlib.pyplot.title" 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">title</span></a><span class="p">(</span><span class="s2">"Shuffled dataset"</span><span class="p">)</span>
<span class="n">model</span> <span class="o">=</span> <a href="../../modules/generated/sklearn.cluster.SpectralCoclustering.html#sklearn.cluster.SpectralCoclustering" title="sklearn.cluster.SpectralCoclustering" class="sphx-glr-backref-module-sklearn-cluster sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">SpectralCoclustering</span></a><span class="p">(</span><span class="n">n_clusters</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
<span class="n">score</span> <span class="o">=</span> <a href="../../modules/generated/sklearn.metrics.consensus_score.html#sklearn.metrics.consensus_score" title="sklearn.metrics.consensus_score" class="sphx-glr-backref-module-sklearn-metrics sphx-glr-backref-type-py-function"><span class="n">consensus_score</span></a><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">biclusters_</span><span class="p">,</span> <span class="p">(</span><span class="n">rows</span><span class="p">[:,</span> <span class="n">row_idx</span><span class="p">],</span> <span class="n">columns</span><span class="p">[:,</span> <span class="n">col_idx</span><span class="p">]))</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">"consensus score: </span><span class="si">{:.3f}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">score</span><span class="p">))</span>
<span class="n">fit_data</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><a href="https://numpy.org/doc/stable/reference/generated/numpy.argsort.html#numpy.argsort" title="numpy.argsort" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-function"><span class="n">np</span><span class="o">.</span><span class="n">argsort</span></a><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">row_labels_</span><span class="p">)]</span>
<span class="n">fit_data</span> <span class="o">=</span> <span class="n">fit_data</span><span class="p">[:,</span> <a href="https://numpy.org/doc/stable/reference/generated/numpy.argsort.html#numpy.argsort" title="numpy.argsort" class="sphx-glr-backref-module-numpy sphx-glr-backref-type-py-function"><span class="n">np</span><span class="o">.</span><span class="n">argsort</span></a><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">column_labels_</span><span class="p">)]</span>
<a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.matshow.html#matplotlib.pyplot.matshow" title="matplotlib.pyplot.matshow" 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">matshow</span></a><span class="p">(</span><span class="n">fit_data</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">cm</span><span class="o">.</span><span class="n">Blues</span><span class="p">)</span>
<a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.title.html#matplotlib.pyplot.title" title="matplotlib.pyplot.title" 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">title</span></a><span class="p">(</span><span class="s2">"After biclustering; rearranged to show biclusters"</span><span class="p">)</span>
<a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.show.html#matplotlib.pyplot.show" title="matplotlib.pyplot.show" 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">show</span></a><span class="p">()</span>
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<p class="rubric">Related examples</p>
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<p><a class="reference internal" href="plot_spectral_biclustering.html#sphx-glr-auto-examples-bicluster-plot-spectral-biclustering-py"><span class="std std-ref">A demo of the Spectral Biclustering algorithm</span></a></p>
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<div class="sphx-glr-thumbnail-title">Segmenting the picture of greek coins in regions</div>
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<p><a class="reference internal" href="../cluster/plot_agglomerative_clustering_metrics.html#sphx-glr-auto-examples-cluster-plot-agglomerative-clustering-metrics-py"><span class="std std-ref">Agglomerative clustering with different metrics</span></a></p>
<div class="sphx-glr-thumbnail-title">Agglomerative clustering with different metrics</div>
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