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<section id="module-networkit.correlation">

<span id="networkit-correlation"></span><h1>networkit.correlation<a class="headerlink" href="#module-networkit.correlation" title="Link to this heading">¶</a></h1>

<dl class="py class">

<dt class="sig sig-object py" id="networkit.correlation.Assortativity">

<span class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></span><span class="sig-prename descclassname"><span class="pre">networkit.correlation.</span></span><span class="sig-name descname"><span class="pre">Assortativity</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">G</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#networkit.correlation.Assortativity" title="Link to this definition">¶</a></dt>

<dd><p>Bases: <a class="reference internal" href="base.html#networkit.base.Algorithm" title="networkit.base.Algorithm"><code class="xref py py-class docutils literal notranslate"><span class="pre">Algorithm</span></code></a></p>

<p>Assortativity computes a coefficient that expresses the correlation of a

node attribute among connected pairs of nodes.</p>

<p>For a partition of the node set (a nominal attribute), the coefficient is

computed from the mixing matrix e, where e_ij is the fraction of edge counts

from nodes in subset i to nodes in subset j. In undirected graphs, each edge

{u, v} with u != v is counted once in each direction and each self-loop is

counted once, and the mixing matrix is normalized by the total of these

counts (2m minus the number of self-loops). In directed graphs, each edge is

counted once and the matrix is normalized by m.</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>G</strong> (<em>networkit.graph</em>) – The input graph.</p></li>

<li><p><strong>data</strong> (<em>list</em><em>(</em><em>float</em><em>) or </em><em>networkit.Partition</em>) – Numerical node value array, or a partition of the node set.</p></li>

<dl class="py method">

<dt class="sig sig-object py" id="networkit.correlation.Assortativity.getCoefficient">

<span class="sig-name descname"><span class="pre">getCoefficient</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#networkit.correlation.Assortativity.getCoefficient" title="Link to this definition">¶</a></dt>

<dd><p>Return the assortativity coefficient.</p>

<dl class="field-list simple">

<dt class="field-odd">Returns<span class="colon">:</span></dt>

<dd class="field-odd"><p>The assortativity coefficient.</p>

<dt class="field-even">Return type<span class="colon">:</span></dt>

<dd class="field-even"><p>float</p>

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