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  <div class="section" id="directed-laplacian-matrix">
<h1>directed_laplacian_matrix<a class="headerlink" href="#directed-laplacian-matrix" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="networkx.linalg.laplacianmatrix.directed_laplacian_matrix">
<tt class="descname">directed_laplacian_matrix</tt><big>(</big><em>G</em>, <em>nodelist=None</em>, <em>weight='weight'</em>, <em>walk_type=None</em>, <em>alpha=0.95</em><big>)</big><a class="reference internal" href="../../_modules/networkx/linalg/laplacianmatrix.html#directed_laplacian_matrix"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#networkx.linalg.laplacianmatrix.directed_laplacian_matrix" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the directed Laplacian matrix of G.</p>
<p>The graph directed Laplacian is the matrix</p>
<div class="math">
<p><span class="math">L = I - (\Phi^{1/2} P \Phi^{-1/2} + \Phi^{-1/2} P^T \Phi^{1/2} ) / 2</span></p>
</div><p>where <span class="math">I</span> is the identity matrix, <span class="math">P</span> is the transition matrix of the
graph, and <span class="math">\Phi</span> a matrix with the Perron vector of <span class="math">P</span> in the diagonal and
zeros elsewhere.</p>
<p>Depending on the value of walk_type, <span class="math">P</span> can be the transition matrix
induced by a random walk, a lazy random walk, or a random walk with
teleportation (PageRank).</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters :</th><td class="field-body"><p class="first"><strong>G</strong> : DiGraph</p>
<blockquote>
<div><p>A NetworkX graph</p>
</div></blockquote>
<p><strong>nodelist</strong> : list, optional</p>
<blockquote>
<div><p>The rows and columns are ordered according to the nodes in nodelist.
If nodelist is None, then the ordering is produced by G.nodes().</p>
</div></blockquote>
<p><strong>weight</strong> : string or None, optional (default=&#8217;weight&#8217;)</p>
<blockquote>
<div><p>The edge data key used to compute each value in the matrix.
If None, then each edge has weight 1.</p>
</div></blockquote>
<p><strong>walk_type</strong> : string or None, optional (default=None)</p>
<blockquote>
<div><p>If None, <span class="math">P</span> is selected depending on the properties of the
graph. Otherwise is one of &#8216;random&#8217;, &#8216;lazy&#8217;, or &#8216;pagerank&#8217;</p>
</div></blockquote>
<p><strong>alpha</strong> : real</p>
<blockquote>
<div><p>(1 - alpha) is the teleportation probability used with pagerank</p>
</div></blockquote>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns :</th><td class="field-body"><p class="first"><strong>L</strong> : NumPy array</p>
<blockquote>
<div><p>Normalized Laplacian of G.</p>
</div></blockquote>
</td>
</tr>
<tr class="field-odd field"><th class="field-name">Raises :</th><td class="field-body"><p class="first"><strong>NetworkXError</strong> :</p>
<blockquote>
<div><p>If NumPy cannot be imported</p>
</div></blockquote>
<p><strong>NetworkXNotImplemnted</strong> :</p>
<blockquote class="last">
<div><p>If G is not a DiGraph</p>
</div></blockquote>
</td>
</tr>
</tbody>
</table>
<div class="admonition-see-also admonition seealso">
<p class="first admonition-title">See also</p>
<p class="last"><a class="reference internal" href="networkx.linalg.laplacianmatrix.laplacian_matrix.html#networkx.linalg.laplacianmatrix.laplacian_matrix" title="networkx.linalg.laplacianmatrix.laplacian_matrix"><tt class="xref py py-obj docutils literal"><span class="pre">laplacian_matrix</span></tt></a></p>
</div>
<p class="rubric">Notes</p>
<p>Only implemented for DiGraphs</p>
<p class="rubric">References</p>
<table class="docutils citation" frame="void" id="r293" rules="none">
<colgroup><col class="label" /><col /></colgroup>
<tbody valign="top">
<tr><td class="label"><a class="fn-backref" href="#id1">[R293]</a></td><td>Fan Chung (2005).
Laplacians and the Cheeger inequality for directed graphs.
Annals of Combinatorics, 9(1), 2005</td></tr>
</tbody>
</table>
</dd></dl>

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