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- <title>Function betweenness_centrality_clustering</title>
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- <div class="refnamediv">
- <IMG SRC="../../../boost.png"
- ALT="C++ Boost" width="277" height="86">
- <h1><img src="figs/python.gif" alt="(Python)"/><span class="refentrytitle">Function
- betweenness_centrality_clustering</span></h1>
- <p>boost::betweenness_centrality_clustering — Graph
- clustering based on edge betweenness centrality.</p>
- </div>
- <h2 xmlns:rev=
- "http://www.cs.rpi.edu/~gregod/boost/tools/doc/revision" class=
- "refsynopsisdiv-title">Synopsis</h2>
- <div xmlns:rev=
- "http://www.cs.rpi.edu/~gregod/boost/tools/doc/revision" class=
- "refsynopsisdiv">
- <pre class="synopsis">
- <span class="bold"><b>template</b></span><<span class=
- "bold"><b>typename</b></span> MutableGraph, <span class=
- "bold"><b>typename</b></span> Done, <span class=
- "bold"><b>typename</b></span> EdgeCentralityMap,
- <span class=
- "bold"><b>typename</b></span> VertexIndexMap>
- <span class="type"><span class=
- "bold"><b>void</b></span></span> betweenness_centrality_clustering(MutableGraph & g, Done done,
- EdgeCentralityMap edge_centrality,
- VertexIndexMap vertex_index);
- <span class="bold"><b>template</b></span><<span class=
- "bold"><b>typename</b></span> MutableGraph, <span class=
- "bold"><b>typename</b></span> Done, <span class=
- "bold"><b>typename</b></span> EdgeCentralityMap>
- <span class="type"><span class=
- "bold"><b>void</b></span></span> betweenness_centrality_clustering(MutableGraph & g, Done done,
- EdgeCentralityMap edge_centrality);
- <span class="bold"><b>template</b></span><<span class=
- "bold"><b>typename</b></span> MutableGraph, <span class=
- "bold"><b>typename</b></span> Done>
- <span class="type"><span class=
- "bold"><b>void</b></span></span> betweenness_centrality_clustering(MutableGraph & g, Done done);
- </pre></div>
- <div class="refsect1" lang="en"><a name="id822306" id=
- "id822306"></a>
- <h2>Description</h2>
- <p>This algorithm implements graph clustering based on edge
- betweenness centrality. It is an iterative algorithm, where in each
- step it computes the edge betweenness centrality (via <a href=
- "betweenness_centrality.html">brandes_betweenness_centrality</a>) and
- removes the edge with the maximum betweenness centrality. The
- <tt class="computeroutput">done</tt> function object determines
- when the algorithm terminates (the edge found when the algorithm
- terminates will not be removed).</p>
- <h2>Parameters</h2>
- IN: <tt>const Graph& g</tt>
- <blockquote>
- The graph object on which the algorithm will be applied. The type
- <tt>Graph</tt> must be a model of <a
- href="VertexListGraph.html">Vertex List Graph</a> and <a
- href="IncidenceGraph.html">Incidence Graph</a>. When an edge
- centrality map is supplied, it must also model <a
- href="EdgeListGraph.html">Edge List Graph</a> and <a
- href="MutableGraph.html">MutableGraph</a>.<br>
- <b>Python</b>: The parameter is named <tt>graph</tt>.
- </blockquote>
- IN: <tt>Done done</tt>
- <blockquote>
- The function object that indicates termination of the algorithm.
- It must be a ternary function object thats accepts the maximum
- centrality, the descriptor of the edge that will be removed, and
- the graph <tt class="computeroutput">g</tt>.<br>
- <b>Python</b>: Any callable Python object will suffice.
- </blockquote>
- OUT/UTIL: <tt>EdgeCentralityMap edge_centrality_map</tt>
- <blockquote>
- This property map is used to accumulate the betweenness centrality
- of each edge, and is a secondary form of output for the
- algorithm. The type <tt>EdgeCentralityMap</tt> must be a model of <a
- href="../../property_map/doc/ReadWritePropertyMap.html">Read/Write
- Property Map</a>, with the graph's edge descriptor type as its key
- type. The value type of this property map should be the same as the
- value type of the <tt>CentralityMap</tt> property map.<br>
- <b>Default:</b> a <tt>dummy_property_map</tt>, which requires no
- work to compute and returns no answer.<br>
- <b>Python</b>: The color map must be a <tt>edge_double_map</tt> for
- the graph.<br>
- <b>Python default</b>: <tt>graph.get_edge_double_map("centrality")</tt>
- </blockquote>
- IN: <tt>VertexIndexMap vertex_index</tt>
- <blockquote>
- This maps each vertex to an integer in the range <tt>[0,
- num_vertices(g))</tt>. This is necessary for efficient updates of the
- heap data structure when an edge is relaxed. The type
- <tt>VertexIndexMap</tt> must be a model of
- <a href="../../property_map/doc/ReadablePropertyMap.html">Readable Property Map</a>. The value type of the map must be an
- integer type. The vertex descriptor type of the graph needs to be
- usable as the key type of the map.<br>
- <b>Default:</b> <tt>get(vertex_index, g)</tt>.
- Note: if you use this default, make sure your graph has
- an internal <tt>vertex_index</tt> property. For example,
- <tt>adjacency_list</tt> with <tt>VertexList=listS</tt> does
- not have an internal <tt>vertex_index</tt> property.<br>
- <b>Python</b>: Unsupported parameter.
- </blockquote>
- <table xmlns:rev=
- "http://www.cs.rpi.edu/~gregod/boost/tools/doc/revision" width=
- "100%">
- <tr>
- <td align="left"></td>
- <td align="right"></td>
- </tr>
- </table>
- <h3>Where Defined</h3>
- <<a href=
- "../../../boost/graph/bc_clustering.hpp">boost/graph/bc_clustering.hpp</a>>
- <hr>
- <table>
- <tr valign="top">
- <td nowrap>Copyright © 2004</td>
- <td><a href="http://www.boost.org/people/doug_gregor.html">Douglas Gregor</a>,
- Indiana University (dgregor@cs.indiana.edu)<br>
- <a href="https://homes.cs.washington.edu/~al75">Andrew Lumsdaine</a>, Indiana
- University (<a href=
- "mailto:lums@osl.iu.edu">lums@osl.iu.edu</a>)</td>
- </tr>
- </table>
- </body>
- </html>
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