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| <title>Function betweenness_centrality_clustering</title> |
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| <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= |
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| "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>adjacenty_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="http://www.osl.iu.edu/~lums">Andrew Lumsdaine</a>, Indiana |
| University (<a href= |
| "mailto:lums@osl.iu.edu">lums@osl.iu.edu</a>)</td> |
| </tr> |
| </table> |
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