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OptimizerModularity
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Class OptimizerModularity</H2>
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java.lang.Object
<IMG SRC="./resources/inherit.gif" ALT="extended by "><B>OptimizerModularity</B>
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<DT><PRE>public class <B>OptimizerModularity</B><DT>extends java.lang.Object</DL>
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<P>
Optimizer for a generalization of Newman and Girvan's Modularity measure, for computing graph clusterings. The Modularity measure is generalized to arbitrary node weights; it is recommended to set the weight of each node to its degree, i.e. the total weight of its edges, as Newman and Girvan did. For more information on the (used version of the) Modularity measure, see M. E. J. Newman: "Analysis of weighted networks", Physical Review E 70, 056131, 2004. For the relation of Modularity to the LinLog energy model, see Andreas Noack: <a href="http://arxiv.org/abs/0807.4052"> "Modularity clustering is force-directed layout"</a>, Preprint arXiv:0807.4052, 2008.
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<TD><CODE><B><A HREF="OptimizerModularity.html#OptimizerModularity()">OptimizerModularity</A></B>()</CODE>
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<CODE> java.util.Map<<A HREF="Node.html" title="class in <Unnamed>">Node</A>,java.lang.Integer></CODE></FONT></TD>
<TD><CODE><B><A HREF="OptimizerModularity.html#execute(java.util.List, java.util.List, boolean)">execute</A></B>(java.util.List<<A HREF="Node.html" title="class in <Unnamed>">Node</A>> nodes,
java.util.List<<A HREF="Edge.html" title="class in <Unnamed>">Edge</A>> edges,
boolean ignoreLoops)</CODE>
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Computes a clustering of a given graph by maximizing the Modularity.</TD>
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<TH ALIGN="left"><B>Methods inherited from class java.lang.Object</B></TH>
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<TD><CODE>clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait</CODE></TD>
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<A NAME="OptimizerModularity()"><!-- --></A><H3>
OptimizerModularity</H3>
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public <B>OptimizerModularity</B>()</PRE>
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<A NAME="execute(java.util.List, java.util.List, boolean)"><!-- --></A><H3>
execute</H3>
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public java.util.Map<<A HREF="Node.html" title="class in <Unnamed>">Node</A>,java.lang.Integer> <B>execute</B>(java.util.List<<A HREF="Node.html" title="class in <Unnamed>">Node</A>> nodes,
java.util.List<<A HREF="Edge.html" title="class in <Unnamed>">Edge</A>> edges,
boolean ignoreLoops)</PRE>
<DL>
<DD>Computes a clustering of a given graph by maximizing the Modularity.
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<DD><DL>
<DT><B>Parameters:</B><DD><CODE>nodes</CODE> - weighted nodes of the graph. It is recommended to set the weight of each node to the sum of the weights of its edges. Weights must not be negative.<DD><CODE>edges</CODE> - weighted edges of the graph. Omit edges with weight 0.0 (i.e. non-edges). For unweighted graphs use weight 1.0 for all edges. Weights must not be negative. Weights must be symmetric, i.e. the weight from node <code>n1</code> to node <code>n2</code> must be equal to the weight from node <code>n2</code> to node <code>n1</code>.<DD><CODE>ignoreLoops</CODE> - set to <code>true</code> to use an adapted version of Modularity for graphs without loops (edges whose start node equals the end node)
<DT><B>Returns:</B><DD>clustering with large Modularity, as map from graph nodes to cluster IDs.</DL>
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