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CLUSTER(1)		     General Commands Manual		      CLUSTER(1)

NAME
     cluster - find clusters in a graph and augment the graph with this informa-
     tion.

SYNOPSIS
     cluster [-v?]  [ -Ck ] [ -ck ] [ -o outfile ] [ files ]

DESCRIPTION
     cluster  takes as input a graph in DOT format, finds node clusters and aug-
     ments the graph with this information.  The clusters are specified  by  the
     "cluster"	attribute attached to nodes; cluster values are non-negative in-
     tegers.  cluster attempts to maximize the modularity of the clustering.  If
     the edge attribute "weight" is defined, this will be used in computing  the
     clustering.

OPTIONS
     The following options are supported:

     -Ck    specifies  a  targeted  number of clusters that should be generated.
	    The specified number k is only a suggestion and may not  be  realis-
	    able.   If k == 0, the default, the number of clusters that approxi-
	    mately optimizes the modularity is returned.

     -ck    specifies clustering method.  If k ==  0,  the  default,  modularity
	    clustering will be used.  If k == 1 modularity quality will be used.

     -ooutfile
	    Specifies  that  output should go into the file outfile. By default,
	    stdout is used.

     -v     Verbose mode.

     -?     Prints the usage and exits.

EXAMPLES
     Applying cluster to the following graph,

	graph {
	    1--2 [weight=10.]
	    2--3 [weight=1]
	    3--4 [weight=10.]
	    4--5 [weight=10]
	    5--6 [weight=10]
	    3--6 [weight=0.1]
	    4--6 [weight=10.]
	   }

     gives

	graph {
	      node [cluster="-1"];
	      1 [cluster=1];
	      2 [cluster=1];
	      3 [cluster=2];
	      4 [cluster=2];
	      5 [cluster=2];
	      6 [cluster=2];
	      1 -- 2 [weight="10."];
	      2 -- 3 [weight=1];
	      3 -- 4 [weight="10."];
	      4 -- 5 [weight=10];
	      5 -- 6 [weight=10];
	      3 -- 6 [weight="0.1"];
	      4 -- 6 [weight="10."];
	}

AUTHOR
     Yifan Hu <yifanhu@yahoo.com>

SEE ALSO
     gvmap(1)

     Blondel, V.D., Guillaume, J.L., Lambiotte, R., Lefebvre, E.: Fast unfolding
     of communities in large networks. Journal of Statistical Mechanics:  Theory
     and Experiment (2008), P10008.

				  3 March 2011			      CLUSTER(1)

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