NAME

       cluster - find clusters in a graph and augment the graph with this information.

SYNOPSIS

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

DESCRIPTION

       cluster  takes  as input a graph in DOT format, finds node clusters and augments the graph
       with this information.  The clusters are specified by the "cluster" attribute attached  to
       nodes;  cluster  values  are  non-negative  integers.   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 realisable.  If k == 0,  the  default,
              the number of clusters that approximately 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.

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@research.att.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)