(self, edge_weights=None, vertex_weights=None, trials=10)
return VertexClustering(
            self,
            membership,
            params={"codelength": codelength},
            modularity_params={"weights": edge_weights},
        )
Finds the community structure of the network according to the Infomap
        method of Martin Rosvall and Carl T. Bergstrom.

        @param edge_weights: name of an edge attribute or a list containing
          edge weights.
        @param vertex_weights: name of an vertex attribute or a list containing
          vertex weights.
        @param trials: the number of attempts to partition the network.
        @return: an appropriate L{VertexClustering} object with an extra attribute
          called C{codelength} that stores the code length determined by the
          algorithm.

        @newfield ref: Reference
        @ref: M. Rosvall and C. T. Bergstrom: Maps of information flow reveal
          community structure in complex networks, PNAS 105, 1118 (2008).
          U{http://dx.doi.org/10.1073/pnas.0706851105},
          U{http://arxiv.org/abs/0707.0609}.
        @ref: M. Rosvall, D. Axelsson, and C. T. Bergstrom: The map equation,
          Eur. Phys. J. Special Topics 178, 13 (2009).
          U{http://dx.doi.org/10.1140/epjst/e2010-01179-1},
          U{http://arxiv.org/abs/0906.1405}.
Finds the community structure of the network according to the Infomap
        method of Martin Rosvall and Carl T. Bergstrom.
Finds the community structure of the network according to the Infomap method of Martin Rosvall and Carl T . Bergstrom .
def community_infomap(self, edge_weights=None, vertex_weights=None, trials=10):
        """Finds the community structure of the network according to the Infomap
        method of Martin Rosvall and Carl T. Bergstrom.

        @param edge_weights: name of an edge attribute or a list containing
          edge weights.
        @param vertex_weights: name of an vertex attribute or a list containing
          vertex weights.
        @param trials: the number of attempts to partition the network.
        @return: an appropriate L{VertexClustering} object with an extra attribute
          called C{codelength} that stores the code length determined by the
          algorithm.

        @newfield ref: Reference
        @ref: M. Rosvall and C. T. Bergstrom: Maps of information flow reveal
          community structure in complex networks, PNAS 105, 1118 (2008).
          U{http://dx.doi.org/10.1073/pnas.0706851105},
          U{http://arxiv.org/abs/0707.0609}.
        @ref: M. Rosvall, D. Axelsson, and C. T. Bergstrom: The map equation,
          Eur. Phys. J. Special Topics 178, 13 (2009).
          U{http://dx.doi.org/10.1140/epjst/e2010-01179-1},
          U{http://arxiv.org/abs/0906.1405}.
        """
        membership, codelength = GraphBase.community_infomap(
            self, edge_weights, vertex_weights, trials
        )
        return VertexClustering(
            self,
            membership,
            params={"codelength": codelength},
            modularity_params={"weights": edge_weights},
        )
def community_infomap ( self , edge_weights = None , vertex_weights = None , trials = 10 ) : membership , codelength = GraphBase . community_infomap ( self , edge_weights , vertex_weights , trials ) return VertexClustering ( self , membership , params = { "codelength" : codelength } , modularity_params = { "weights" : edge_weights } , )