networkx.linalg.modularitymatrix.modularity_matrix¶

modularity_matrix
(G, nodelist=None, weight=None)[source]¶ Return the modularity matrix of G.
The modularity matrix is the matrix B = A  <A>, where A is the adjacency matrix and <A> is the average adjacency matrix, assuming that the graph is described by the configuration model.
More specifically, the element B_ij of B is defined as
\[A_{ij}  {k_i k_j m \over 2}\]where k_i is the degree of node i, and were m is the number of edges in the graph. When weight is set to a name of an attribute edge, Aij, k_i, k_j and m are computed using its value.
Parameters:  G (Graph) – A NetworkX graph
 nodelist (list, optional) – The rows and columns are ordered according to the nodes in nodelist. If nodelist is None, then the ordering is produced by G.nodes().
 weight (string or None, optional (default=None)) – The edge attribute that holds the numerical value used for the edge weight. If None then all edge weights are 1.
Returns: B – The modularity matrix of G.
Return type: Numpy matrix
Examples
>>> import networkx as nx >>> k =[3, 2, 2, 1, 0] >>> G = nx.havel_hakimi_graph(k) >>> B = nx.modularity_matrix(G)
See also
to_numpy_matrix()
,adjacency_matrix()
,laplacian_matrix()
,directed_modularity_matrix()
References
[1] M. E. J. Newman, “Modularity and community structure in networks”, Proc. Natl. Acad. Sci. USA, vol. 103, pp. 85778582, 2006.