# communicability_centrality_exp¶

communicability_centrality_exp(G)[source]

Return the communicability centrality for each node of G

Communicability centrality, also called subgraph centrality, of a node is the sum of closed walks of all lengths starting and ending at node .

Parameters: G (graph) – nodes – Dictionary of nodes with communicability centrality as the value. dictionary NetworkXError – If the graph is not undirected and simple.

communicability()
Communicability between all pairs of nodes in G.
communicability_centrality()
Communicability centrality for each node of G.

Notes

This version of the algorithm exponentiates the adjacency matrix. The communicability centrality of a node in G can be found using the matrix exponential of the adjacency matrix of G [1] [2],

References

 [1] Ernesto Estrada, Juan A. Rodriguez-Velazquez, “Subgraph centrality in complex networks”, Physical Review E 71, 056103 (2005). http://arxiv.org/abs/cond-mat/0504730
 [2] Ernesto Estrada, Naomichi Hatano, “Communicability in complex networks”, Phys. Rev. E 77, 036111 (2008). http://arxiv.org/abs/0707.0756

Examples

>>> G = nx.Graph([(0,1),(1,2),(1,5),(5,4),(2,4),(2,3),(4,3),(3,6)])
>>> sc = nx.communicability_centrality_exp(G)