Return communicability centrality for each node in 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 : 

Returns :  nodes: dictionary :

Raises :  NetworkXError :

See also
Notes
This version of the algorithm computes eigenvalues and eigenvectors of the adjacency matrix.
Communicability centrality of a node in G can be found using a spectral decomposition of the adjacency matrix [R136] [R137],
where is an eigenvector of the adjacency matrix of G corresponding corresponding to the eigenvalue .
References
[R136]  (1, 2) Ernesto Estrada, Juan A. RodriguezVelazquez, “Subgraph centrality in complex networks”, Physical Review E 71, 056103 (2005). http://arxiv.org/abs/condmat/0504730 
[R137]  (1, 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(G)