communicability_centrality¶

communicability_centrality(G)[source]¶

Return communicability centrality for each node in G.

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

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

See also

communicability

Communicability between all pairs of nodes in G.

communicability_centrality

Communicability centrality for each node of G.

Notes

This version of the algorithm computes eigenvalues and eigenvectors of the adjacency matrix.

Communicability centrality of a node $u$ in G can be found using a spectral decomposition of the adjacency matrix [R178] [R179],

$$SC(u)=\sum_{j=1}^{N}(v_{j}^{u})^2 e^{\lambda_{j}},$$

where $v_j$ is an eigenvector of the adjacency matrix $A$ of G corresponding corresponding to the eigenvalue $\lambda_j$.

References

[R178]

(1, 2) Ernesto Estrada, Juan A. Rodriguez-Velazquez, “Subgraph centrality in complex networks”, Physical Review E 71, 056103 (2005). http://arxiv.org/abs/cond-mat/0504730

[R179]

(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)