networkx.algorithms.centrality.eigenvector_centrality_numpy

networkx.algorithms.centrality.eigenvector_centrality_numpy(G)

Compute the eigenvector centrality for the graph G.

Parameters :

G : graph

A networkx graph

Returns :

nodes : dictionary

Dictionary of nodes with eigenvector centrality as the value.

See also

eigenvector_centrality, pagerank, hits

Notes

This algorithm uses the NumPy eigenvalue solver.

For directed graphs this is “right” eigevector centrality. For “left” eigenvector centrality, first reverse the graph with G.reverse().

Examples

>>> G=nx.path_graph(4)
>>> centrality=nx.eigenvector_centrality_numpy(G)
>>> print(['%s %0.2f'%(node,centrality[node]) for node in centrality])
['0 0.37', '1 0.60', '2 0.60', '3 0.37']