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Note

This documents the development version of NetworkX. Documentation for the current release can be found here.

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Centrality¶

Degree¶

`degree_centrality`(G)	Compute the degree centrality for nodes.
`in_degree_centrality`(G)	Compute the in-degree centrality for nodes.
`out_degree_centrality`(G)	Compute the out-degree centrality for nodes.

`eigenvector_centrality`(G[, max_iter, tol, …])	Compute the eigenvector centrality for the graph `G`.
`eigenvector_centrality_numpy`(G[, weight, …])	Compute the eigenvector centrality for the graph G.
`katz_centrality`(G[, alpha, beta, max_iter, …])	Compute the Katz centrality for the nodes of the graph G.
`katz_centrality_numpy`(G[, alpha, beta, …])	Compute the Katz centrality for the graph G.

`closeness_centrality`(G[, u, distance, …])	Compute closeness centrality for nodes.
`incremental_closeness_centrality`(G, edge[, …])	Incremental closeness centrality for nodes.

`current_flow_closeness_centrality`(G[, …])	Compute current-flow closeness centrality for nodes.
`information_centrality`(G[, weight, dtype, …])	Compute current-flow closeness centrality for nodes.

`betweenness_centrality`(G[, k, normalized, …])	Compute the shortest-path betweenness centrality for nodes.
`betweenness_centrality_source`(G[, …])
`betweenness_centrality_subset`(G, sources, …)	Compute betweenness centrality for a subset of nodes.
`edge_betweenness_centrality`(G[, k, …])	Compute betweenness centrality for edges.
`edge_betweenness_centrality_subset`(G, …[, …])	Compute betweenness centrality for edges for a subset of nodes.

`current_flow_betweenness_centrality`(G[, …])	Compute current-flow betweenness centrality for nodes.
`edge_current_flow_betweenness_centrality`(G)	Compute current-flow betweenness centrality for edges.
`approximate_current_flow_betweenness_centrality`(G)	Compute the approximate current-flow betweenness centrality for nodes.
`current_flow_betweenness_centrality_subset`(G, …)	Compute current-flow betweenness centrality for subsets of nodes.
`edge_current_flow_betweenness_centrality_subset`(G, …)	Compute current-flow betweenness centrality for edges using subsets of nodes.

Returns subgraph communicability for all pairs of nodes in G.

`group_betweenness_centrality`(G, C[, …])	Compute the group betweenness centrality for a group of nodes.
`group_closeness_centrality`(G, S[, weight])	Compute the group closeness centrality for a group of nodes.
`group_degree_centrality`(G, S)	Compute the group degree centrality for a group of nodes.
`group_in_degree_centrality`(G, S)	Compute the group in-degree centrality for a group of nodes.
`group_out_degree_centrality`(G, S)	Compute the group out-degree centrality for a group of nodes.

`load_centrality`(G[, v, cutoff, normalized, …])	Compute load centrality for nodes.
`edge_load_centrality`(G[, cutoff])	Compute edge load.

`subgraph_centrality`(G)	Returns subgraph centrality for each node in G.
`subgraph_centrality_exp`(G)	Returns the subgraph centrality for each node of G.
`estrada_index`(G)	Returns the Estrada index of a the graph G.

harmonic_centrality(G[, nbunch, distance])

Compute harmonic centrality for nodes.

dispersion(G[, u, v, normalized, alpha, b, c])

Calculate dispersion between u and v in G.

`local_reaching_centrality`(G, v[, paths, …])	Returns the local reaching centrality of a node in a directed graph.
`global_reaching_centrality`(G[, weight, …])	Returns the global reaching centrality of a directed graph.

Compute the percolation centrality for nodes.

Compute the second order centrality for nodes of G.

`trophic_levels`(G[, weight])	Compute the trophic levels of nodes.
`trophic_differences`(G[, weight])	Compute the trophic differences of the edges of a directed graph.
`trophic_incoherence_parameter`(G[, weight, …])	Compute the trophic incoherence parameter of a graph.

voterank(G[, number_of_nodes])

Select a list of influential nodes in a graph using VoteRank algorithm