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#

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#

closeness_centrality(G[, u, distance, ...])

Compute closeness centrality for nodes.

incremental_closeness_centrality(G, edge[, ...])

Incremental closeness centrality for nodes.

Current Flow Closeness#

current_flow_closeness_centrality(G[, ...])

Compute current-flow closeness centrality for nodes.

information_centrality(G[, weight, dtype, ...])

Compute current-flow closeness centrality for nodes.

(Shortest Path) Betweenness#

betweenness_centrality(G[, k, normalized, ...])

Compute the shortest-path betweenness centrality for nodes.

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#

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.

Communicability Betweenness#

communicability_betweenness_centrality(G)

Returns subgraph communicability for all pairs of nodes in G.

Group Centrality#

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.

prominent_group(G, k[, weight, C, ...])

Find the prominent group of size \(k\) in graph \(G\).

Load#

load_centrality(G[, v, cutoff, normalized, ...])

Compute load centrality for nodes.

edge_load_centrality(G[, cutoff])

Compute edge load.

Subgraph#

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#

harmonic_centrality(G[, nbunch, distance, ...])

Compute harmonic centrality for nodes.

Dispersion#

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

Calculate dispersion between u and v in G.

Reaching#

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.

Percolation#

percolation_centrality(G[, attribute, ...])

Compute the percolation centrality for nodes.

Second Order Centrality#

second_order_centrality(G)

Compute the second order centrality for nodes of G.

Trophic#

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#

voterank(G[, number_of_nodes])

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