networkx.algorithms.centrality.approximate_current_flow_betweenness_centrality¶

approximate_current_flow_betweenness_centrality(G, normalized=True, weight=None, dtype=<class 'float'>, solver='full', epsilon=0.5, kmax=10000, seed=None)[source]¶

Compute the approximate current-flow betweenness centrality for nodes.

Approximates the current-flow betweenness centrality within absolute error of epsilon with high probability 1.

Parameters

G (graph) – A NetworkX graph
normalized (bool, optional (default=True)) – If True the betweenness values are normalized by 2/[(n-1)(n-2)] where n is the number of nodes in G.
weight (string or None, optional (default=None)) – Key for edge data used as the edge weight. If None, then use 1 as each edge weight.
dtype (data type (float)) – Default data type for internal matrices. Set to np.float32 for lower memory consumption.
solver (string (default=’lu’)) – Type of linear solver to use for computing the flow matrix. Options are “full” (uses most memory), “lu” (recommended), and “cg” (uses least memory).
epsilon (float) – Absolute error tolerance.
kmax (int) – Maximum number of sample node pairs to use for approximation.
seed (integer, random_state, or None (default)) – Indicator of random number generation state. See Randomness.

Returns

nodes – Dictionary of nodes with betweenness centrality as the value.

Return type

dictionary