current_flow_closeness_centrality¶

current_flow_closeness_centrality(G, normalized=True, weight='weight', dtype=<type 'float'>, solver='lu')¶

Compute current-flow closeness centrality for nodes.

A variant of closeness centrality based on effective resistance between nodes in a network. This metric is also known as information centrality.

Parameters :

G : graph

A NetworkX graph

normalized : bool, optional

If True the values are normalized by 1/(n-1) where n is the number of nodes in G.

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).

Returns :

nodes : dictionary

Dictionary of nodes with current flow closeness centrality as the value.