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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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networkx.algorithms.components.attracting_components

attracting_components(G)

Generates the attracting components in G.

An attracting component in a directed graph G is a strongly connected component with the property that a random walker on the graph will never leave the component, once it enters the component.

The nodes in attracting components can also be thought of as recurrent nodes. If a random walker enters the attractor containing the node, then the node will be visited infinitely often.

To obtain induced subgraphs on each component use: (G.subgraph(c).copy() for c in attracting_components(G))

Parameters

G (DiGraph, MultiDiGraph) – The graph to be analyzed.

Returns

attractors – A generator of sets of nodes, one for each attracting component of G.

Return type

generator of sets

Raises

NetworkXNotImplemented – If the input graph is undirected.

See also

number_attracting_components(), is_attracting_component()