strongly_connected_components_recursive

strongly_connected_components_recursive(G)

Generate nodes in strongly connected components of graph.

Recursive version of algorithm.

Parameters:

GNetworkX Graph

A directed graph.

Returns:

compgenerator of sets

A generator of sets of nodes, one for each strongly connected component of G.

Raises:

NetworkXNotImplemented

If G is undirected.

See also

connected_components

Notes

Uses Tarjan’s algorithm[Re7cb971df765-1]_ with Nuutila’s modifications[Re7cb971df765-2]_.

References

[1]

Depth-first search and linear graph algorithms, R. Tarjan SIAM Journal of Computing 1(2):146-160, (1972).

[2]

On finding the strongly connected components in a directed graph. E. Nuutila and E. Soisalon-Soinen Information Processing Letters 49(1): 9-14, (1994)..

Examples

Generate a sorted list of strongly connected components, largest first.

>>> G = nx.cycle_graph(4, create_using=nx.DiGraph())
>>> nx.add_cycle(G, [10, 11, 12])
>>> [
...     len(c)
...     for c in sorted(
...         nx.strongly_connected_components_recursive(G), key=len, reverse=True
...     )
... ]
[4, 3]

If you only want the largest component, it’s more efficient to use max instead of sort.

>>> largest = max(nx.strongly_connected_components_recursive(G), key=len)

To create the induced subgraph of the components use: >>> S = [G.subgraph(c).copy() for c in nx.weakly_connected_components(G)]