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kl_connected_subgraph(G, k, l, low_memory=False, same_as_graph=False)

A graph is locally :None:None:`(k, l)`-connected if for each edge :None:None:`(u, v)` in the graph there are at least l edge-disjoint paths of length at most k joining :None:None:`u` to :None:None:`v`.

Parameters

G : NetworkX graph

The graph in which to find a maximum locally :None:None:`(k, l)`-connected subgraph.

k : integer

The maximum length of paths to consider. A higher number means a looser connectivity requirement.

l : integer

The number of edge-disjoint paths. A higher number means a stricter connectivity requirement.

low_memory : bool

If this is True, this function uses an algorithm that uses slightly more time but less memory.

same_as_graph : bool

If True then return a tuple of the form :None:None:`(H, is_same)`, where :None:None:`H` is the maximum locally :None:None:`(k, l)`-connected subgraph and :None:None:`is_same` is a Boolean representing whether G is locally :None:None:`(k, l)`-connected (and hence, whether :None:None:`H` is simply a copy of the input graph G).

Returns

NetworkX graph or two-tuple

If :None:None:`same_as_graph` is True, then this function returns a two-tuple as described above. Otherwise, it returns only the maximum locally :None:None:`(k, l)`-connected subgraph.

Returns the maximum locally :None:None:`(k, l)`-connected subgraph of G.

See Also

is_kl_connected

Examples

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

networkx.algorithms.hybrid.is_kl_connected

Local connectivity graph

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GitHub : /networkx/algorithms/hybrid.py#12
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