is_bipartite(G)

Parameters

G : NetworkX graph

Returns True if graph G is bipartite, False if not.

See Also

color

is_bipartite_node_set

Examples

>>> from networkx.algorithms import bipartite
... G = nx.path_graph(4)
... print(bipartite.is_bipartite(G))
True

See :

Back References

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

networkx.algorithms.bipartite.projection.collaboration_weighted_projected_graph networkx.algorithms.bipartite.projection.overlap_weighted_projected_graph networkx.algorithms.bipartite.projection.generic_weighted_projected_graph networkx.algorithms.bipartite.projection.projected_graph networkx.algorithms.bipartite.centrality.closeness_centrality networkx.algorithms.bipartite.basic.is_bipartite networkx.algorithms.bipartite.projection.weighted_projected_graph networkx.algorithms.bipartite.centrality.betweenness_centrality networkx.algorithms.bipartite.centrality.degree_centrality

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

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GitHub : /networkx/algorithms/bipartite/basic.py#85
type: <class 'function'>
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