Note

This documents the development version of NetworkX. Documentation for the current release can be found here.

# networkx.algorithms.bipartite.generators.configuration_model¶

configuration_model(aseq, bseq, create_using=None, seed=None)[source]

Returns a random bipartite graph from two given degree sequences.

Parameters
• aseq (list) – Degree sequence for node set A.

• bseq (list) – Degree sequence for node set B.

• create_using (NetworkX graph instance, optional) – Return graph of this type.

• seed (integer, random_state, or None (default)) – Indicator of random number generation state. See Randomness.

• The graph is composed of two partitions. Set A has nodes 0 to

• (len(aseq) - 1) and set B has nodes len(aseq) to (len(bseq) - 1).

• Nodes from set A are connected to nodes in set B by choosing

• randomly from the possible free stubs, one in A and one in B.

Notes

The sum of the two sequences must be equal: sum(aseq)=sum(bseq) If no graph type is specified use MultiGraph with parallel edges. If you want a graph with no parallel edges use create_using=Graph() but then the resulting degree sequences might not be exact.

The nodes are assigned the attribute ‘bipartite’ with the value 0 or 1 to indicate which bipartite set the node belongs to.

This function is not imported in the main namespace. To use it use nx.bipartite.configuration_model