from_biadjacency_matrix

from_biadjacency_matrix(A, create_using=None, edge_attribute='weight', *, row_order=None, column_order=None)

Creates a new bipartite graph from a biadjacency matrix given as a SciPy sparse array.

Parameters:

Ascipy sparse array

A biadjacency matrix representation of a graph

create_usingNetworkX graph

Use specified graph for result. The default is Graph()

edge_attributestring

Name of edge attribute to store matrix numeric value. The data will have the same type as the matrix entry (int, float, (real,imag)).

row_orderlist, optional (default: range(number of rows in A))

A list of the nodes represented by the rows of the matrix A. Will be represented in the graph as nodes with the bipartite attribute set to 0. Must be the same length as the number of rows in A.

column_orderlist, optional (default: range(number of columns in A))

A list of the nodes represented by the columns of the matrix A. Will be represented in the graph as nodes with the bipartite attribute set to 1. Must be the same length as the number of columns in A.

Returns:

GNetworkX graph

A bipartite graph with edges from the biadjacency matrix A, and nodes from row_order and column_order.

Raises:

ValueError

If row_order or column_order are provided and are not the same length as the number of rows or columns in A, respectively.

See also

biadjacency_matrix

from_numpy_array

Notes

The nodes are labeled with the attribute bipartite set to an integer 0 or 1 representing membership in the top set (bipartite=0) or bottom set (bipartite=1) of the bipartite graph.

If create_using is an instance of networkx.MultiGraph or networkx.MultiDiGraph and the entries of A are of type int, then this function returns a multigraph (of the same type as create_using) with parallel edges. In this case, edge_attribute will be ignored.

References

[1] https://en.wikipedia.org/wiki/Adjacency_matrix#Adjacency_matrix_of_a_bipartite_graph

Additional backends implement this function

cugraph : GPU-accelerated backend.