networkx.algorithms.bipartite.projection.weighted_projected_graph¶

weighted_projected_graph
(B, nodes, ratio=False)[source]¶ Returns a weighted projection of B onto one of its node sets.
The weighted projected graph is the projection of the bipartite network B onto the specified nodes with weights representing the number of shared neighbors or the ratio between actual shared neighbors and possible shared neighbors if
ratio is True
[1]. The nodes retain their attributes and are connected in the resulting graph if they have an edge to a common node in the original graph.Parameters:  B (NetworkX graph) – The input graph should be bipartite.
 nodes (list or iterable) – Nodes to project onto (the “bottom” nodes).
 ratio (Bool (default=False)) – If True, edge weight is the ratio between actual shared neighbors and maximum possible shared neighbors (i.e., the size of the other node set). If False, edges weight is the number of shared neighbors.
Returns: Graph – A graph that is the projection onto the given nodes.
Return type: NetworkX graph
Examples
>>> from networkx.algorithms import bipartite >>> B = nx.path_graph(4) >>> G = bipartite.weighted_projected_graph(B, [1, 3]) >>> list(G) [1, 3] >>> list(G.edges(data=True)) [(1, 3, {'weight': 1})] >>> G = bipartite.weighted_projected_graph(B, [1, 3], ratio=True) >>> list(G.edges(data=True)) [(1, 3, {'weight': 0.5})]
Notes
No attempt is made to verify that the input graph B is bipartite. The graph and node properties are (shallow) copied to the projected graph.
See
bipartite documentation
for further details on how bipartite graphs are handled in NetworkX.See also
is_bipartite()
,is_bipartite_node_set()
,sets()
,collaboration_weighted_projected_graph()
,overlap_weighted_projected_graph()
,generic_weighted_projected_graph()
,projected_graph()
References
[1] Borgatti, S.P. and Halgin, D. In press. “Analyzing Affiliation Networks”. In Carrington, P. and Scott, J. (eds) The Sage Handbook of Social Network Analysis. Sage Publications.