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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=True [R163]. 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 possible shared neighbors. If False, edges weight is the number of shared neighbors.
Returns : Graph : NetworkX graph
A graph that is the projection onto the given nodes.
See also
is_bipartite, is_bipartite_node_set, sets, collaboration_weighted_projected_graph, overlap_weighted_projected_graph, generic_weighted_projected_graph, projected_graph
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.
References
[R163] (1, 2) 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. Examples
>>> from networkx.algorithms import bipartite >>> B = nx.path_graph(4) >>> G = bipartite.weighted_projected_graph(B, [1,3]) >>> print(G.nodes()) [1, 3] >>> print(G.edges(data=True)) [(1, 3, {'weight': 1})] >>> G = bipartite.weighted_projected_graph(B, [1,3], ratio=True) >>> print(G.edges(data=True)) [(1, 3, {'weight': 0.5})]