This documents the development version of NetworkX. Documentation for the current release can be found here.
projected_graph(B, nodes, multigraph=False)¶
Returns the projection of B onto one of its node sets.
Returns the graph G that is the projection of the bipartite graph B onto the specified nodes. They retain their attributes and are connected in G if they have a common neighbor in B.
- BNetworkX graph
The input graph should be bipartite.
- nodeslist or iterable
Nodes to project onto (the “bottom” nodes).
- multigraph: bool (default=False)
If True return a multigraph where the multiple edges represent multiple shared neighbors. They edge key in the multigraph is assigned to the label of the neighbor.
- GraphNetworkX graph or multigraph
A graph that is the projection onto the given nodes.
No attempt is made to verify that the input graph B is bipartite. Returns a simple graph that is the projection of the bipartite graph B onto the set of nodes given in list nodes. If multigraph=True then a multigraph is returned with an edge for every shared neighbor.
Directed graphs are allowed as input. The output will also then be a directed graph with edges if there is a directed path between the nodes.
The graph and node properties are (shallow) copied to the projected graph.
bipartite documentationfor further details on how bipartite graphs are handled in NetworkX.
>>> from networkx.algorithms import bipartite >>> B = nx.path_graph(4) >>> G = bipartite.projected_graph(B, [1, 3]) >>> list(G) [1, 3] >>> list(G.edges()) [(1, 3)]
bare connected through both nodes 1 and 2 then building a multigraph results in two edges in the projection onto [
>>> B = nx.Graph() >>> B.add_edges_from([("a", 1), ("b", 1), ("a", 2), ("b", 2)]) >>> G = bipartite.projected_graph(B, ["a", "b"], multigraph=True) >>> print([sorted((u, v)) for u, v in G.edges()]) [['a', 'b'], ['a', 'b']]