bfs_beam_edges#

bfs_beam_edges(G, source, value, width=None)[source]#

Iterates over edges in a beam search.

The beam search is a generalized breadth-first search in which only the “best” w neighbors of the current node are enqueued, where w is the beam width and “best” is an application-specific heuristic. In general, a beam search with a small beam width might not visit each node in the graph.

Note

With the default value of width=None or width greater than the maximum degree of the graph, this function equates to a slower version of bfs_edges. All nodes will be visited, though the order of the reported edges may vary. In such cases, value has no effect - consider using bfs_edges directly instead.

Parameters:

GNetworkX graph
sourcenode: Starting node for the breadth-first search; this function iterates over only those edges in the component reachable from this node.
valuefunction: A function that takes a node of the graph as input and returns a real number indicating how “good” it is. A higher value means it is more likely to be visited sooner during the search. When visiting a new node, only the width neighbors with the highest value are enqueued (in decreasing order of value).
widthint (default = None): The beam width for the search. This is the number of neighbors (ordered by value) to enqueue when visiting each new node.

Yields:

edge: Edges in the beam search starting from source, given as a pair of nodes.

Examples

To give nodes with, for example, a higher centrality precedence during the search, set the value function to return the centrality value of the node:

>>> G = nx.karate_club_graph()
>>> centrality = nx.eigenvector_centrality(G)
>>> list(nx.bfs_beam_edges(G, source=0, value=centrality.get, width=3))
[(0, 2), (0, 1), (0, 8), (2, 32), (1, 13), (8, 33)]