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
orwidth
greater than the maximum degree of the graph, this function equates to a slower version ofbfs_edges
. All nodes will be visited, though the order of the reported edges may vary. In such cases,value
has no effect - consider usingbfs_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 highestvalue
are enqueued (in decreasing order ofvalue
).- 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)]