sklearn.utils.graph.single_source_shortest_path_length¶

sklearn.utils.graph.single_source_shortest_path_length(graph, source, *, cutoff=None)[source]¶

Return the shortest path length from source to all reachable nodes.

Returns a dictionary of shortest path lengths keyed by target.

Parameters

graph{sparse matrix, ndarray} of shape (n, n)

Adjacency matrix of the graph. Sparse matrix of format LIL is preferred.

sourceint

Starting node for path.

cutoffint, default=None

Depth to stop the search - only paths of length <= cutoff are returned.

Examples

>>> from sklearn.utils.graph import single_source_shortest_path_length
>>> import numpy as np
>>> graph = np.array([[ 0, 1, 0, 0],
...                   [ 1, 0, 1, 0],
...                   [ 0, 1, 0, 1],
...                   [ 0, 0, 1, 0]])
>>> list(sorted(single_source_shortest_path_length(graph, 0).items()))
[(0, 0), (1, 1), (2, 2), (3, 3)]
>>> graph = np.ones((6, 6))
>>> list(sorted(single_source_shortest_path_length(graph, 2).items()))
[(0, 1), (1, 1), (2, 0), (3, 1), (4, 1), (5, 1)]