72 lines
2.5 KiB
Python
72 lines
2.5 KiB
Python
"""
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Graph utilities and algorithms
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Graphs are represented with their adjacency matrices, preferably using
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sparse matrices.
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"""
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# Authors: Aric Hagberg <hagberg@lanl.gov>
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# Gael Varoquaux <gael.varoquaux@normalesup.org>
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# Jake Vanderplas <vanderplas@astro.washington.edu>
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# License: BSD 3 clause
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from scipy import sparse
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from .graph_shortest_path import graph_shortest_path # noqa
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from .validation import _deprecate_positional_args
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###############################################################################
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# Path and connected component analysis.
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# Code adapted from networkx
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@_deprecate_positional_args
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def single_source_shortest_path_length(graph, source, *, cutoff=None):
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"""Return the shortest path length from source to all reachable nodes.
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Returns a dictionary of shortest path lengths keyed by target.
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Parameters
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----------
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graph : {sparse matrix, ndarray} of shape (n, n)
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Adjacency matrix of the graph. Sparse matrix of format LIL is
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preferred.
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source : int
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Starting node for path.
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cutoff : int, default=None
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Depth to stop the search - only paths of length <= cutoff are returned.
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Examples
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--------
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>>> from sklearn.utils.graph import single_source_shortest_path_length
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>>> import numpy as np
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>>> graph = np.array([[ 0, 1, 0, 0],
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... [ 1, 0, 1, 0],
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... [ 0, 1, 0, 1],
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... [ 0, 0, 1, 0]])
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>>> list(sorted(single_source_shortest_path_length(graph, 0).items()))
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[(0, 0), (1, 1), (2, 2), (3, 3)]
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>>> graph = np.ones((6, 6))
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>>> list(sorted(single_source_shortest_path_length(graph, 2).items()))
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[(0, 1), (1, 1), (2, 0), (3, 1), (4, 1), (5, 1)]
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"""
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if sparse.isspmatrix(graph):
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graph = graph.tolil()
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else:
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graph = sparse.lil_matrix(graph)
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seen = {} # level (number of hops) when seen in BFS
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level = 0 # the current level
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next_level = [source] # dict of nodes to check at next level
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while next_level:
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this_level = next_level # advance to next level
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next_level = set() # and start a new list (fringe)
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for v in this_level:
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if v not in seen:
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seen[v] = level # set the level of vertex v
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next_level.update(graph.rows[v])
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if cutoff is not None and cutoff <= level:
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break
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level += 1
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return seen # return all path lengths as dictionary
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