def n_shortest_paths(self,
source,
target,
n,
distance=None,
strategy="naive",
exclude_edge=False):
"""Compute n shortest paths from the source to the target.
Two search strategies are available: 'naive' and 'yen'.
The naive strategy first finds the set of all shortest paths from the
source to the target node, it then ranks them by the cumulative distance
score and returns n best paths. The second strategy uses Yen's
algorithm [1] for finding n shortest paths. The first naive strategy
performs better for highly dense graphs (where every node is connected to
almost every other node). Note that if there are less than n unweighted
shortest paths in the graph, the naive strategy may return less than n
paths.
1. Yen, Jin Y. "Finding the k shortest loopless paths in a network".
Management Science 17.11 (1971): 712-716.
Parameters
----------
source : str
Source node ID
target : str
Target node ID
n : int
Number of top paths to include in the result
distance : str, optional
The name of the attribute to use as the edge distance
path_condition : func, optional
Edge filtering function returning Boolean flag
strategy : str, optional
Path finding strategy: `naive` or `yen`. By default, `naive`.
exclude_edge : bool, optional
Flag indicating whether the direct edge from the source to
the target should be excluded from the result (if exists).
Returns
-------
paths : list
List containing top n best paths according to the distance score
"""
if strategy == "yen":
raise PathFinder.NotImplementedError(
"Yen's algorithm for finding n shortest paths "
"is currently not implemented")
else:
return super().n_shortest_paths(source,
target,
n,
distance=distance,
strategy="naive",
exclude_edge=exclude_edge)
def _compute_yen_shortest_paths(graph,
source,
target,
n,
distance,
exclude_edge=False):
"""Compute n shortest paths using the Yen's algo."""
raise PathFinder.NotImplementedError(
"Yen's algorithm for finding n shortest paths "
"is currently not implemented for graph-tool backend")