shortest_simple_paths#
- shortest_simple_paths(G, source, target, weight=None)[source]#
- Generate all simple paths in the graph G from source to target,
starting from shortest ones.
A simple path is a path with no repeated nodes.
If a weighted shortest path search is to be used, no negative weights are allowed.
- Parameters:
- GNetworkX graph
- sourcenode
Starting node for path
- targetnode
Ending node for path
- weightstring or function
If it is a string, it is the name of the edge attribute to be used as a weight.
If it is a function, the weight of an edge is the value returned by the function. The function must accept exactly three positional arguments: the two endpoints of an edge and the dictionary of edge attributes for that edge. The function must return a number.
If None all edges are considered to have unit weight. Default value None.
- Returns:
- path_generator: generator
A generator that produces lists of simple paths, in order from shortest to longest.
- Raises:
- NetworkXNoPath
If no path exists between source and target.
- NetworkXError
If source or target nodes are not in the input graph.
- NetworkXNotImplemented
If the input graph is a Multi[Di]Graph.
See also
all_shortest_paths
shortest_path
all_simple_paths
Notes
This procedure is based on algorithm by Jin Y. Yen [1]. Finding the first \(K\) paths requires \(O(KN^3)\) operations.
References
[1]Jin Y. Yen, â€śFinding the K Shortest Loopless Paths in a Networkâ€ť, Management Science, Vol. 17, No. 11, Theory Series (Jul., 1971), pp. 712-716.
Examples
>>> G = nx.cycle_graph(7) >>> paths = list(nx.shortest_simple_paths(G, 0, 3)) >>> print(paths) [[0, 1, 2, 3], [0, 6, 5, 4, 3]]
You can use this function to efficiently compute the k shortest/best paths between two nodes.
>>> from itertools import islice >>> def k_shortest_paths(G, source, target, k, weight=None): ... return list( ... islice(nx.shortest_simple_paths(G, source, target, weight=weight), k) ... ) >>> for path in k_shortest_paths(G, 0, 3, 2): ... print(path) [0, 1, 2, 3] [0, 6, 5, 4, 3]