bellman_ford_path#

bellman_ford_path(G, source, target, weight='weight')[source]#

Returns the shortest path from source to target in a weighted graph G.

Parameters:
GNetworkX graph
sourcenode

Starting node

targetnode

Ending node

weightstring or function (default=”weight”)

If this is a string, then edge weights will be accessed via the edge attribute with this key (that is, the weight of the edge joining u to v will be G.edges[u, v][weight]). If no such edge attribute exists, the weight of the edge is assumed to be one.

If this 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.

Returns:
pathlist

List of nodes in a shortest path.

Raises:
NodeNotFound

If source is not in G.

NetworkXNoPath

If no path exists between source and target.

Notes

Edge weight attributes must be numerical. Distances are calculated as sums of weighted edges traversed.

Examples

>>> G = nx.path_graph(5)
>>> nx.bellman_ford_path(G, 0, 4)
[0, 1, 2, 3, 4]
----

Additional backends implement this function

cugraphGPU-accelerated backend.

Negative cycles are not yet supported. NotImplementedError will be raised if there are negative edge weights. We plan to support negative edge weights soon. Also, callable weight argument is not supported.

Additional parameters:
dtypedtype or None, optional

The data type (np.float32, np.float64, or None) to use for the edge weights in the algorithm. If None, then dtype is determined by the edge values.

graphblas : OpenMP-enabled sparse linear algebra backend.