single_source_bellman_ford(G, source, target=None, weight='weight')

Uses Bellman-Ford algorithm for shortest paths.

Notes

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

Parameters

G : NetworkX graph

source : node label

Starting node for path

target : node label, optional

Ending node for path

weight : string or function

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 :None:None:`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.

Raises

NodeNotFound

If :None:None:`source` is not in G.

Returns

distance, path : pair of dictionaries, or numeric and list

If target is None, returns a tuple of two dictionaries keyed by node. The first dictionary stores distance from one of the source nodes. The second stores the path from one of the sources to that node. If target is not None, returns a tuple of (distance, path) where distance is the distance from source to target and path is a list representing the path from source to target.

Compute shortest paths and lengths in a weighted graph G.

See Also

single_source_bellman_ford_path

single_source_bellman_ford_path_length

single_source_dijkstra

Examples

>>> G = nx.path_graph(5)
... length, path = nx.single_source_bellman_ford(G, 0)
... length[4]
4

>>> for node in [0, 1, 2, 3, 4]:
...     print(f"{node}: {length[node]}")
0: 0
1: 1
2: 2
3: 3
4: 4

>>> path[4]
[0, 1, 2, 3, 4]

>>> length, path = nx.single_source_bellman_ford(G, 0, 1)
... length
1

>>> path
[0, 1]

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path networkx.algorithms.shortest_paths.weighted.single_source_dijkstra networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford_path_length networkx.algorithms.shortest_paths.weighted.single_source_dijkstra_path networkx.algorithms.shortest_paths.weighted.single_source_bellman_ford

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

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GitHub : /networkx/algorithms/shortest_paths/weighted.py#1701
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