single_source_dijkstra_path_length#

single_source_dijkstra_path_length(G, source, cutoff=None, weight='weight')[source]#

Find shortest weighted path lengths in G from a source node.

Compute the shortest path length between source and all other reachable nodes for a weighted graph.

Parameters:

GNetworkX graph

sourcenode label

Starting node for path

cutoffinteger or float, optional

Length (sum of edge weights) at which the search is stopped. If cutoff is provided, only return paths with summed weight <= cutoff.

weightstring 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 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 or None to indicate a hidden edge.

Returns:

lengthdict: Dict keyed by node to shortest path length from source.

Raises:

NodeNotFound: If source is not in G.

See also

single_source_dijkstra, single_source_bellman_ford_path_length

Notes

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

The weight function can be used to hide edges by returning None. So weight = lambda u, v, d: 1 if d['color']=="red" else None will find the shortest red path.

Examples

>>> G = nx.path_graph(5)
>>> length = nx.single_source_dijkstra_path_length(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
----

Additional backends implement this function

cugraphGPU-accelerated backend.

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.