# networkx.algorithms.shortest_paths.weighted.johnson¶

johnson(G, weight='weight')[source]

Uses Johnson’s Algorithm to compute shortest paths.

Johnson’s Algorithm finds a shortest path between each pair of nodes in a weighted graph even if negative weights are present.

Parameters
GNetworkX graph
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.

Returns
distancedictionary

Dictionary, keyed by source and target, of shortest paths.

Raises
NetworkXError

If given graph is not weighted.

floyd_warshall_predecessor_and_distance
floyd_warshall_numpy
all_pairs_shortest_path
all_pairs_shortest_path_length
all_pairs_dijkstra_path
bellman_ford_predecessor_and_distance
all_pairs_bellman_ford_path
all_pairs_bellman_ford_path_length

Notes

Johnson’s algorithm is suitable even for graphs with negative weights. It works by using the Bellman–Ford algorithm to compute a transformation of the input graph that removes all negative weights, allowing Dijkstra’s algorithm to be used on the transformed graph.

The time complexity of this algorithm is $$O(n^2 \log n + n m)$$, where $$n$$ is the number of nodes and $$m$$ the number of edges in the graph. For dense graphs, this may be faster than the Floyd–Warshall algorithm.

Examples

>>> graph = nx.DiGraph()