average_shortest_path_length(G, weight=None, method=None)
The average shortest path length is
$$a =\sum_{s,t \in V} \frac{d(s, t)}{n(n-1)}$$where :None:None:`V` is the set of nodes in G, :None:None:`d(s, t)` is the shortest path from :None:None:`s` to t, and :None:None:`n` is the number of nodes in G.
If None, every edge has weight/distance/cost 1. If a string, use this edge attribute as the edge weight. Any edge attribute not present defaults to 1. 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.
The algorithm to use to compute the path lengths. Supported options are 'unweighted', 'dijkstra', 'bellman-ford', 'floyd-warshall' and 'floyd-warshall-numpy'. Other method values produce a ValueError. The default method is 'unweighted' if :None:None:`weight` is None, otherwise the default method is 'dijkstra'.
If G is the null graph (that is, the graph on zero nodes).
If G is not connected (or not weakly connected, in the case of a directed graph).
If :None:None:`method` is not among the supported options.
Returns the average shortest path length.
>>> G = nx.path_graph(5)
... nx.average_shortest_path_length(G) 2.0
For disconnected graphs, you can compute the average shortest path length for each component
>>> G = nx.Graph([(1, 2), (3, 4)])See :
... for C in (G.subgraph(c).copy() for c in nx.connected_components(G)):
... print(nx.average_shortest_path_length(C)) 1.0 1.0
The following pages refer to to this document either explicitly or contain code examples using this.
networkx.algorithms.shortest_paths.generic.average_shortest_path_length
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