is_strongly_connected(G)
This function is more theoretically efficient than the ~networkx.algorithms.components.is_strongly_connected
function.
The given graph must be a tournament, otherwise this function's behavior is undefined.
Although this function is more theoretically efficient than the generic strong connectivity function, a speedup requires the use of parallelism. Though it may in the future, the current implementation does not use parallelism, thus you may not see much of a speedup.
This algorithm comes from [1].
A directed graph representing a tournament.
Whether the tournament is strongly connected.
Decides whether the given tournament is strongly connected.
>>> from networkx.algorithms import tournament
... G = nx.DiGraph([(0, 1), (0, 2), (0, 3), (1, 2), (1, 3), (2, 3), (3, 0)])
... tournament.is_strongly_connected(G) True
>>> G.remove_edge(1, 3)See :
... tournament.is_strongly_connected(G) False
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