scipy.sparse.csgraph.connected_components(csgraph, directed=True, connection='weak', return_labels=True)

Analyze the connected components of a sparse graph

New in version 0.11.0.


csgraph : array_like or sparse matrix

The N x N matrix representing the compressed sparse graph. The input csgraph will be converted to csr format for the calculation.

directed : bool, optional

If True (default), then operate on a directed graph: only move from point i to point j along paths csgraph[i, j]. If False, then find the shortest path on an undirected graph: the algorithm can progress from point i to j along csgraph[i, j] or csgraph[j, i].

connection : str, optional

[‘weak’|’strong’]. For directed graphs, the type of connection to use. Nodes i and j are strongly connected if a path exists both from i to j and from j to i. Nodes i and j are weakly connected if only one of these paths exists. If directed == False, this keyword is not referenced.

return_labels : str, optional

If True (default), then return the labels for each of the connected components.


n_components: int

The number of connected components.

labels: ndarray

The length-N array of labels of the connected components.


[R204]D. J. Pearce, “An Improved Algorithm for Finding the Strongly Connected Components of a Directed Graph”, Technical Report, 2005