Note

This is the documentation for the current state of the development branch of rustworkx. The documentation or APIs here can change prior to being released.

rustworkx.hits#

hits(graph, /, weight_fn=None, nstart=None, tol=1e-08, max_iter=100, normalized=True)#

Computes the hubs and authorities in a PyDiGraph.

For details on the HITS algorithm, refer to:

J. Kleinberg. “Authoritative Sources in a Hyperlinked Environment”. Journal of the ACM, 46 (5), (1999). <http://www.cs.cornell.edu/home/kleinber/auth.pdf>

This function uses a power iteration method to compute the hubs and authorities and convergence is not guaranteed. The function will stop when max_iter iterations is reached or when the computed vector between two iterations is smaller than the error tolerance multiplied by the number of nodes.

In the case of multigraphs the weights of any parallel edges will be summed when computing the hubs and authorities.

Parameters:

  • graph (PyDiGraph) – The graph object to run the algorithm on

  • weight_fn – An optional input callable that will be passed the edge’s payload object and is expected to return a float weight for that edge. If this is not specified 1.0 will be used as the weight for every edge in graph

  • nstart (dict) – Optional starting value for the power iteration for each node.

  • tol (float) – The error tolerance used when checking for convergence in the power method. If this is not specified default value of 1e-8 is used.

  • max_iter (int) – The maximum number of iterations in the power method. If not specified a default value of 100 is used.

  • normalized (boolean) – If the scores should be normalized (defaults to True).

Returns:

a tuple of read-only dict-like object whose keys are the node indices. The first value in the tuple contain the hubs scores. The second value contains the authority scores.

Return type:

tuple[CentralityMapping, CentralityMapping]