This documents the development version of NetworkX. Documentation for the current release can be found here.
hits_scipy(G, max_iter=100, tol=1e-06, normalized=True)[source]
Returns HITS hubs and authorities values for nodes.
The HITS algorithm computes two numbers for a node.
Authorities estimates the node value based on the incoming links.
Hubs estimates the node value based on outgoing links.
A NetworkX graph
- max_iterinteger, optional
Maximum number of iterations in power method.
- tolfloat, optional
Error tolerance used to check convergence in power method iteration.
- nstartdictionary, optional
Starting value of each node for power method iteration.
- normalizedbool (default=True)
Normalize results by the sum of all of the values.
- (hubs,authorities)two-tuple of dictionaries
Two dictionaries keyed by node containing the hub and authority
If the algorithm fails to converge to the specified tolerance
within the specified number of iterations of the power iteration
This implementation uses SciPy sparse matrices.
The eigenvector calculation is done by the power iteration method
and has no guarantee of convergence. The iteration will stop
after max_iter iterations or an error tolerance of
number_of_nodes(G)*tol has been reached.
The HITS algorithm was designed for directed graphs but this
algorithm does not check if the input graph is directed and will
execute on undirected graphs.
A. Langville and C. Meyer,
“A survey of eigenvector methods of web information retrieval.”
Authoritative sources in a hyperlinked environment
Journal of the ACM 46 (5): 604-632, 1999.
>>> G = nx.path_graph(4)
>>> h, a = nx.hits(G)