pylibcugraph.hits#

pylibcugraph.hits(ResourceHandle resource_handle, _GPUGraph graph, double tol, size_t max_iter, initial_hubs_guess_vertices, initial_hubs_guess_values, bool_t normalized, bool_t do_expensive_check)[source]#

Compute HITS hubs and authorities values for each vertex

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.

Parameters:
resource_handleResourceHandle

Handle to the underlying device resources needed for referencing data and running algorithms.

graphSGGraph or MGGraph

The input graph, for either Single or Multi-GPU operations.

tolfloat, optional (default=1.0e-5)

Set the tolerance the approximation, this parameter should be a small magnitude value. This parameter is not currently supported.

max_iterint, optional (default=100)

The maximum number of iterations before an answer is returned.

initial_hubs_guess_verticesdevice array type, optional (default=None)

Device array containing the pointer to the array of initial hub guess vertices

initial_hubs_guess_valuesdevice array type, optional (default=None)

Device array containing the pointer to the array of initial hub guess values

normalizedbool, optional (default=True)
do_expensive_checkbool

If True, performs more extensive tests on the inputs to ensure validitity, at the expense of increased run time.

Returns:
A tuple of device arrays, where the third item in the tuple is a device
array containing the vertex identifiers, the first and second items are device
arrays containing respectively the hubs and authorities values for the corresponding
vertices

Examples

# FIXME: No example yet