alis.link_analysis.idealized_page_rank

alis.link_analysis.idealized_page_rank(M, tol=1e-06, max_iter=100)

Compute the Idealized PageRank (without Taxation) of a given Transition Matrix

Parameters

Mnumpy array

Transition Matrix: Array of shape (n, n), where n is the number of nodes in the network

tolfloat

Tolerance: Iteration stops if the distance between previous and updated PageRank vectors goes below this value

max_iterinteger

Maximum number of iterations

Returns

vnumpy array

Vector of size n containing the ordinary PageRank values