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Calculate massively parallelised personalised page rank scores

rs_page_rank_parallel.Rd

Helper function to calculate in parallel on the same (unweighted) network the personalised page rank as fast as possible. Can be used for permutations type approaches.

Usage

rs_page_rank_parallel(
  node_names,
  from,
  to,
  weights,
  diffusion_scores,
  undirected
)

Arguments

node_names

String vector. Name of the graph nodes.

from

String vector. The names of the from edges from the edge list.

to

String vector. The names of the to edges from the edge list.

weights

Optional weight vector. If NULL, defaults to 1.0 as weight for all edges.

diffusion_scores

List. The personalised vectors for the page rank reset values. Each element must sum to 1 and be of same length of node_names!

undirected

Boolean. Is this an undirected graph.

Value

A matrix of the scores with each row representing an element in the diffusion_scores list (in order), and each column representing the value of the personalised page rank diffusion for this node.