find_partition_with_rep_rcpp: Finds the optimal partition using the Leiden algorithm

In leidenAlg: Implements the Leiden Algorithm via an R Interface

Finds the optimal partition using the Leiden algorithm

Description

Finds the optimal partition using the Leiden algorithm

Usage

find_partition_with_rep_rcpp(
  edgelist,
  edgelist_length,
  num_vertices,
  direction,
  edge_weights,
  resolution = 1,
  niter = 2L,
  nrep = 1L
)

Arguments

edgelist	The graph edge list
edgelist_length	integer The length of the graph edge list
num_vertices	integer The number of vertices in the graph
direction	boolean Whether the graph is directed or undirected
edge_weights	Vector of edge weights. In weighted graphs, a real number is assigned to each (directed or undirected) edge. For an unweighted graph, this is set to 1. Refer to igraph, weighted graphs.
resolution	Numeric scalar, resoluiton parameter controlling communities detected (default=1.0) Higher resolutions lead to more communities, while lower resolutions lead to fewer communities.
niter	Number of iterations that the algorithm should be run for (default=2)
nrep	Number of replicate starts with random number being updated. (default=10) The result with the best quality will be returned.

Details

For notes of the graph object, refer to https://igraph.org/c/doc/igraph-Basic.html

Examples

library(igraph)

edgelist <- as.vector(t(igraph::as_edgelist(exampleGraph, names=FALSE))) - 1
edgelist_len <- length(edgelist)  ## The length of the graph edge list
n_vertices <- length(igraph::V(exampleGraph)) - 1  ## The number of vertices in the graph
direct <- igraph::is_weighted(exampleGraph)  ## Whether the graph is directed or undirected
edge_weights <- E(exampleGraph)$weight
find_partition_with_rep_rcpp(edgelist, edgelist_len, n_vertices, direct, edge_weights, nrep = 10)

leidenAlg documentation built on Sept. 8, 2023, 5:42 p.m.