info.centrality: Extensions to iGraph for Information Centrality

In TomKellyGenetics/info.centrality: an R implementation of information centrality using igraph

Description

Functions to compute the information centrality of a vertex (node) and network respectively. Includes a network efficiency measure to compute as a metric for information centrality. Uses graphs functions as an extension of igraph.

Usage

network.efficiency(graph)

info.centrality.vertex(graph, net = NULL, verbose = F)

info.centrality.network(graph, net = network.efficiency(graph), verbose = F)

Arguments

graph	An igraph object. May be directed or weighted as long as a shortest path can be computed.
net	Numeric. Efficiency of the Network without any nodes removed. Defaults to computing for Graph given as input, can be given as a numeric if computed in advance to save run time.
verbose	Logical. Whether computing information centrality of each node prints to monitor progress of a potentially long run-time. Defaults to FALSE.

Examples

#generate example graphs
library("igraph")
g1 <- make_ring(10)
g2 <- make_star(10)

#show network paths
distances(g1)
shortest_paths(g1, 5)

#compute efficiency of full graphs
network.efficiency(g1)
network.efficiency(g2)

#compute information centrality (relative efficency when removed) for each node
info.centrality.vertex(g1)
info.centrality.vertex(g2)

#compute total information centrality for a network
info.centrality.network(g1)
info.centrality.network(g2)

TomKellyGenetics/info.centrality documentation built on May 9, 2019, 4:53 p.m.