[igraph] Performance issue regarding when calculating induced_subgraph and authority_score within a loop

[Roland Sztaho]

Hello Guys,

I would like to prepare some stats based on clusters made by cluster_label_prop() method. When I use authority_score() and induced_subgraph() within a loop, it shows weak performance and I am looking for a workaround to speed up the code. My network contains approx. 3.000.000 edges and 250.000 clusters. I think calculation of these measure for the clusters without the loop could be a good point, however I didn't find a way in the docs for this.

R version 3.2.5 (2016 04 14)

igraph package version 1.0.1

OS: windows 7 64bit

Here is what I have so far:

library("igraph")

library("plyr")

setwd("C:/Projects/R/igraph")

g_in = read.csv("my_network.csv", sep=" ")

g = graph.data.frame(g_in, directed=FALSE)

clust = groups(cluster_label_prop(g, weights=E(g)$weight))

clust_count <- length(clust)

clustm <- as.matrix(ldply((clust), data.matrix))

clustm1 <- clustm[clustm[, ".id"] == 1, 2]

g_sub = induced_subgraph(g, clustm1)

auth_scr = as.matrix(authority_score(g_sub)$vector)

for (i in 2:clust_count) {

g_sub = induced_subgraph(g, clustm[clustm[, ".id"] == i, 2])

auth_scr = rbind(as.matrix(auth_scr), as.matrix(authority_score(g_sub)$vector))

}

Any suggestions would be great!

Thanks,

Roland