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cmclean5/rSpectral
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The goal of ‘rSpectral’ is to make Spectral Modularity graph clusteringmethod available to most of R graph frameworks.
You can install the development version of rSpectral fromGitHub with:
# install.packages("devtools")devtools::install_github("cmclean5/rSpectral")
The stable version is available on CRAN:
install.packages("rSpectral")This is a basic example which shows you how to solve a common problem
- load the karate club graph and plot Faction membership:
library(rSpectral)library(igraph)#>#> Attaching package: 'igraph'#> The following objects are masked from 'package:stats':#>#> decompose, spectrum#> The following object is masked from 'package:base':#>#> uniondata(karate,package="igraphdata")l<-layout_nicely(karate)memT<-V(karate)$Factionpalette<- rainbow(max(as.numeric(memT)))plot(karate,vertex.color=palette[memT],layout=l)
- run spectral clustering on graph
mem0<-igraph::membership(rSpectral::spectral_igraph_communities(karate))
- plot the graph with membership colors
palette<- rainbow(max(as.numeric(mem0)))plot(karate,vertex.color=palette[mem0],layout=l)
- run spectral clustering on graph, fixing neighbouring nodes found insame community
mem1<-igraph::membership(rSpectral::spectral_igraph_communities(karate,fix_neig=1))
- and plot again
palette<- rainbow(max(as.numeric(mem1)))plot(karate,vertex.color=palette[mem1],layout=l)
- run spectral clustering - fixing neighbouring nodes, Cnmin=5
mem1.5<-igraph::membership(rSpectral::spectral_igraph_communities(karate,fix_neig=1,Cn_min=5))
- and the last plot
palette<- rainbow(max(as.numeric(mem1.5)))plot(karate,vertex.color=palette[mem1.5],layout=l)
GraphNEL objects could be processed similarily, all other graph typescould be converted either toigraph or toGraphNEL by packages suchasIntergraph.
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