Reading SNA data for #snaspb2013

library(RCurl)
library(igraph)
library(compiler)

su<-function(x) return(sort(unique(x)))
su<-cmpfun(su)

read.sstab<-function(theurl, ...){ #Function to read in a data table from online
  #_theurl_ refers to the location of the data
  #_..._ are parameters passed onto read.table
  require(RCurl)
  outtab<-getURL(theurl, ssl.verifypeer=FALSE)
  outtab<-textConnection(outtab)
  outtab<-read.table(outtab, sep="\t", ...)
  return(outtab)
  }

#Import the data
wikidat<-read.sstab("http://pastebin.com/raw.php?i=UVmTznBj", header=TRUE, skip=6)
#Convert the data to igraph
wikidat<-graph.data.frame(wikidat, directed=TRUE)

V(wikidat)$comp.w<-clusters(wikidat, mode="weak")$membership
V(wikidat)$comp.s<-clusters(wikidat, mode="strong")$membership

#I'll need to recalculate these scores
wikidat.eb<-read.sstab("http://pastebin.com/raw.php?i=w4fTuUje", header=TRUE) #Read in edge betweenness scores
wikidat<-igraph::set.edge.attribute(wikidat, "edge.betw", value=wikidat.eb$Edge.Betw) #Set edge betweenness as an edge attribute
wikidat<-igraph::set.edge.attribute(wikidat, "max.minus.edge.betw", value=wikidat.eb$max.minus.Edge.Betw) #Set max(edge betweenness) - edge betweenness as an attribute
rm(wikidat.eb)

download.file("http://pastebin.com/raw.php?i=a7sF1V75", "snaspb2013.net") #Download data
snaspb2013<-read.graph("snaspb2013.net", "pajek") #Create igraph object
file.remove("snaspb2013.net") #Remove downloaded item

V(snaspb2013)$indegree<-degree(snaspb2013, mode="in")
V(snaspb2013)$outdegree<-degree(snaspb2013, mode="out")
V(snaspb2013)$totaldegree<-degree(snaspb2013, mode="total")
V(snaspb2013)$loc.trans<-transitivity(snaspb2013, "local")

V(snaspb2013)$betw<-betweenness(snaspb2013)
E(snaspb2013)$eb<-edge.betweenness(snaspb2013)
V(snaspb2013)$comp.w<-clusters(snaspb2013, mode="weak")$membership
V(snaspb2013)$comp.s<-clusters(snaspb2013, mode="strong")$membership
V(snaspb2013)$closeness<-closeness(snaspb2013)
V(snaspb2013)$evcent<-evcent(snaspb2013)$vector
V(snaspb2013)$kc.undir<-graph.coreness(as.undirected(snaspb2013, mode="collapse"))

snaspb2013.sg.members<-which(V(snaspb2013)$comp.w == which.max(clusters(snaspb2013, mode="weak")$csize))
snaspb2013.sg<-induced.subgraph(snaspb2013, snaspb2013.sg.members)
snaspb2013.comms<-multilevel.community(as.undirected(snaspb2013.sg, mode="collapse"))
snaspb2013.comms$modularity
V(snaspb2013.sg)$comms<-snaspb2013.comms$membership
names(snaspb2013.comms$membership)<-V(snaspb2013.sg)$id
sort(snaspb2013.comms$membership)
snaspb2013.comms.w<-multilevel.community(as.undirected(snaspb2013.sg, mode="collapse"), weights=max(E(snaspb2013.sg)$eb)-E(snaspb2013.sg)$eb)
snaspb2013.comms.w$modularity
V(snaspb2013.sg)$comms.w<-snaspb2013.comms.w$membership
names(snaspb2013.comms.w$membership)<-V(snaspb2013.sg)$id
sort(snaspb2013.comms.w$membership)

snaspb.layout<-layout.fruchterman.reingold(snaspb2013, params=list(niter=5000, area=vcount(snaspb2013)^3))
V(snaspb2013)$x<-snaspb.layout[,1]
V(snaspb2013)$y<-snaspb.layout[,2]
rm(snaspb.layout)

snaspb2013.sg.layout<-layout.fruchterman.reingold(snaspb2013.sg, params=list(niter=5000, area=vcount(snaspb2013.sg)^3))
V(snaspb2013.sg)$x<-snaspb2013.sg.layout[,1]
V(snaspb2013.sg)$y<-snaspb2013.sg.layout[,2]
rm(snaspb2013.sg.layout)