Mercurial > repos > bornea > network_attributes
comparison Calculate_attributes.R @ 1:e4a55256547a draft
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| author | bornea |
|---|---|
| date | Wed, 18 Oct 2017 15:23:06 -0400 |
| parents | |
| children |
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| 0:c8a8a1e90a9d | 1:e4a55256547a |
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| 1 library(igraph) | |
| 2 library(dplyr) | |
| 3 library(ggplot2) | |
| 4 | |
| 5 NetworkAttributes <- function(edges,centrality = "eigenvector",community="fast.greedy") { | |
| 6 "This function takes in a SIF formatted dataframe and returns a node attribute dataframe." | |
| 7 "It performs community optimization and calculates a centrality metric." | |
| 8 nodes <- data.frame(V1 = unique(c(as.character(edges[,1]),as.character(edges[,2])))) | |
| 9 graph <- graph.data.frame(edges, directed = FALSE, vertices = nodes) | |
| 10 graph = simplify(graph) | |
| 11 if(community == "optimal"){V(graph)$comm <- membership(optimal.community(graph))} # computationally intensive | |
| 12 if(community == "fast.greedy"){V(graph)$comm <- membership(fastgreedy.community(graph))} # for larger datasets\ | |
| 13 if(community == "edge.betweenness"){V(graph)$comm <- membership(edge.betweenness.community(graph))} | |
| 14 if(community == "walk.trap"){V(graph)$comm <- membership(walktrap.community(graph))} | |
| 15 if(community == "spin.glass"){V(graph)$comm <- membership(spinglass.community(graph))} | |
| 16 if(community == "leading.eigenvector"){V(graph)$comm <- membership(leading.eigenvector.community(graph))} | |
| 17 if(community == "label.propagation"){V(graph)$comm <- membership(label.propagation.community(graph))} | |
| 18 if(community == "multilevel"){V(graph)$comm <- membership(multilevel.community(graph))} | |
| 19 | |
| 20 if(centrality == "closeness"){V(graph)$closeness <- centralization.closeness(graph)$res} | |
| 21 if(centrality == "betweenness"){V(graph)$betweenness <- centralization.betweenness(graph)$res} | |
| 22 if(centrality == "eigenvector"){V(graph)$eigen <- centralization.evcent(graph)$vector} | |
| 23 if(centrality == "PageRank"){V(graph)$page <- page_rank(graph)$vector} | |
| 24 | |
| 25 return(get.data.frame(graph, what = "vertices")) | |
| 26 } | |
| 27 #calculate_attributes(nodes,edgelist,centrality = "betweenness",community="fastgreedy") | |
| 28 args <- commandArgs(trailingOnly = TRUE) | |
| 29 edgelist <- read.table(file=as.character(args[1]), stringsAsFactors = FALSE,sep="\t",header=FALSE) | |
| 30 write.table(NetworkAttributes(edgelist,args[2],args[3]),"node_attr.txt",sep="\t",quote=FALSE,row.names=FALSE) |