igraph

I'm studying about detection communities in networks. I'm use igraph and Python For the optimal number of communities in terms of the modularity measure: from igraph import * karate = Nexus.get("karate") cl = karate.community_fastgreedy() cl.as_clustering().membership For supply the desired number of communities: from igraph import * karate = Nexus.get("karate") cl = karate.community_fastgreedy() k=2 cl.as_clustering(k).membership However, I like to do this using networkx. I know get optimal number of communities in terms of the modularity measure: import community # --> http://perso.crans.org

I'm using R for networks. I've used the 'network' package, but now using 'igraph'. I can plot the igraph using geographic coords. I can plot a map using 'maptools'(readShapePoly). How can I plot the igraph on top of the map? I have tried new=FALSE and add=TRUE but it doesn't work, plotting the igraph object always overwrites. greece <- readShapePoly.("Z:/GeoData/World_data/Basemaps/Greece/GRC_adm1.shp") df<-data.frame("from" = c.("Athens", "Iraklio", "Thessaloniki", "Patra"), "to"= c("Thessaloniki", "Thessaloniki", "Athens", "Iraklio")) meta <- data.frame("name"=c("Athens", "Iraklio",

I'm trying to mine for 3-node motifs in R using the package igraph . I would like to retrieve the number of motifs for each individual vertex in the graph, which does not appear possible from the graph.motifs() function. So, for the example graph: testGraph = barabasi.game(10, m = 5, power = 2, out.pref = TRUE, zero.appeal = 0.5, directed = TRUE) I can use graph.motifs() to count the total number of each 3-node motif in the entire graph: graph.motifs(testGraph, size = 3) [1] 0 0 26 0 16 0 2 58 0 0 0 0 0 0 0 0 But I would like to know the individual vertex participation. So, how many motifs

I have an network that I would like to analyze using the edge_betweenness community detection algorithm in iGraph. I'm familiar with NetworkX, but am trying to learning iGraph because of it's additional community detection methods over NetworkX. My ultimate goal is to run edge_betweenness community detection and find the optimal number of communities and write a CSV with community membership for each node in the graph. Below is my code as it currently stands. Any help figuring out community membership is greatly appreciated. input data ('network.txt'): 1 2 2 3 2 7 3 1 4 2 4 6 5 4 5 6 7 4 7 8 8

I've a relatively large graph with Vertices: 524 Edges: 1125, of real world transactions. The edges are directed and have a weight (inclusion is optional). I'm trying investigate the various communities within the graph and essentially need a method which: -Calculates all possible communities -Calculates the optimum number of communities -Returns the members/# of members of each (optimum) community So far I've managed to pull together the following code which plots a color coded graph corresponding to the various communities, however I've no idea how to control the number of communities (i.e

I have been searching for an answer to this question but could not find any mention, so I decided to post here. I am trying to see if igraph or any packages provide a simple way to create a "community graph" where each node represents a community in the network and the ties represent ties between the communities. I can get the community detection algorithm to work fine in igraph, but I could not find a way to collapse the results to just show connections between each community. Any assistance would be appreciated. You can simply use the contract.vertices() function. This contracts groups of