igraph

I need view (drawn or plot) the communities structure in networks I have this: import igraph from random import randint def _plot(g, membership=None): layout = g.layout("kk") visual_style = {} visual_style["edge_color"] = "gray" visual_style["vertex_size"] = 30 visual_style["layout"] = layout visual_style["bbox"] = (1024, 768) visual_style["margin"] = 40 for vertex in g.vs(): vertex["label"] = vertex.index if membership is not None: colors = [] for i in range(0, max(membership)+1): colors.append('%06X' % randint(0, 0xFFFFFF)) for vertex in g.vs(): vertex["color"] = str('#') + colors[membership

Given is a tree: library(igraph) # setup graph g= graph.formula(A -+ B, A -+ C, B -+ C, B -+ D, B -+ E ) plot(g, layout = layout.reingold.tilford(g, root="A")) Vertex "A" is the root of the tree, while vertices "C", "D", "E" are considered as terminal leaves. Problem: The task is to find all paths between root and leaves. I fail with following code, as it only provides the shortest paths: # find root and leaves leaves= which(degree(g, v = V(g), mode = "out")==0, useNames = T) root= which(degree(g, v = V(g), mode = "in")==0, useNames = T) # find all paths paths= lapply(root, function(x) get.all

I am using Igraph package in R and when I am accessing the list of vertices names through V(graph), I am getting the following result: Vertex sequence: [1] "d66cp96igcdnt25brjeics9d11" "bovlonq25tmuaiak6do92v9cj0" "simj1u4714pa07p38vhstusf36" "6t6tnkoh4ftbgt787pvpmp1323" [5] "mf987tcmm8u8j3pdo4cts6jml3" The problem that I need a vectors of these names, but this is structure(1:20, class = "igraph.vs", env = <environment>) my ideas to transform it with as.vector(), as.factor did not yield a result. Is there a way how to convert it to a vector of strings? .... Ok, I found a way out: V(graph)$name

I am wondering if there is a generic way to overlay any R plot / visualization appearing in the R output window with a logo (as well as position it) so output is always branded? I read this post where they use a stripe banner as part of ggplot, but is there more of a generic way of doing this so I can include it in any output to automatically put the appropriate branding in particular location (realizing it will likely have to be adjusted, but at least so it is always there) so I cna have it be part of say the 'default code template' so whether I or my colleague use generic plot, igraph,

How would you load the results of a Cypher query into an igraph in python, keeping all the edge and vertex attributes? This is easy with py2neo and igraph's Graph.TupleList method. You'll need both py2neo and igraph installed. pip install py2neo pip install python-igraph Both of these packages rely on a Graph class so we should alias them as something else on import. from py2neo import Graph as pGraph from igraph import Graph as iGraph First, connect to Neo4j with py2neo's Graph object. neo4j = pGraph() Then write a Cypher query to return an edgelist. Let's say we have the example movie

I made a small change to the source code of the igraph package because I want to implement the forest fire method based on the breadth first search method . I used Rtools to build the package and followed the steps as this link . But, I got a error message: foreign-graphml.c:38:29: fatal error: libxml/encoding.h: No such file or directory. I tested using the source code, but still had the same error. I also used the install.packages() method. It still showed the same error. Update: I downloaded the Libxml2 and set the bin location to the path. The libxml/encoding.h file is actually in the

I found the following question ( Find distance of route from get.shortest.paths() ) very helpful, but would like to take it one step further. I have added one column to the data frame and I would like to get the "total distance" related to the min newcost path. Below the igraph / R code that I used. df2 = rbind(c(234,235,21.6,75), c(234,326,11.0,35), c(235,241,14.5,78), c(326,241,8.2,98), c(241,245,15.3,75), c(234,245,38.46,65)) df2 = as.data.frame(df2) names(df2) = c("start_id","end_id","newcost","distance") df2 require(igraph) g2 <- graph.data.frame(df2, directed=FALSE) tkplot(g2) (tmp2 =