igraph

let's say I have n igraphs objects g1 , g2 ,.., gn . They are undirected and weighted graphs, i.e. new weight's attribute should be added. I'd like to union n graphs into the weighted graph g . It is known from the documentation (see ?graph.union ) if the n graphs have the weight attribute, it is renamed by adding a _1 and _2 (and _3 , etc.) suffix, i.e. weight_1 , weight_2 ,..., weight_n . I have seen the answer and wrote the code for n=3 graphs (see below). Edited: library(igraph) rm(list=ls(all=TRUE)) # delete all objects g1 <- graph_from_literal(A1-B1-C1) g2 <- graph_from_literal(A2-B2-C2)

I'm wondering if there is a function within igraph to calculate connection probabilities among vertices in a weighted graph, where the weights for the edges are probabilities of connection of the adjacent vertices. I've built a graph based on such an adjacency matrix where adjacent connection probabilities form the weights (this is for a river network so each node of the graph is only connected to a single downstream node). I had hoped to use something like the shortest.paths function in igraph but that sums the weights rather than calculates the product of them and I can't work out a way to

I wonder if anyone has had a similar issue to this and found a solution? I am trying to install igraph for with Python 2.7.9 Anaconda 2.2.0 on Mac osx 10.10.2. I managed to brew install homebrew/science/igraph OK but when I try to pip install python-igraph I get the following error: grep: /usr/lib/libiconv.la: No such file or directory sed: /usr/lib/libiconv.la: No such file or directory libtool: link: `/usr/lib/libiconv.la' is not a valid libtool archive make[3]: *** [libigraph.la] Error 1 make[2]: *** [all] Error 2 make[1]: *** [all-recursive] Error 1 make: *** [all] Error 2 Extracting

I used the fastgreedy algorithm in igraph for my community detection in a weighted, undirected graph. Afterwards I wanted to have a look at the modularity and I got different values for different methods and I am wondering why. I included a short example, which demonstrates my problem: library(igraph) d<-matrix(c(1, 0.2, 0.3, 0.9, 0.9, 0.2, 1, 0.6, 0.4, 0.5, 0.3, 0.6, 1, 0.1, 0.8, 0.9, 0.4, 0.1, 1, 0.5, 0.9, 0.5, 0.8, 0.5, 1), byrow=T, nrow=5) g<-graph.adjacency(d, weighted=T, mode="lower",diag=FALSE, add.colnames=NA) fc<-fastgreedy.community(g) fc$modularity[3] #[1] -0.05011095 modularity(g

I started evaluating igraph library and its functionality. I need to calculate hamiltonian path of a graph generated by igraph_de_bruijn() function. Is there any ready made function in igraph library for that? I don't want to implement it from scratch. An example in C would be perfect. The Hamiltonian path problem can be cast as a subgraph isomorphism problem, for which igraph has several functions. Construct a 1D lattice graph (a "line") with the same number of vertices as your graph, then search for this pattern using subisomorphism functions. Here's an example using the Mathematica

I have a data frame with the following format: name workplace a A b B c A d C e D .... I would like to convert this data frame into an affiliation network in R with the format A B C D ... a 1 0 0 0 b 0 1 0 0 c 1 0 0 0 d 0 0 1 0 e 0 0 0 1 ... and I used the following program: for (i in 1:nrow(A1)) { a1[rownames(a1) == A1$name[i], colnames(a1) == A1$workplace[i]] <- 1 } where A1 is the data frame, and a1 is the affiliation network. However, since I have a large data frame, the above program runs very slow. Is there an efficient way that avoids looping in data conversion? Thank you very much! If

I'm trying to string up some patio lights. Based on another question I asked, I realize I need an algorithm to solve a Route Inspection Problem to figure out the most efficient route the lights should take so there's minimal duplicate edges covered with lights. After some searching I realized that perhaps something like this would be my best bet: Solving Chinese Postman algorithm with eulerization . However, I'm having trouble creating the graph. Here's what it needs to look like: pink circles represent places in the structure I can hang lights from "Start" is the only available electrical

I need to plot a network from a correlation matrix. A small subset of my data: Taxon CD1 CD2 Actinomycetaceae;g__Actinomyces 0.072998825 0.031399459 Coriobacteriaceae;g__Atopobium 0.040946468 0.002703265 Corynebacteriaceae;g__Corynebacterium 0.002517201 0.006446247 Micrococcaceae;g__Rothia 0.001174694 0.002703265 Porphyromonadaceae;g__Porphyromonas 0.023326061 0.114368892 Prevotellaceae;g__Prevotella 0.252894781 0.102308172 Flavobacteriaceae;g__Capnocytophaga 0.001174694 0.029320025 Aerococcaceae;g__Abiotrophia 0.002013761 0.003327095 Carnobacteriaceae;g__Granulicatella 0.042960228 0.049490539