[igraph] getting k-connected nodes from a vertex

Has igraph any function to retrieve the nodes connected to a specified vertex recursively? For example, a root is connected to 3 leaves, and then these 3 leaves are each connected to 2, 1, 4 leaves respectively, and then that 2, 1, 4 leaves are used again to search. So this should be something like

Re: [igraph] make igraph charts wider

It is called graph.data.frame(). There is a misunderstanding here, I think. An igraph object does not store how the graph will look when you plot it (although you can attach attributes to the graph and these might store some plotting information. I.e. 'g' in the example below has no information abo

Re: [igraph] MST

See write.graph() and the 'ncol' format, i.e. something like this: library(igraph) g <- read.graph("file.txt", format= "ncol") mst <- minimum.spanning.tree(g) write.graph(mst, file="output.txt", format="ncol") Gabor On Tue, Dec 4, 2012 at 3:34 PM, Flavia Rovira wrote: > Hello, > > I´m running

[igraph] MST

Hello, I´m running the minimun.spanning.tree algorithm and I can´t see the output, how can I export the MST results into a .txt?The imput txt is a three columns and n rows file, containing var1, var2 and edge, and i would need that the output has the same format. In previous versions this out

Re: [igraph] Comparing large graphs

> If I remember right, some months ago somebody posted here about > measures to compare networks. I looked for this post in the historial > of the list, but I didn't find it, sorry. This is a thread that seems related, although it is quite old: http://lists.gnu.org/archive/html/igraph-help/2008-04

Re: [igraph] Creation of a random graph with high clustering coefficiant

Hi Jeff, what about geometric random graphs, where nodes are randomly distributed on a plane and connect to nodes within a given distance radius? You might wanna have a look at ?grg.game() if you use the R interface. Maybe one could start like that and add a touch of rewiring once the network is

Re: [igraph] Creation of a random graph with high clustering coefficiant

Hi Jeff, Perhaps there is a smarter way to do this, but I've found that a rewiring approach works well (though it can be slow) for a number of different network properties. You first use the appropriate graph constructor to get a network with the desired degree distribution. Then you can use the

Re: [igraph] Feedback on network animation code?

Very cool. Thank you. On Thu, Nov 29, 2012 at 1:58 PM, Gábor Csárdi wrote: > On Thu, Nov 29, 2012 at 10:52 AM, Jeff Hemsley > wrote: > [...] >> >> The area of code that I'm actually interested in making more efficient >> is where I am fading out the colors of links/vertex because it is a >> loop

[igraph] Creation of a random graph with high clustering coefficiant

I'm looking for a function to create a random graph where nodes have a high clustering coefficient. I'm trying to simulate a large network where there are lots of strong tie clusters with 5 to 7 nodes with a few links to other clusters. So lots of local connections but not very many long range lin

[igraph] Comparing large graphs

Dear all, I am using an algorithm to compare networks based on the shortest-paths and diameter measures, but, of course, it seems to be very slow for large graphs. If I remember right, some months ago somebody posted here about measures to compare networks. I looked for this post in the historial

Re: [igraph] make igraph charts wider

Hi Gabor: Sorry to bother you again. Is it possible to strerch the igraph using data.frame.graph? On Monday, November 26, 2012 3:02:00 PM UTC-5, Mike Dylan wrote: > plot(g, layout = layout.kamada.kawai, vertex.label = V(g)$name, > vertex.label.color= "darkblue",edge.arrow.size=0.8, edge.cu