Re: [igraph] Multiplex networks: Edge type related metrics by node

[lookman sanni]

I have been using the default plot, and also Tkplot for a graph of 1K nodes, but with very low density (Less than 10 nodes having a significant local density actually). It takes between 3 and 5 minutes. I should however recognize that I am not using the appropriate material for that (an HP Envy).

On Thu, Dec 4, 2014 at 11:45 AM, Gábor Csárdi <address@hidden> wrote:

So subgraph.edges is slow for you? How long does it take?

Gabor

On Thu, Dec 4, 2014 at 5:09 AM, lookman sanni <address@hidden> wrote:

I was not meaning, but rather fearing it may be. I will be dealing with networks of 20K nodes and 7 layers(subgraphs). I just need to make sure that I am making the most from the optimization opportunities that may exist.

Thank you Fatemeh for the links. I will be looking into that as well.

Regards,

On Mon, Dec 1, 2014 at 5:25 PM, Fatemeh a <address@hidden> wrote:

Hi,

I searched a little some times ago on Multilayered network : you may find them helpful :

http://arxiv.org/pdf/1309.7233v4.pdf

http://arxiv.org/pdf/1407.0742.pdf

 

and here : http://muxviz.net/ a framework  is developed to deal with multilayered network : I didn't work with it and I have no idea whether you could combine these two package or not.

Regards,

Fatemeh

On Sat, Nov 29, 2014 at 1:52 AM, lookman sanni <address@hidden> wrote:

Hello everyone. I am new to SNA and learning how to use the igraph package. I have built a multiplex network from some flat file and would like to compute couple of metrics on top of that network:

• The number of edge types by node (multiplexity)
• A metric (matrix, contingent table) of edge types association between the same nodes (e.g: money transfer + good transfer: 20 pairs of nodes; money transfer + kinship: 120 pairs of nodes)

I have not seen any likely metrics in my web searches. Would I need to write them ? If yes, is there any available guideline on how to contribute to igraph ?

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Best Regards

Lookman SANNI
http://blog.lookouster.org

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regards

F..A

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Lookman SANNI
http://blog.lookouster.org

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Best Regards

Lookman SANNI
http://blog.lookouster.org