Re: [igraph] Community similarity / dissimilarity

[Tim Wilson]

Wow!

Thank you Tamas, that's perfect..

: )

Thanks again

On Wed, Dec 19, 2012 at 4:25 PM, Tamás Nepusz <address@hidden> wrote:
>> vc = g.community_infomap()
> You could try the following:
>
> g2 = g.copy()
> g2.contract_vertices(vc.membership)
> g2.es["weight"] = 1
> g2.simplify(combine_edges="sum")
>
> This would give you a graph where the nodes represent the communities of the 
> original graph, the edges are weighted, and the weight of an edge going 
> between node A and B is the number of edges connecting community A and B. 
> g2.get_adjacency(attribute="weight") would then give you the weighted 
> adjacency matrix of g2, which is essentially a similarity matrix between the 
> communities. Of course it is very well conceivable that other similarity or 
> distance measures make more sense, but this is a good starting point.
>
>> My ultimate goal is to use this similarity matrix and multidimensional
>> scaling to make a nice 2d layout of the discovered communities
> You can use any layout algorithm on g2 (including g2.layout_mds for what it's 
> worth) to obtain a layout.
>
> Cheers,
> Tamas
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