Re: [igraph] best method of preserving network interactions in a 2D map?

[Tamás Nepusz]

Actually, I just realized that layout.mds is already a part of the R interface 
of igraph even in 0.5.4, so if you happen to use igraph from R, then just use 
that. The Python interface does not support MDS in 0.5.4, only in 0.6.

-- 
T.

On 14 Aug 2011, at 21:35, James T Metz wrote:

> 
> Igraph List, 
> 
>         Suppose I have a set of interactions e.g., similarities or distances 
> where distance = 1 - similarity 
> for a set of nodes.  I can read in those interactions, generate a network and 
> output the 2D coordinates. 
> 
>         Suppose I would like to preserve the input similarities (or 
> distances) as much as possible so that 
> if I computed the Euclidean distances from the resulting network 2D 
> coordinates, I would get an excellent 
> agreement with the original input distances (similar to multidimensional 
> scaling). 
> 
>         Is this possible using the igraph package?  If so, what functions and 
> options should be used. 
> 
>         I already know how to generate a network and output coordinates, but 
> I am currently not obtaining 
> very good agreement between the input distances and the network 2D distances 
> between nodes.  I have 
> tried various weight functions where weight = f(similarity), but I can not 
> seem to get this to work very 
> well either. 
> 
>         Am I trying to do something that is not currently possible with 
> Igraph, or am I just ignorant of 
> the appropriate function and options? 
> 
>         I greatly welcome comments and suggestions. 
> 
>         Thank you. 
> 
>         Regards, 
>         Jim Metz 
>         
> 
> James T. Metz, Ph.D.
> Senior Scientist III Chemistry
> 
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