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

From: Gábor Csárdi
Subject: Re: [igraph] best method of preserving network interactions in a 2D map?
Date: Fri, 19 Aug 2011 14:32:25 +0200


please stay on the list. Thanks. If you have very long distances and you want to keep these in the 2D layout, then there is not much you can do IMHO. Could you not work with the logarithm of the distances instead? The logarithm makes the distance distribution less skewed.


On Thu, Aug 18, 2011 at 4:24 PM, James T Metz <address@hidden> wrote:


        Thank you for your response.

        I have already tried the using cmdscale and smacof within R.

        My input distance matrix contains many "long" distances.  The
output 2D coordinates from cmdscale do not reproduce my input distance
matrix very well.  I am getting distance errors on the order of the dimensions
of the 2D map!  Hence my points might as well be anywhere!

        I am getting similar behavior with smacof.  

        I have also tried various weighting schemes with little success so

        I am trying Igraph since there might be some advantage to having my
nodes being layed out in 2D and not overlapping.  This approach might work
for some cases, but may not be useful in general.

        Jim Metz

James T. Metz, Ph.D.
Senior Scientist III Chemistry

GPRD R4DG AP52 - 01D10P
Abbott Laboratories
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Abbott Park, IL  60064 - 6100

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From: Gábor Csárdi <address@hidden>
To: Help for igraph users <address@hidden>
James T Metz <address@hidden>
Date: 08/18/2011 05:15 AM
Subject: Re: [igraph] best method of preserving network interactions in a 2D map?
Sent by: address@hidden

On Sun, Aug 14, 2011 at 9:35 PM, James T Metz <address@hidden> 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.

If you use R, then you don't need igraph for this, see the cmdscale() function.



Gabor Csardi <address@hidden>     MTA KFKI RMKI

Gabor Csardi <address@hidden>     MTA KFKI RMKI

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