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Andrei,

A very good option for Python is networkx (NX), which I use heavily in my
work.

NX has a gallery of visualizations.  Perhaps you can find there something
which meet your needs:
http://networkx.lanl.gov/gallery.html

You can also hack the NX layout methods to account for the weights any way
you want to.

Cheers,
-Sasha.

On Tue, May 17, 2011 at 3:19 PM, Andrei Boutyline <
[log in to unmask]> wrote:

> ***** To join INSNA, visit http://www.insna.org ***** Thanks a lot to
> everybody who responded!  SOCNET is always so wonderfully helpful.
>
> Looks like there are a whole lot of options for doing this.  I am going to
> give a number of these a try.  If I find that something works especially
> well for displaying these kinds of networks, I'll report back to the list.
>
> Andrei
>
>
> On Tue, May 17, 2011 at 5:21 AM, Carl Nordlund <[log in to unmask]>wrote:
>
>>  Several years ago I experimented with spring-embedding algorithms and
>> wrote a couple of java applet. I have also written a C# (Windows) client
>> program to visualize the social network of the people attending my PhD
>> graduation party, but that one was just an ordinary 2d-open type without
>> calculating Kruskal stress indices.
>>
>> I did an applet prototype that allows data to be displayed in a variety of
>> spring-embedding ways - open 2d, open 3d, closed 2d (i.e. on the surface of
>> a sphere) - and they work well for dense, weighted networks with many nodes.
>> Also, the spring-embedders calculate Kruskal stress indices - although
>> spring-embedders generally doesn't arrive at the optimum minimum for stress,
>> you can tweak the parameters to minimize this value.
>>
>> At that time, I primarily worked with international trade flow data which
>> are also typically very dense and have huge value spans.
>>
>> The program is located here:
>> http://demesta.com/sph_dev/test2/
>>
>> If you could send me your data, preferably in a syntax like this:
>> http://www.demesta.com/sph_dev/test2/data/migflows.txt
>> ...I can install it on the server so you can experiment with the applet to
>> see whether it yields any good output.
>>
>> Or a simple csv-textfile should also work - I can then convert into my
>> format.
>>
>> Yours,
>> Carl
>>
>> Dr Carl Nordlund
>> carl.nordlund(at)hek.lu.se
>> Human Ecology Division, Lund university
>> www.hek.lu.se
>>  ------------------------------
>> *Från:* Social Networks Discussion Forum [[log in to unmask]] för
>> Andrei Boutyline [[log in to unmask]]
>> *Skickat:* den 17 maj 2011 05:49
>> *Till:* [log in to unmask]
>> *Ämne:* [SOCNET] Plotting weighted networks in R or Python?
>>
>>  ***** To join INSNA, visit http://www.insna.org ***** Dear all,
>>
>>
>> I'm hoping somebody can point me to a good tool for laying out and
>> plotting weighted networks.  In my data, every node is connect to every
>> other node, albeit with different tie strengths. So, a layout algorithm that
>> doesn't take weights into account will just give me a ball of nodes.  Is
>> there a library for R or Python that can produce a more meaningful layout
>> from such data?  Or, in the absence of a library, is there a standalone
>> program?
>>
>> (By the way, the total number of nodes in my network under 150.)
>>
>> Thanks a lot!
>> Andrei
>>
>> --
>> Andrei Boutyline
>> University of California, Berkeley
>> PhD Student, Sociology
>> www.ocf.berkeley.edu/~andrei <http://www.ocf.berkeley.edu/%7Eandrei>
>> _____________________________________________________________________
>> SOCNET is a service of INSNA, the professional association for social
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>>
>
>
>
> --
> Andrei Boutyline
> University of California, Berkeley
> PhD Student, Sociology
> www.ocf.berkeley.edu/~andrei <http://www.ocf.berkeley.edu/%7Eandrei>
> _____________________________________________________________________
> SOCNET is a service of INSNA, the professional association for social
> network researchers (http://www.insna.org). To unsubscribe, send an email
> message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET
> in the body of the message.
>



-- 
Alexander "Sasha" Gutfraind
Theoretical Division
Los Alamos National Lab
http://www.cam.cornell.edu/~gfriend/

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