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Re: [igraph] Language remmendations
From: |
Tom Backer Johnsen |
Subject: |
Re: [igraph] Language remmendations |
Date: |
Fri, 30 Jan 2009 22:41:12 +0100 |
User-agent: |
Thunderbird 2.0.0.19 (Windows/20081209) |
Tom Backer Johnsen wrote:
I should have added that I normally use Windows XP, but in a pinch I am
able to handle Linux (Ubuntu).
Tom
Gentlepersons:
I need a tool for the analysis (and perhaps simulation as well) of
social networks, in particular small social groups (10+- 2 members or
smaller) in respect to concepts like balance (Heider, Cartwright &
Harary etc.). In other words, the graphs I will be working with are
signed (valued) and directed graphs.
It seems to me that a scan of the literature reveals one serious
alternative in two different versions, igraph for R and Python.
I am fairly familiar with R, much less familiar with Python (but I
anticipate few problems in learning a new programming language), and the
latter one in any case looks like a nice and useful language.
I have downloaded the documentation for the R version of igraph package.
However, I have not been able to locate anything specifically for the
2.5 version of Python. Does that mean that the calls on functions are
essentially the same? Is it possible to find sample Python program
snippets on the net? Also, the R documentation I have is at least half
a year old, which may make a difference, given the fair amount of
activity on this list.
For the possible (type agent-based) simulations I am thinking of using
Netlogo. R should be an execellent tool for any data analysis of the
results from any simulations. So, what I am looking for is some kind of
advice (or opinions) in respect to the most efficient combination of
these tools. For instance, would it be advisable to drop Python
altogether and exclusively work with a combination of Netlogo and R? Or
is the versatility of Python useful?
Tom
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| Tom Backer Johnsen, Psychometrics Unit, Faculty of Psychology |
| University of Bergen, Christies gt. 12, N-5015 Bergen, NORWAY |
| Tel : +47-5558-9185 Fax : +47-5558-9879 |
| Email : address@hidden URL : http://www.galton.uib.no/ |
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