[SciPy-user] Scipy for Cluster Detection

Matthieu Brucher matthieu.brucher@gmail....
Thu Dec 27 00:42:01 CST 2007


Hi,

Sounds like a pseudo correlation clustering problem, isn't ? It's not too
hard to create the clusters once you have the similarity matrix. You can
make a loop and for every point not labeled, you cluster around it every
point that are similar. This way you get a good approximation of your
optimal correlation problem (don't remember which article demonstrates it).

Matthieu

2007/12/27, Lorenzo Isella <lorenzo.isella@gmail.com>:
>
> Dear All,
> I hope this will not sound too off-topic.
> Without going into details, I am simulating the behavior of a set of
> particles interacting with a short-ranged, strongly binding potential. I
> start with a number N of particles which undergo collisions with each
> other and, in doing so, they stick giving rise to clusters.
> The code which does that is not written in Python, but it returns the
> positions of these particles in space.
> As time goes on, more and more particles coagulate around one of these
> clusters. Eventually, they will all end up in the same cluster.
> Two particles are considered to be bounded if their distance falls below
> a certain threshold d.
> A cluster is nothing else than a group of particles all directly or
> indirectly bound together.
> Having said so, I now need an efficient algorithm to look for clusters,
> since at the very least I need to be able to count them to study how the
> number of clusters evolve in time.
> Is there anything suitable for this already implemented in SciPy? I
> wonder if people in Astronomy have similar problems if they need e.g. to
> detect/study clusters of stars.
> Simply I would like not to re-invent the wheel and it goes without
> saying that any suggestions here are really appreciated.
> Many thanks and a nice Xmas break to everybody on this list.
>
> Lorenzo
>
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-- 
French PhD student
Website : http://matthieu-brucher.developpez.com/
Blogs : http://matt.eifelle.com and http://blog.developpez.com/?blog=92
LinkedIn : http://www.linkedin.com/in/matthieubrucher
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