From: Gabor Csardi <csardi_at_rmki.kfki.hu>

Date: Mon, 7 Jan 2008 15:45:53 +0100

Date: Mon, 7 Jan 2008 15:45:53 +0100

g <- graph.adjacency( DIST < 0.5, mode="undirected" )
g <- simplify(g)

no.clusters(g)

Btw. from your vector of points you can create the distance matrix by using the 'outer' function.

On Mon, Jan 07, 2008 at 03:26:57PM +0100, Lorenzo Isella wrote:

> Dear All,

*> I hope I am not asking a FAQ. I am dealing with a problem of graph
**> theory [connected components in a non-directed graph] and I do not
**> want to rediscover the wheel.
**> I saw a large number of R packages dealing for instance with the
**> k-means method or hierarchical clustering for spatially distributed
**> data and I am basically facing a similar problem.
**> I am given a set of data which are the positions of particles in 3
**> dimensions; I define two particles A and B to be directly connected if
**> their Euclidean distance is below a certain threshold d. If A and B
**> are directly connected and B and C are directly connected, then A,B
**> and C are connected components (physically it means that they are
**> members of the same cluster).
**> All my N particles then split into k disjointed clusters, each with a
**> certain number of connected components, and this is what I want to
**> investigate.
**> I do not know a priori how many clusters I have (this is my problem
**> with e.g. k-means since k is an output for me); the only input is the
**> set of 3-dimensional particle positions and a threshold distance.
**> The algorithm/package I am looking should return the number of
**> clusters and the composition of each cluster, e.g. the fact that the
**> second cluster is made up of particles {R,T,L}.
**> Consider for instance:
**>
**> # a 2-dimensional example
**> x <- rbind(matrix(rnorm(100, sd = 0.3), ncol = 2),
**> matrix(rnorm(100, mean = 1, sd = 0.3), ncol = 2))
**> colnames(x) <- c("x", "y")
**>
**> How can I then find out how many connected components I have when my
**> threshold distance is d=0.5?
**>
**> Many thanks
**>
**> Lorenzo
**>
**> ______________________________________________
**> R-help_at_r-project.org mailing list
**> https://stat.ethz.ch/mailman/listinfo/r-help
**> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
**> and provide commented, minimal, self-contained, reproducible code.
*

-- Csardi Gabor <csardi_at_rmki.kfki.hu> MTA RMKI, ELTE TTK ______________________________________________ R-help_at_r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.Received on Mon 07 Jan 2008 - 14:50:16 GMT

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