This seems a single linkage clustering issue:
> grouping <- hclust(dist(data.frame(x,y)),"single")
> cutree(grouping, h=0.5)
[1] 1 1 1 2 3 3 3
Cheers,
Marcelino
At 13:04 26/10/2010, jgarcia at ija.csic.es wrote:
Dear all,
I am wondering if there is a direct function (I cannot find any) in R, to
obtain, a "factor" vector to identify which points could be grouped in a
set, using a specific threshold distance as clustering criterion.
#e.g, with 7 points with coordinates:
x <- c(1.01,0.95,1.05,1.03,3.03,2.99,3.04)
y <- c(3.01,3.02,3.04,5.23,2.01,2.02,1.98)
# and, let's say, distance threshold 0.5, the answer would be:
(1,1,1,2,3,3,3)
# where the threshold is the maximum distance between any two points for
each cluster
A better approach would be that threshold could be specified as the
distance between any point in each cluster, and its corresponding center
of mass for that cluster, but I guess this would require some loops.
Isn't
it? S, I would be happy enough with the abovementioned approach.
If there isn't a direct function, don't worry. I'll try to find a
solution
computing distances...
Thanks,
Javier
---
is it possible to load a complete Grass mapset into a raster stack or
brick
with a single command?
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