[R-sig-Geo] creating polygons of clusters of points?
Hans Ekbrand
hans at sociologi.cjb.net
Fri Apr 23 16:37:38 CEST 2010
How to create nice polygons from a number of clusters?
I have sorted list of clusters representing hot-spots
> sorted.list.of.clusters
[1] 7 1 11 9 26 2 5 10 33 40 18 28 37 20 30 47 53
whereas my.cluster holds the classification of events (criminal
fire-setting) to clusters:
head(my.cluster, 100)
[1] 1 2 3 3 4 5 6 7 8 5 9 10 11 12 1 13 2 14 15 10 16 17 5 13 7 7 18 19 18 20 20 2 21 16 22 18 10 1
[39] 9 23 4 7 24 9 9 7 7 5 2 11 25 12 7 7 26 27 13 7 7 28 18 28 29 9 2 5 30 11 31 14 18 1 32 26 2 31
[77] 29 33 2 34 2 26 35 36 7 2 35 37 26 38 11 2 11 26 30 7 4 11 8 11
> number.of.fires.at.hotspots <- sapply(sorted.list.of.clusters, function(x) {length(which(my.cluster == x))})
> number.of.fires.at.hotspots
[1] 44 39 38 32 22 21 21 21 15 15 14 14 14 12 12 12 12
The "SpatialPointsDataFrame" object clust.geo.test holds the events.
A list coordinates of the events of each cluster is generated with:
> sapply(sorted.list.of.clusters, function(x) {clust.geo.test at coords[which(my.cluster == x),]})
[[1]]
Ost Nord
[1,] 322737.4 6406939
[2,] 323104.9 6406968
[3,] 323104.9 6406968
...
[[2]]
Ost Nord
[1,] 315359.9 6393110
[2,] 315177.0 6394031
[3,] 314697.8 6394565
...
And I can plot the points in the hot-spots with
> plot(sdn)
> sapply(sorted.list.of.clusters, function(x) {plot(clust.geo.test[which(my.cluster == x),], add = T)})
But would like to plot each cluster as a polygon, ideally filled with
darker colors for clusters with higher number of fires.
I guess I need to create polygons for each cluster and then plot each
polygon. How do you do that?
For your convenience I have created a RData object containing the
objects refered to above and uploaded to this URI
http://sociologi.cjb.net/temp/to-polygons-help.RData, so
print(load(url("http://sociologi.cjb.net/temp/to-polygons-help.RData")))
plot(sdn)
sapply(sorted.list.of.clusters, function(x) {plot(clust.geo.test[which(my.cluster == x),], add = T)})
would get you to the point I am now.
Hans Ekbrand
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