User:Timothee Flutre/Notebook/Postdoc/2011/11/07: Difference between revisions
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(→Entry title: test KMLOCAL) |
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myheatmap(mydata.sort) | myheatmap(mydata.sort) | ||
* try [http://www.cs.umd.edu/~mount/Projects/KMeans/ KMLOCAL], yet another kmeans clustering program: | |||
wget http://www.cs.umd.edu/~mount/Projects/KMeans/kmlocal-1.7.2.tar.gz | |||
cat test_kmlocal.config | |||
show_assignments yes # show final cluster assignments | |||
validate yes # validate assignments | |||
dim 3 # dimension | |||
data_size 1000 # number of data points | |||
seed 1859 # random number seed | |||
read_data_pts matrix.txt # read data points | |||
kcenters 4 # number of centers | |||
max_tot_stage 20 0 0 0 # number of stages | |||
seed 4 # use different seed | |||
run_kmeans swap # run with this algorithm | |||
kmltest -i test_kmlocal.config -o test_kmlocal.out | |||
But it doesn't work on a big dataset (bad_alloc). | |||
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Revision as of 08:16, 8 November 2011
 Project name
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Entry title
S <- 3 # nb of subgroups
V <- 7 # nb of observations
z <- matrix(c(0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,0,0), nrow=V, ncol=S, byrow=TRUE)
myheatmap <- function(z, out.file="") {
def.par <- par(no.readonly=TRUE)
par(mar=c(4,5,3,2), font=2, font.axis=2, font.lab=2, cex=1.5, lwd=2)
if (out.file != "")
pdf(out.file)
layout(mat=cbind(1, 2), width=c(7,1)) # plot + legend
mycol <- rev(heat.colors(4))
image(x=1:NCOL(z), y=1:NROW(z), z=t(z),
xlim=0.5+c(0,NCOL(z)), ylim=0.5+c(0,NROW(z)),
xlab="", ylab="Observations sorted by cluster", main="Custom heatmap",
axes=FALSE, col=mycol)
axis(1, 1:NCOL(z), labels=paste("subgroup", 1:NCOL(z)), tick=0)
par(mar=c(0,0,0,0))
plot.new()
legend("center", legend=sprintf("%.2f", seq(from=min(z), to=max(z), length.out=5)[-1]),
fill=mycol, border=mycol, bty="n")
if (out.file != "")
dev.off()
par(def.par)
}
myheatmap(mydata.sort)
wget http://www.cs.umd.edu/~mount/Projects/KMeans/kmlocal-1.7.2.tar.gz cat test_kmlocal.config show_assignments yes # show final cluster assignments validate yes # validate assignments dim 3 # dimension data_size 1000 # number of data points seed 1859 # random number seed read_data_pts matrix.txt # read data points kcenters 4 # number of centers max_tot_stage 20 0 0 0 # number of stages seed 4 # use different seed run_kmeans swap # run with this algorithm kmltest -i test_kmlocal.config -o test_kmlocal.out But it doesn't work on a big dataset (bad_alloc). | |
