User:Timothee Flutre/Notebook/Postdoc/2011/11/07
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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). |