Repository of R scripts used by IRIDIA members

From IridiaWiki
Jump to navigationJump to search
The printable version is no longer supported and may have rendering errors. Please update your browser bookmarks and please use the default browser print function instead.

Boxplot of solution values by algorithm

Tai100a 1000.png


In order to produce boxplots like the one above you can look at the R source used to produce it.


optimal_values<-read.table("optimal_values_100.txt",header=TRUE)
resPIR2OPT<-read.table("parallel_independent_2-opt_100_100.txt",header=TRUE)
resSEQ2OPT<-read.table("sequential_2-opt_100_800.txt",header=TRUE)
resSEQ22OPT<-read.table("sequential2_2-opt_100_100.txt",header=TRUE)
resFC1x102OPT<-read.table("fc.1.x.10_2-opt_100_100.txt",header=TRUE)
resFC26102OPT<-read.table("fc.2.6.10_2-opt_100_100.txt",header=TRUE)
resFC27102OPT<-read.table("fc.2.7.10_2-opt_100_100.txt",header=TRUE)
resFC28102OPT<-read.table("fc.2.8.10_2-opt_100_100.txt",header=TRUE)
resFC29102OPT<-read.table("fc.2.9.10_2-opt_100_100.txt",header=TRUE)
resFC36102OPT<-read.table("fc.3.6.10_2-opt_100_100.txt",header=TRUE)
resFC37102OPT<-read.table("fc.3.7.10_2-opt_100_100.txt",header=TRUE)
resFC38102OPT<-read.table("fc.3.8.10_2-opt_100_100.txt",header=TRUE)
resFC39102OPT<-read.table("fc.3.9.10_2-opt_100_100.txt",header=TRUE)
resHC1x102OPT<-read.table("hc.1.x.10_2-opt_100_100.txt",header=TRUE)
resHC26102OPT<-read.table("hc.2.6.10_2-opt_100_100.txt",header=TRUE)
resHC27102OPT<-read.table("hc.2.7.10_2-opt_100_100.txt",header=TRUE)
resHC28102OPT<-read.table("hc.2.8.10_2-opt_100_100.txt",header=TRUE)
resHC29102OPT<-read.table("hc.2.9.10_2-opt_100_100.txt",header=TRUE)
resHC36102OPT<-read.table("hc.3.6.10_2-opt_100_100.txt",header=TRUE)
resHC37102OPT<-read.table("hc.3.7.10_2-opt_100_100.txt",header=TRUE)
resHC38102OPT<-read.table("hc.3.8.10_2-opt_100_100.txt",header=TRUE)
resHC39102OPT<-read.table("hc.3.9.10_2-opt_100_100.txt",header=TRUE)
resRW1x102OPT<-read.table("rw.1.x.10_2-opt_100_100.txt",header=TRUE)
resRW26102OPT<-read.table("rw.2.6.10_2-opt_100_100.txt",header=TRUE)
resRW27102OPT<-read.table("rw.2.7.10_2-opt_100_100.txt",header=TRUE)
resRW28102OPT<-read.table("rw.2.8.10_2-opt_100_100.txt",header=TRUE)
resRW29102OPT<-read.table("rw.2.9.10_2-opt_100_100.txt",header=TRUE)
resRW36102OPT<-read.table("rw.3.6.10_2-opt_100_100.txt",header=TRUE)
resRW37102OPT<-read.table("rw.3.7.10_2-opt_100_100.txt",header=TRUE)
resRW38102OPT<-read.table("rw.3.8.10_2-opt_100_100.txt",header=TRUE)
resRW39102OPT<-read.table("rw.3.9.10_2-opt_100_100.txt",header=TRUE)
resUR1x102OPT<-read.table("ur.1.x.10_2-opt_100_100.txt",header=TRUE)
resUR26102OPT<-read.table("ur.2.6.10_2-opt_100_100.txt",header=TRUE)
resUR27102OPT<-read.table("ur.2.7.10_2-opt_100_100.txt",header=TRUE)
resUR28102OPT<-read.table("ur.2.8.10_2-opt_100_100.txt",header=TRUE)
resUR29102OPT<-read.table("ur.2.9.10_2-opt_100_100.txt",header=TRUE)
resUR36102OPT<-read.table("ur.3.6.10_2-opt_100_100.txt",header=TRUE)
resUR37102OPT<-read.table("ur.3.7.10_2-opt_100_100.txt",header=TRUE)
resUR38102OPT<-read.table("ur.3.8.10_2-opt_100_100.txt",header=TRUE)
resUR39102OPT<-read.table("ur.3.9.10_2-opt_100_100.txt",header=TRUE)

res<-rbind(resFC1x102OPT,resFC26102OPT,resFC27102OPT,resFC28102OPT,resFC29102OPT,resFC36102OPT,resFC37102OPT,resFC38102OPT,resFC39102OPT,resRW1x102OPT,resRW26102OPT,resRW27102OPT,resRW28102OPT,resRW29102OPT,resRW36102OPT,resRW37102OPT,resRW38102OPT,resRW39102OPT,resHC1x102OPT,resHC26102OPT,resHC27102OPT,resHC28102OPT,resHC29102OPT,resHC36102OPT,resHC37102OPT,resHC38102OPT,resHC39102OPT,resUR1x102OPT,resUR26102OPT,resUR27102OPT,resUR28102OPT,resUR29102OPT,resUR36102OPT,resUR37102OPT,resUR38102OPT,resUR39102OPT,resPIR2OPT,resSEQ2OPT,resSEQ22OPT)

linstance<-levels(res$instance)

res.split<-split(1:nrow(res), list(res$instance, res$try, res$idalgo), drop=TRUE)

min.list <- lapply(res.split, function(x){
        x[match(min(res$best[x]), res$best[x])]
        })

# matches return the first among all the values with min best!!!
# so is not the one with minimal time

min.vector <- unlist(min.list)

bestalgo<-res[min.vector,]

bestalgo.split <- split(1:nrow(bestalgo), bestalgo$instance, drop=TRUE)

for (i in (1:length(bestalgo.split)))
{
        bestalgo.vector <- unlist(bestalgo.split[i])
        bestalgo.temp <- bestalgo[bestalgo.vector,]
        l<-split(bestalgo.temp$best,bestalgo.temp$idalgo)

        epsfile=paste(linstance[i],"_100_nolim.eps",sep="")
        postscript(file=epsfile,onefile=TRUE,horizontal=TRUE)
        par(mar=c(5,5,5,3),cex.axis=0.7,las=2,mgp=c(4, 1, 0))
        title_plot=paste("100 iterations - instance ",linstance[i],sep="")
        boxplot(l,xlab="",ylab="solution value",names=c(levels(bestalgo$idalgo)),main=title_plot,yaxt="n",ylim=c(optimal_values[optimal_values$instance==linstance[i],]$optimum,max(bestalgo.temp$best)))
        axis(2, seq(from=optimal_values[optimal_values$instance==linstance[i],]$optimum,to=max(bestalgo.temp$best),length.out=10))
        abline(h=optimal_values[optimal_values$instance==linstance[i],]$optimum)
        grid(nx=0, ny=55,col="gray5")
        dev.off()
}