Re: [R] How to speed up nested for loop computations

[Max Manfrin]

On 11 Aug 2006, at 12:40, jim holtman wrote:

In your split, you used the dataframe. What you want to do is to split the row numbers to give the list of indices. Once you have dont this, you can 'lapply' this list of indices to a function.

The new R code looks like this:

--- BEGIN CODE ---

optimal_values<-read.table("optimal_values_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)



linstance<-levels(res$instance)



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))

        grid(nx=0, ny=55,col="gray5")
        dev.off()
}

--- END CODE ---




        missing value where TRUE/FALSE needed
In addition: Warning message:
NAs produced by integer overflow in: x[floor(d)] + x[ceiling(d)]








        missing value where TRUE/FALSE needed
In addition: Warning message:
NAs produced by integer overflow in: x[floor(d)] + x[ceiling(d)]

> str(l)
List of 39







----
Max MANFRIN
http://iridia.ulb.ac.be/~mmanfrin/

Once again I have to thank you, because I was able to finally code something that works (except for an error that I'll explain below) and is very fast. resPIR2OPT<-read.table("parallel_independent_2- opt_100_100.txt",header=TRUE) res<-rbind (resFC1x102OPT,resFC26102OPT,resFC27102OPT,resFC28102OPT,resFC29102OPT,r esFC36102OPT,resFC37102OPT,resFC38102OPT,resFC39102OPT,resRW1x102OPT,res RW26102OPT,resRW27102OPT,resRW28102OPT,resRW29102OPT,resRW36102OPT,resRW 37102OPT,resRW38102OPT,resRW39102OPT,resHC1x102OPT,resHC26102OPT,resHC27 102OPT,resHC28102OPT,resHC29102OPT,resHC36102OPT,resHC37102OPT,resHC3810 2OPT,resHC39102OPT,resUR1x102OPT,resUR26102OPT,resUR27102OPT,resUR28102O PT,resUR29102OPT,resUR36102OPT,resUR37102OPT,resUR38102OPT,resUR39102OPT ,resPIR2OPT,resSEQ2OPT,resSEQ22OPT) res.split<-split(1:nrow(res), list(res$instance, res$try, res $idalgo), drop=TRUE) title_plot=paste("100 iterations - instance ",linstance [i],sep="") boxplot(l,xlab="",ylab="solution value",names=c(levels (bestalgo$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) res contains the results of the experiments on 4 problem instances. The code produces the boxplots for the first 3 of them and give an errore on instance number 4 when it should execute the boxplot command. The error is the following: > boxplot(l,xlab="",ylab="solution value",names=c(levels(bestalgo $idalgo)),main="title_plot",ylim=c(optimal_values[optimal_values $instance==linstance[4],]$optimum,max(bestalgo.temp$best))) Error in if (any(out[nna])) stats[c(1, 5)] <- range(x[!out], na.rm = TRUE) : I removed the ylim to see if something changed, but the error is still there... > boxplot(l,xlab="",ylab="solution value",names=c(levels(bestalgo $idalgo)),main="title_plot") Error in if (any(out[nna])) stats[c(1, 5)] <- range(x[!out], na.rm = TRUE) : $ FC.1.x.10-2opt: int [1:30] 1185996137 1186007112 1186410641 1187064761 1186282173 1186282173 1185996137 1187148446 1188080133 1186282173 ... $ FC.2.6.10-2opt: int [1:30] 1186282173 1185996137 1187179912 1186282173 1186282173 1186369404 1185996137 1185996137 1186369404 1186282173 ... $ FC.2.7.10-2opt: int [1:30] 1186282173 1185996137 1185996137 1187864667 1187717114 1186282173 1185996137 1186369404 1186336586 1185996137 ... $ FC.2.8.10-2opt: int [1:30] 1185996137 1186282173 1185996137 1186282173 1185996137 1185996137 1186282173 1185996137 1187713774 1186007112 ... $ FC.2.9.10-2opt: int [1:30] 1186282173 1187071224 1186369404 1186007112 1187252903 1186282173 1186282173 1185996137 1186007112 1186412178 ... $ FC.3.6.10-2opt: int [1:30] 1187064761 1186007112 1186812662 1186231612 1186369404 1185996137 1186441298 1186886951 1186207793 1185996137 ... $ FC.3.7.10-2opt: int [1:30] 1186462444 1186027320 1186526792 1186007112 1186455716 1186336586 1186123369 1185996137 1186733089 1187033739 ... $ FC.3.8.10-2opt: int [1:30] 1186052259 1187302984 1186202613 1186282173 1186052259 1186648860 1186579169 1187252903 1186819027 1186459107 ... $ FC.3.9.10-2opt: int [1:30] 1186420877 1186475071 1186808113 1187187542 1186007112 1186733089 1186373891 1186007112 1186007112 1186305438 ... $ RW.1.x.10-2opt: int [1:30] 1186369404 1186007112 1185996137 1185996137 1185996137 1185996137 1186282173 1186055449 1187148446 1186007112 ... $ RW.2.6.10-2opt: int [1:30] 1186353513 1185996137 1187252903 1186369404 1185996137 1186282173 1186282173 1186373891 1186282173 1187695581 ... $ RW.2.7.10-2opt: int [1:30] 1185996137 1185996137 1186282173 1186007112 1186336586 1185996137 1186282173 1185996137 1187066018 1186282173 ... $ RW.2.8.10-2opt: int [1:30] 1186336586 1185996137 1186369404 1185996137 1186129090 1186378509 1186266654 1186336586 1185996137 1187189825 ... $ RW.2.9.10-2opt: int [1:30] 1186420877 1185996137 1186007112 1186113036 1186336586 1185996137 1185996137 1186407072 1186052259 1186407072 ... $ RW.3.6.10-2opt: int [1:30] 1186571192 1186415725 1186291434 1185996137 1186007112 1186474741 1187084030 1186202995 1186341458 1186687874 ... $ RW.3.7.10-2opt: int [1:30] 1186318813 1186007112 1186282173 1186282173 1185996137 1186398695 1187252982 1186377917 1186407550 1186570096 ... $ RW.3.8.10-2opt: int [1:30] 1186207793 1186007112 1186282173 1186535035 1186205881 1186007112 1186572299 1187314416 1186373891 1186957225 ... $ RW.3.9.10-2opt: int [1:30] 1186347814 1186548317 1185996137 1186369404 1187009587 1187479550 1186730064 1186282173 1185996137 1186007112 ... $ HC.1.x.10-2opt: int [1:30] 1185996137 1185996137 1186282173 1185996137 1186282173 1186369404 1186282173 1185996137 1186369404 1186336586 ... $ HC.2.6.10-2opt: int [1:30] 1185996137 1187552951 1185996137 1185996137 1185996137 1185996137 1187385192 1186369404 1185996137 1187021722 ... $ HC.2.7.10-2opt: int [1:30] 1186282173 1187183908 1185996137 1186373891 1185996137 1186720189 1185996137 1185996137 1187702896 1186027320 ... $ HC.2.8.10-2opt: int [1:30] 1186027320 1186282173 1186282173 1186369404 1186282173 1186282173 1186373891 1187148446 1185996137 1186336586 ... $ HC.2.9.10-2opt: int [1:30] 1185996137 1186007112 1186369404 1186726691 1186282173 1185996137 1186369404 1186369404 1185996137 1186282173 ... $ HC.3.6.10-2opt: int [1:30] 1186007112 1186701767 1186007112 1186757911 1186639768 1185996137 1186380214 1186007112 1187003657 1186556661 ... $ HC.3.7.10-2opt: int [1:30] 1185996137 1186007112 1186027320 1186373891 1186369404 1186702245 1186373891 1185996137 1186402320 1185996137 ... $ HC.3.8.10-2opt: int [1:30] 1186386501 1186282173 1185996137 1185996137 1186096431 1186007112 1186336586 1186213980 1185996137 1186369404 ... $ HC.3.9.10-2opt: int [1:30] 1187080500 1186052259 1186420877 1186658757 1187268873 1186503010 1186052259 1186417092 1187252982 1186336586 ... $ UR.1.x.10-2opt: int [1:30] 1185996137 1186121052 1185996137 1186282173 1185996137 1186282173 1186282173 1185996137 1186282173 1186078911 ... $ UR.2.6.10-2opt: int [1:30] 1187693812 1186282173 1186282173 1185996137 1185996137 1185996137 1186048686 1185996137 1187686384 1187064761 ... $ UR.2.7.10-2opt: int [1:30] 1186007112 1186407072 1185996137 1186282173 1186291836 1186282173 1185996137 1186282173 1186997336 1186282173 ... $ UR.2.8.10-2opt: int [1:30] 1186378509 1186903795 1186336586 1188401386 1186282173 1186007112 1187385192 1185996137 1186282173 1185996137 ... $ UR.2.9.10-2opt: int [1:30] 1186007112 1185996137 1186336586 1186498687 1185996137 1186336586 1186007112 1186202995 1186144595 1186410641 ... $ UR.3.6.10-2opt: int [1:30] 1186750319 1185996137 1186736815 1186336586 1185996137 1186243800 1186346937 1185996137 1187506525 1187056082 ... $ UR.3.7.10-2opt: int [1:30] 1186410205 1186007112 1186762512 1186638875 1186718248 1186235407 1186052259 1185996137 1186407072 1185996137 ... $ UR.3.8.10-2opt: int [1:30] 1186336586 1186007112 1186613948 1185996137 1186282173 1186452282 1186535035 1186380560 1186061771 1186373891 ... $ UR.3.9.10-2opt: int [1:30] 1186558839 1186007112 1187209137 1186923983 1186953819 1186774611 1186963867 1186642445 1186007112 1186407072 ... $ PIR-2opt : int [1:30] 1186007112 1185996137 1186608743 1185996137 1186585807 1186606396 1188127153 1186407072 1186373891 1186007112 ... $ SEQ-2opt : int [1:30] 1186129090 1186201301 1185996137 1185996137 1187064761 1186369404 1185996137 1186007112 1185996137 1187252903 ... $ SEQ2-2opt : int [1:30] 1185996137 1187142110 1188212339 1186919119 1187252903 1188978682 1187581451 1187127822 1188706301 1188649642 ... l contains data that "looks" ok: each of the 39 algorithms has his own 30 points for the boxplot. I don't understand the error message. Could anybody help me understand what's going on?

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