On 12.12.2012 00:05, Marian Talbert wrote:> I'm trying to use Rprof() to identify bottlenecks and speed up a
particullary
> slow section of code which reads in a portion of a tif file and compares
> each of the values to values of predictors used for model fitting.
I've
> written up an example that anyone can run. Generally temp would be a
> section of a tif read into a data.frame and used later for other
processing.
> The first portion which just records the time works in about 6 seconds the
> second part causes RGui to immediately close with no error or warning. Any
> advice on how to get Rprof to work or how to speed up this code would be
> greatly appreciated. I'm using Windows 7 (which might be my problem)
and R
> version 2.15.0.
The problem is rather the R version: I cannot reproduce errors with a
recent R.
Uwe Ligges
>
> CalcMESS<-function(tiff.entry,pred.vect){
> f<-sum(pred.vect<tiff.entry)/length(pred.vect)*100
> if(is.na(f)) return(NA)
> if(f==0)
> return((tiff.entry-min(pred.vect))/(max(pred.vect)-min(pred.vect))*100)
> if(0<f & f<=50) return(2*f)
> if(50<=f & f<100) return(2*(100-f))
> if(f==100)
> return((max(pred.vect)-tiff.entry)/(max(pred.vect)-min(pred.vect))*100)
> else return(NA)
> }
>
> train.dat <-
data.frame(a=runif(200),b=runif(200),c=runif(200),d=runif(200))
> temp <-
> data.frame(a=runif(130000),b=runif(130000),c=runif(130000),d=runif(130000))
> pred.rng<-temp
> vnames.final.mod <- names(train.dat)
> nvars.final <- length(vnames.final.mod)
>
> start.time<-Sys.time()
> for(k in 1:nvars.final){
>
> pred.range<-train.dat[,match(vnames.final.mod[k],names(train.dat))]
>
>
pred.rng[,k]<-mapply(CalcMESS,tiff.entry=temp[,match(vnames.final.mod[k],names(temp))],MoreArgs=list(pred.vect=pred.range))
> }
> Sys.time()-start.time
>
>
> Rprof("C:\\temp\\mapply.out")
> for(k in 1:nvars.final){
>
> pred.range<-train.dat[,match(vnames.final.mod[k],names(train.dat))]
>
>
pred.rng[,k]<-mapply(CalcMESS,tiff.entry=temp[,match(vnames.final.mod[k],names(temp))],MoreArgs=list(pred.vect=pred.range))
> }
> Rprof(NULL)
>
>
>
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