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# R script that produces histograms from benchmarked values
# Can be called from the bash script with the following code:
# export R_INPUT=$inputfile
# export R_OUTPUT=$outputfile
# export R_TYPE=$hist_type
# R CMD BATCH $this_script.R or Rscript $this_script.R
# Use functions from bench.h to benchmark execution time of the desired block, then Rhist.R script to read all timings
# and produce histograms and finally inject.h to inject values instead of executing block
# This is a small function to help merging empty nbins for dhist histograms
merge_empty_bins <- function (h){
i<-1
j<-1
counts2<--1
breaks2<-h$breaks[1]
if (length(h$counts)>1)
for(i in 1:(length(h$counts)-1)){
if(h$counts[i]!=0 || h$counts[i+1]!=0){
counts2[j]<-h$counts[i]
breaks2[j+1]<-h$breaks[i+1]
j<-j+1
}
}
counts2[j]<-h$counts[length(h$counts)]
breaks2[j+1]<-h$breaks[length(h$breaks)]
h$counts<-counts2
h$breaks<-breaks2
return (h)
}
# Main
source("analysis/hist_script/Rdhist.R")
inputfile<-Sys.getenv("R_INPUT")
outputfile<-Sys.getenv("R_OUTPUT")
type<-Sys.getenv("R_TYPE")
if (!(type %in% c("mean","default","sturges","scott"))){stop("Wrong histogram type")}
df<-read.table(inputfile,header=F)
df<-df[,c(1,4)]
names(df)<-c("NAME","TIME")
attach(df)
for(i in unique(NAME)){
vector1<-df[NAME==i,2]
if (length(vector1)==1){
#If there is only one element
h<-hist(vector1) # Just for R compatibility reasons
h$breaks<-c(vector1,vector1)
h$counts<-1
} else {
if (type=="mean"){
#Mean value only
h<-hist(vector1) # Just for R compatibility reasons
h$breaks<-c(mean(vector1),mean(vector1))
h$counts<-length(vector1)
} else
if (type=="default")
#Standard HISTOGRAM:
h<-hist(vector1)
else {
#Dhist:
h<-dhist(vector1,nbins=type, plot = FALSE, lab.spikes = FALSE, a=5*iqr(vector1), eps=0.15)
h$breaks<-h$xbr
h$count<-as.vector(h$counts)
h$counts<-h$count
h<-merge_empty_bins(h)
}
}
cat(i, file = outputfile, sep = "\t", append = TRUE)
cat("\t", file = outputfile, append = TRUE)
cat(sum(h$counts), file =outputfile, sep = "\t", append = TRUE)
cat("\t", file = outputfile, append = TRUE)
cat(sprintf("%.8f", mean(vector1)), file =outputfile, sep = "\t", append = TRUE)
cat("\t", file = outputfile, append = TRUE)
cat(length(h$breaks), file = outputfile, append = TRUE)
cat("\t", file = outputfile, append = TRUE)
cat(sprintf("%.8f", h$breaks), file = outputfile, sep = "\t", append = TRUE)
cat("\t", file = outputfile, append = TRUE)
h$density = h$counts/sum(h$counts)
cat(sprintf("%.8f", h$density), file = outputfile, sep = "\t", append = TRUE)
cat("\n", file = outputfile, append = TRUE)
}
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