Add script for execution of R analysis without benchmark

tools/getConfidenceIntervalTable/getConfidenceIntervalTable.sh

+#!/bin/bash
+
+## Generate Results file
+function run-r() {
+R --vanilla --silent << EOF
+results_fn="${RAWFN}"
+outtxt_fn="${RESULTS_DIR}/results-text.txt"
+outcsv_fn="${RESULTS_DIR}/results-text.csv"
+configs.loop=${NUM_OF_LOOPS}
+configs.recursion=${RECURSION_DEPTH}
+configs.labels=c($LABELS)
+results.count=${TOTAL_NUM_OF_CALLS}
+results.skip=${TOTAL_NUM_OF_CALLS}/2
+source("${RSCRIPT_PATH}")
+EOF
+}
+
+function createVariantsString {
+	local LABELS=""
+	local variants=$(ls $RESULTS_DIR | grep ".csv" | awk -F'[.-]' '{print $4}' | sort | uniq | sed '/^[[:space:]]*$/d')
+	for variant in $variants
+	do
+		if [ -z "$LABELS" ]
+		then
+			LABELS="\"$variant\""
+		else
+			LABELS="$LABELS, \"$variant\""
+		fi
+	done
+	echo $LABELS
+}
+
+function createLatexTable {
+	cat $RESULTS_DIR/results-text.txt | tail -n 8 > transposeMe.csv
+	awk '
+	{ 
+	    for (i=1; i<=NF; i++)  {
+		a[NR,i] = $i
+	    }
+	}
+	NF>p { p = NF }
+	END {    
+	    for(j=1; j<=p; j++) {
+		str=a[1,j]
+		for(i=2; i<=NR; i++){
+		    str=str" "a[i,j];
+		}
+		print str
+	    }
+	}' transposeMe.csv > transposed.csv
+
+	cat transposed.csv | awk '{print "["$1-$3";"$1+$3"] & "$2}'
+}
+
+if [ "$#" -lt 1 ]
+then
+    echo "Please pass folder with MooBench CSV files for analysis!"
+    exit 1
+fi
+
+
+RESULTS_DIR=$1
+
+RAWFN=$RESULTS_DIR/raw
+NUM_OF_LOOPS=10
+RECURSION_DEPTH=10
+TOTAL_NUM_OF_CALLS=2000000
+LABELS=$(createVariantsString)
+
+
+RSCRIPT_PATH=$MOOBENCH_HOME/frameworks/Kieker/scripts/stats.csv.r
+
+run-r
+
+createLatexTable

tools/getConfidenceIntervalTable/stats.csv.r

+############################################
+# R - script to collect all moobench results
+############################################
+
+# these values are here only as documentation. The parameters are set by benchmark.sh
+#rm(list=ls(all=TRUE))
+#data_fn="data/"
+#folder_fn="results-benchmark-binary"
+#results_fn=paste(data_fn,folder_fn,"/raw",sep="")
+#outtxt_fn=paste(data_fn,folder_fn,"/results-text.txt",sep="")
+#results_fn="raw"
+#outtxt_fn="results-text.txt"
+
+#########
+# These are configuration parameters which are automatically prepended to this file by the benchmark.sh script.
+# Therefore, they must not be set here. The following lines only serve as documentation.
+#configs.loop=10
+#configs.recursion=c(10)
+#configs.labels=c("No Probe","Inactive Probe","Collecting Data","Writing Data (ASCII)", "Writing Data (Bin)")
+#results.count=2000000
+#results.skip=1000000
+
+#bars.minval=500
+#bars.maxval=600
+
+
+##########
+# Process configuration
+
+# divisor 1 = nano, 1000 = micro, 1000000 = milli seconds
+timeUnit <- 1000 
+
+# number of Kieker writer configurations 
+numberOfWriters <- length(configs.labels)
+recursion_depth <- configs.recursion
+
+numberOfValues <- configs.loop*(results.count-results.skip)
+numbers <- c(1:(numberOfValues))
+resultDimensionNames <- list(configs.labels, numbers)
+
+# result values
+resultsBIG <- array(dim=c(numberOfWriters, numberOfValues), dimnames=resultDimensionNames)
+
+##########
+# Create result
+
+## "[ recursion , config , loop ]"
+
+numOfRowsToRead <- results.count-results.skip
+
+for (writer_idx in (1:numberOfWriters)) {
+   recordsPerSecond = c()
+   rpsLastDuration = 0
+   rpsCount = 0
+   file_idx <- writer_idx - 1
+
+   # loop
+   for (loop_counter in (1:configs.loop)) {
+      results_fn_filepath <- paste(results_fn, "-", loop_counter, "-", recursion_depth, "-", file_idx, ".csv", sep="")
+      message(results_fn_filepath)
+      results <- read.csv2(results_fn_filepath, nrows=numOfRowsToRead, skip=results.skip, quote="", colClasses=c("NULL","numeric", "numeric", "numeric"), comment.char="", col.names=c("thread_id", "duration_nsec", "gc", "t"), header=FALSE)
+      trx_idx <- c(1:numOfRowsToRead)
+      resultsBIG[writer_idx,trx_idx] <- results[["duration_nsec"]]
+   }
+}
+
+qnorm_value <- qnorm(0.975)
+
+# print results
+printDimensionNames <- list(c("mean","sd","ci95%","md25%","md50%","md75%","max","min"), c(1:numberOfWriters))
+# row number == number of computed result values, e.g., mean, min, max
+printvalues <- matrix(nrow=8, ncol=numberOfWriters, dimnames=printDimensionNames)
+
+for (writer_idx in (1:numberOfWriters)) {
+   idx_mult <- c(1:numOfRowsToRead)
+
+   valuesBIG <- resultsBIG[writer_idx,idx_mult]/timeUnit
+
+   printvalues["mean",writer_idx] <- mean(valuesBIG)
+   printvalues["sd",writer_idx] <- sd(valuesBIG)
+   printvalues["ci95%",writer_idx] <- qnorm_value*sd(valuesBIG)/sqrt(length(valuesBIG))
+   printvalues[c("md25%","md50%","md75%"),writer_idx] <- quantile(valuesBIG, probs=c(0.25, 0.5, 0.75))
+   printvalues["max",writer_idx] <- max(valuesBIG)
+   printvalues["min",writer_idx] <- min(valuesBIG)
+}
+resultstext <- formatC(printvalues,format="f",digits=4,width=8)
+
+print(resultstext)
+
+write(paste("Recursion Depth: ", recursion_depth),file=outtxt_fn,append=TRUE)
+write("response time",file=outtxt_fn,append=TRUE)
+write.table(resultstext,file=outtxt_fn,append=TRUE,quote=FALSE,sep="\t",col.names=FALSE)
+
+concResult <- ""
+headResult <- ""
+# write the first n-1 elements preceded by a comma (,)
+for (writer_idx in (1:(numberOfWriters-1))) {
+   headResult <- paste(headResult, configs.labels[writer_idx], ",")
+   concResult <- paste(concResult, printvalues["mean",writer_idx], ",")
+}
+# write the last without a comma
+headResult <- paste(headResult, configs.labels[numberOfWriters])
+concResult <- paste(concResult, printvalues["mean", numberOfWriters])
+  
+write(headResult,file=outcsv_fn,append=TRUE)
+write(concResult,file=outcsv_fn,append=TRUE)
+
+# end