#! /bin/bash

# ./effort $Filename $Path $Learner $TestFile $TrainFile $TargetEMs $LogFile

# Arguments
Filename=$1
Path=$2
Learner=$3
TestFile=$4
TrainFile=$5
TargetEMs=$6
LogFile=$7

gawk -f basiclc.awk Pass=1 TargetEMs=$TargetEMs $TrainFile Pass=2 TargetEMs=$TargetEMs $TestFile > $LogFile
#gawk -f simplelc.awk Pass=1 TargetEMs=$TargetEMs $TrainFile Pass=2 TargetEMs=$TargetEMs $TestFile > $LogFile
#./lc81 $TrainFile $TestFile $TargetEMs "F"> $LogFile

#Stats=$(./calc $LogFile)

#TrainingCount=$(gawk 'END{print NR;}' $TrainFile)

if [ $Learner == "attrLC" ] ; then
	Stats=$(./calc $LogFile)
	#Calculate Standard Deviation of Attribute
	AttrDev=$(gawk -f columnstdev.awk Columns=$TargetEMs $Filename)

	#Calculate Entropy of Attribute (using discrete formula because the effort multipliers are discrete)
	AttrEntropy=$(gawk -f columnentropy.awk Columns=$TargetEMs $Filename)

	AvgCorr=$(echo $Stats | gawk 'BEGIN{FS=","} NR==1{print $4}')

	echo $TargetEMs","$AvgCorr","$AttrDev","$AttrEntropy
fi
if [ $Learner == "simpleLC" ] ; then
	Stats=$(./calc $LogFile)
	echo $Stats","$TargetEMs
fi
if [ $Learner == "BasicLC" ] ; then
	echo -n $TargetEMs","
    gawk 'BEGIN{FS=",";OFS=",";} NR=1{re=($1-$2)/$2;mre=re<0?-1*re:re;print $1,$2,100*mre}' $LogFile
fi