# warning: requires at least 5MB of free disk
##########################################################################
# /* vim: set filetype=sh : */
#    ourmine : a simple learning environment for data mining
#    Copyright (C) 2007, Tim Menzies, tim@menzies.us, http://menzies.us
#
#    This program is free software: you can redistribute it and/or modify
#    it under the terms of the GNU General Public License as published by
#    the Free Software Foundation, version 3.
#
#    This program is distributed in the hope that it will be useful,
#    but WITHOUT ANY WARRANTY; without even the implied warranty of
#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
#    GNU General Public License for more details.
#
#    You should have received a copy of the GNU General Public License
#    along with this program.  If not, see <http://www.gnu.org/licenses/>.
##########################################################################

# for more info on command-line weka stuff, see

# http://www.cs.waikato.ac.nz/~remco/weka_bn/node13.html

Here=`pwd`

#### generic stuff
reload() { 
	cd $Here
   	. $Ourrc  
}
show() {
	local goal1="^$1"
	local com="/^$1 /,/^}/{print}"
	if   (set | grep $goal1 | grep "=" > /tmp/debug)
   	then set  | grep $goal1
   	else set  | gawk "$com"
   	fi
}
blab()   { printf "$*"   >&2; }
blabln() { printf "$*\n" >&2; }
#### initialization stuff
setup() {
	setUpVars
	setUpDirs
}
lcsee() {
	alias ls="ls --color"
}
build() {
	export AWKPATH="$Here/minerc.lib:$AWKPATH"
}
setUpVars() {
	alias ls="ls -G"
	PROMPT_COMMAND='echo -ne "\033]0;${HOSTNAME}: `pwd`\007"'
	PS1="Our MINE! \W#\!> "
	Ourmine="$HOME/opt/ourmine"
	PATH="$Ourmine/bin:$HOME/bin:$PATH"
	Safe=$Ourmine/var/safe
	Dirs="$Our/lib/arffs"
	LibUrl="http://unbox.org/wisp/trunk/our/minerc.lib/lib.zip"
	export AWKPATH="$Ourmine/lib:$AWKPATH"
	Bins=10
	Repeats=2;
	Learners="nb nbk"
	Data="$Ourmine/lib/arff/uci/discrete/a*.arff
	      $Ourmine/lib/arff/uci/discrete/s*.arff"
	Audit="pgawk --profile=$HOME/tmp/awkprof.out --dump-variables=$HOME/tmp/awkvars.out --lint"
}
setUpDirs() {
	mkdir -p $HOME/tmp 
	mkdir -p /tmp/$USER
	Tmp=`mktemp -d -p /tmp/$USER`
	Weka="nice -19 java -Xmx1024M -cp $Tmp/weka.jar "
	mkdir -p $Tmp
	mkdir -p $Ourmine/lib # for support code
	mkdir -p $Ourmine/bin # for our executables
	mkdir -p $HOME/bin  # for your executables
	mkdir -p $Safe      # for stuff you want to keep around
	if [ ! -f "$Ourmine/lib/lib.zip" ]; then
		downloads
	fi
	# I had too much trouble with pathname syntax problems
	# on mac, windows, linux, etc. So now I just copy weka.jar
	# to the working directory (no need for pathnames)
	cp $Ourmine/lib/weka.jar $Tmp
}
downloads() {
	set -x	
	(cd $Ourmine/lib
	wget -O lib.zip $LibUrl
	unzip -o  lib.zip
	)
	set +x
}
#### stuff for the turkey experiment
setUpSeds() {
cat<<-EOF > $Tmp/etc/seds
	s/loccodeandcomment/loc_code_and_comment/
	s/locodeandcomment/loc_code_and_comment/
	s/locandcomment/loc_code_and_comment/
	s/essential_complexity/ev(g)/
	s/cyclomatic_complexity/v(g)/
	s/halstead_length/n/
	s/halstead_level/l/
	s/num_operators/n1/
	s/num_operands/n2/
	s/unique_operands/uniq_opnd/
	s/unique_operators/uniq_op/
	s/halstead_content/i/
	s/halstead_error_est/b/
	s/halstead_prog_time/t/
	s/halstead_effort/e/
	s/halstead_difficulty/d/
	s/halstead_volume/v/
	s/loc_comments/loc_comment/
	s/design_complexity/iv(g)/
	s/locomment/loc_comment/
	s/loc_total/loc/
	s/locode/loc/
	s/[\t ]c[\t ]/ defects /
	s/[\t ]problems[\t ]/ defects /
	s/branchcout/branch_count/
	s/total_op[\t ]/n1 /
	s/total_opnd/n2/
	s/{no,yes}/{false,true}/
EOF
}

prep() {
	for i in $Dirs/mdp/*.arff ; do
	cat $i | 
	tr A-Z a-z |
	sed -f $Tmp/etc/seds \
  	> $Tmp/arff/`basename $i`
done
}
classes() { 
	local brief=0
	while [ `echo $1 | grep "-"` ]; do
		case $1 in
			-b|--brief) brief=1;;
			*)   blabln "'"$1"' unknown\n usage cat file | classes [options]"
			     return 1;;
    	esac
		shift 1
	done
	gawk '
   BEGIN      { OFS=FS=","
                IGNORECASE=1 
		        Brief=0	}
              { gsub(/#.*/,"") } 
   /^[ \t]*$/ { next          } 
   Data  && NF > 1     { Freq[$NF]++ }
   /@data/    { Data=1 } 
   END        {
  				 for(N in Freq) 
					 if (Brief) { print N } else { print Freq[N],N }}
   ' Brief=$brief - 
}
intersectAttributes() {
	# list the intersection of attributes 
	# found in a set of arff files
		gawk '
	BEGIN        { IGNORECASE=1; OFS=","}
	FNR==1       { Files++ }
	/@attribute/ { Got[$2]++ }
	END          { for(A in Got)
                       if (Got[A]>=Files)
                           print  A
	}' $1
}
shared() {
	for i in `intesectAttributes $Tmp/arff/*.arff | 
		      sort | 
			  grep -v defects`; do 
		echo $i
	done
	echo defects
}
some() {
	# generate an arff file that only contains certaina attributes
	gawk -f some.awk -v Some="$1" $2 
}
makeshare() {
	Shared=`shared`
	for i in $Tmp/arff/*.arff; do
		echo $i
		some "$Shared" $i > $Tmp/shared/`basename $i`
	done
}
report() {
	gawk  'BEGIN {RS=""; FS="\n"} 
           NR==1 { M=split(Show,Shows,",") }
		         {  R[++N]=indent($0)
                 } 
           END   {print " "; 
		          for(r=1;r<=M;r++) printf("\n%s",R[Shows[r]]);
	              print ""; }
	
		   function str(n,chr, out) {
		   	    chr = chr ? chr : " ";
		   		while(n-- > 0) out= out chr;
				return out
	   		}
           function indent(str, i, out) {
           		for(i=1;i<=NF;i++)
           			out=out str(Indent," ")  $i "\n"
           		return out
           }
           ' Show=$2 Indent=$1 -
} 

#### end inter intra stuff 

#### misc utils

makeTrainTest() {
	cat - | someArff --seed $1 --bins $2 --bin $3
}
gotwant()    {  gawk '
	BEGIN   {Unlog  = 0; 
			 OFS    = ","       
 			 Ee     = 848456353 / 312129649;
            }
    NF == 3 { if (UnLog) { print Ee^$2 , Ee^$3   
			  } else     { print $2,$3 }
           }
    NF == 4    { print $2 , $4 }
' -
}
abcd() {
	local goal="true|yes"
	local before=""
	local prefix=""
	local decimals=2
    while [ `echo $1 | grep "-"` ]; do
       case $1 in
		   	-d|--decimals) decimals=$2;;
		   	-b|--before) before=$2;;
		   	-p|--prefix) prefix=$2;;
		   	-g|--goal)   goal=$2;;
			*)           blabln "'"$1"' unknown\n usage abcd [options]"; 
				         return 1;;
       esac
       shift 2
    done
	[  -n "$before" ] && printf $before
	gawk '
	BEGIN { 
	     Decimals    = 3
	     Got         = 1
	     Want        = 2;
		 Prefix      = "";
	     True        = "true";  ## define symbol 1
         A=B=C=D=0 ; 
	     FS=OFS=","
		 GoalPd = 1;
		 GoalPf = 0;
       }
	function yes(s) {return s ~ True   }
	function no(s)  {return ( yes(s) ? 0 : 1 ) }
	           { sub(/#.*/,"") }
	/^[ \t]*$/ { next }
	NF==2      { N++;
	             Predicted=$Got;
	             Actual=$Want;
				 if (Predicted == Actual) Good++;
	             if (no( Actual) && no( Predicted)) A++;
	             if (yes(Actual) && no( Predicted)) B++;
	             if (no( Actual) && yes(Predicted)) C++;
	             if (yes(Actual) && yes(Predicted)) D++;
				#print N,$0,A,B,C,D
	           }
	END  { 
		OFMT        = "%." Decimals "f";
		Balance=Precision=Accuracy=Pf=NotPf=Pd=0;
		if (C+D > 0 )      Precision = D/(C+D);
		if ((A+B+C+D) > 0)  Accuracy  = (A+D)/(A+B+C+D);
		if (A+C > 0 )      Pf       = C/(A+C)
		if (B+D > 0 )      Pd        = D/(B+D);
		if (B+C+D > 0)     { # special case- everything misses
			 Balance = 1 - sqrt((GoalPd - Pd)^2 + (GoalPf - Pf)^2)/sqrt(2)
        }
		if(Prefix) printf Txt=Prefix OFS;
		print A,B,C,D,
		      sprintf(OFMT,100*Accuracy),
			  sprintf(OFMT,100*Pd),
			  sprintf(OFMT,100*Pf),
			  sprintf(OFMT,100*Precision),
			  sprintf(OFMT,100*Balance);
	}' Prefix="$prefix" Decimals="$decimals" True="$goal" -
}
quartile2tex() {
	cat - |  gawk 'BEGIN { FS=","
                           OFS="&"}
				   /===/  {print $1; last=0 ; rank=1; next}
                   NF==0 { print ""; next}
					/#/  {next}
	                Last!=NF { 
                            print (NF==7 ? "\\scriptsize\\begin{tabular}{rrrr} rank & treatment & median & distribution\\\\" : "stats") ; Last=NF}

                   NF==5 { print statsprint() }
                   NF==7 { print qprint() }
                  function statsprint(  sep,i,out) {
					if ($4 != last) {
						rank++	
				    } 
                    last=$4
					out = rank " & "
					for(i=1;i<=NF;i++) {
                       out = out sep $i
                       sep="&"
                    }
                    return out "\\\\"
                  } 
                  function qprint( sep,i,out) {
	                 out = "1 & " $1 "&" $4  "&"
                     out=out "\\boxplot{"$2"}{"$3"}{"$4"}{"$5 - $3"}{"$6"}"
                     return out "\\\\"
                  }
                  function trim(s) {
                       gsub(/[ \t]/,"",s);
					   return s
                   } '
 
#	gawk 'BEGIN {FS="\n"; RS=""}
#	         { M=split($0,Lines,/\\t/) 
#				Z=0;
#               for(I=1;I<=M;I++) {
#					N=split(Lines[I],Words,/\\t/)
#					print ++Z " " trim(Lines[I])
#					#for(J=1;J<=N; J++)
#					#		print Z " :: " J " :: " trim(Words[J])
#               }
#			 }
#            function trim(s) {
#	             sub(/^[ \t\n]*/,"",s);
#				 sub(/[ \t]\n*$/,"",s);
#                 return s
#            }'
}
malign() {
	cat - | gawk '
	BEGIN { Width=1;
	        Gutter=1;
			OFS=FS=",";
	}		 
	{ N++;  
	  for(I=1;I<=NF;I++) {
			if( (L=length($I)) > Max[I]) Max[I]=L;
			++Data[N,0];
			Data[N,I]=$I; }
	}
	END {for(J=1;J<=N;J++) {
			Str=Sep1="";
			if (Data[J,0]>1) {  
				for(I=1;I<=NF;I++) {
					L=length(Data[J,I]);
					Str = Str Sep1 \
					      str(most(Width,Max[I]+Gutter+1)-L," ") \
						  Data[J,I];
					Sep1= OFS;
				}} 
			else {Str=Data[J,1]}
		  print Str;}
	}
	function str(n,c,  out) { while(--n > 0) out = out c; return out; }	
    function most(x,y)      { return x > y ? x : y; }  
	' 
}
medians()    { 
	local start="2"
    while [ `echo $1 | grep "-"` ]; do
       case $1 in
		   	-s|--start) start=$2;;
			*)           blabln "'"$1"' unknown\n usage medians [options]"; 
				         return 1;;
       esac
       shift 2
    done
	gawk '
	BEGIN{FS=","}
	     {print}
	/^[ \t]*$/ {next}	 
	/#/  {next}
	     {for(I=Start;I<=NF;I++) {
			(Data[I,0]++); Data[I,Data[I,0]]=$I }
		 }
	END{ print ""
		 printf("##");
		 printf $1
		 for(I=2;I<Start;I++) 
			 printf ","$I
		 for(I=Start;I<=NF;I++) {
			    Max=Data[I,0];
			    delete Val
			    N=0;
			    for(J=1;J<=Max;J++) 
				     Val[J]  = Data[I,J]
				asort(Val);
				if(Max % 2 ) { printf(",%s",Val[int(Max/2)]) }
			    else        { below=Val[int(Max/2)];
					          above=Val[int(Max/2) + 1];
					          printf(",%s",(below+above)/2)
						    }
			}
		   print ""
		}' Start=$start -
}
quartile() {
	gawk '
BEGIN { FS = OFS = ","; # #
        Shrink = 2; #
        Left   = -100; 
        Right  = 100; #
        Off    = " "; #
        Max = "]"; #
        Min = "["; #
        Median = "|"; #
		Low ="-";
		High = "+";
        F      = "5.1f" #
		#Header = "min,q1,median,q3,max,"
}
	{  S[++N]=$1 }
END {asort(S); if(Header) print Header;report(S,N)}
function round(x)      { return int(x<0 ? x-0.5 : x+0.5) }
function report(s,n,     min,q1,median,q3,max,kludge) {
  min   = s[1];
  q1    = s[int(n/4)];
  median= s[int(2*n/4)];
  q3    = s[int(3*n/4)];
  max   = s[n];
  printf("%"F",%"F",%"F",%"F",%"F",%s\n",
         min,q1,median,q3,max,
         quart(min,q1,median,q3,max,Right,Shrink)) | "sort -t, -r -n -k 2,2"
}
function quart(min,q1,median,q3,max,width, scale,  i,l,str) {
	width  /= scale
	min    /= scale 
	q1     /= scale 
	median /= scale
	q3     /= scale 
	max    /= scale
	for(i=  1; i<=width; i++) l[int(i)]= Off;
	for(i=min;    i<=q1; i++) l[int(i)]= Low;
	for(i= q3;   i<=max; i++) l[int(i)]= High;
	l[int(median)] = Median
	for(i= 1; i<=width; i++) str = str l[int(i)];
	return Min str Max
}

' -
}
gains() {
		gawk -f gains.awk Debug=0 -
}
logNumbers() { 
		gawk '
	BEGIN 						                {Min=0.00001; OFS=","; 
	                                             IGNORECASE=1}
	/@attribute/ 				                {Attr++}
	/@attribute/ && $3 ~ /numeric|real|integer/ {Num[Attr]=Attr; }

	/@data/      {In=1; FS=","}
	/@/          {print; next; }
	In && NF > 2 {
	for(I=1;I<=Attr;I++) 
		if (I in Num) 
			if ($I !~ /\?/)  {
				if ( ($I +0) < Min) {Bad=1} else {Bad=0}
				if (Bad) $I= Min;
				$I=log($I)	
		}
	print $0
	}
	' -
}
winLossTie() {
	local fields=10
	local key=1
    local performance=$fields
    local high=1
    local confidence=95
	local input="-"	
	while [ `echo $1 | grep "-"` ]; do
		case $1 in
			-f|--fields)  fields=$2;      shift 2;;
			--99)         confidence=99;  shift 1;;
			--95)         confidence=95;  shift 1;;
			-k|--key)     key=$2;         shift 2;;
			-p|--perform) performance=$2; shift 2;;
			--high)       high=1;         shift 1;;
			--low)        high=0;         shift 1;;
			-i|--input)   input=$2;       shift 2;;
			*)   blabln "'"$1"' unknown\n. usage: winLossTie [options]"
			     return 1;;
    	esac
	done
	(echo "#key,ties,win,loss,win-loss @ ${confidence}%"
	gawk -f mwu.awk Fields=$fields Key=$key Performance=$performance \
	                High=$high Confidence=$confidence $input |
	sort -t, -r -n -k 5,5
	) | malign

}
someArff() { 
	local bins=3
	local bin=1
	local seed=$RANDOM
	while [ `echo $1 | grep "-"` ]; do
		case $1 in
			-B|--bins) bins=$2;;
			-b|--bin) bin=$2;;
			-s|--seed) seed=$2;;
			-h|--help) cat <<-EOF
			someArff : divide an arrf file into Bins, create train/test files 	
			usage: someArff [flags] arffFile

			Flags
		  	-B, --bins NUM   Randomly divide the data into NUM bins
		  	-b, --bin  NUM   Store bin NUM into test.arff and rest into train.arff
		  	-s, --seed NUM   Set the random number seed to NUM
		  	-h, --help       Print this text
			EOF
			return 1;;
			*)   blabln "'"$1"' unknown\n usage cat file | someArff [options]"
			     return 1;;
    	esac
		shift 2
	done
	gawk '
	BEGIN  { 
	  IGNORECASE=1;
      Trainf="train.arff"; Testf="test.arff"; 
      Bins=3; 
      Bin=1; 
      Seed=1;
   } 
              { sub(/#.*/,"") }
              { sub(/\%.*/,"") }
   /^[ \t]*$/          { next }
   /@relation/         { Seed ? srand(Seed) : srand(1)      }
   /@relation/         { printf "">Trainf;  printf "">Testf }
   /@relation/,/@data/ { print $0 >> Trainf;  print $0 >> Testf; next }
                       { Line[rand()] = $0; Lines++ }
  END { 
    Start = Lines/Bins * (Bin - 1) ;
    Stop  = Lines/Bins * Bin;
    for(I in Line) {
       N++;
       What = (N>= Start && N < Stop) ? Testf : Trainf
       print Line[I]>>What; }
   }
   ' Seed=$seed Bins=$bins Bin=$bin -
}

#### Weka stuff
## pruning columns
removeAttributes() {
	blab "/"
	$Weka weka.filters.unsupervised.attribute.Remove \
		-R "${1}-${2}" -i $3 -o tmp.arff
		set +x
	cat tmp.arff					  
}
## discretization
discretizeViaFayyadIrani() {
	blab "x"
    $Weka weka.filters.supervised.attribute.Discretize \
		-c last -R first-last  -i $1 -o tmp.arff
     cat tmp.arff
}
## feature subset selection
rankViaInfoGain() {
	blab "<"
	$Weka  weka.filters.supervised.attribute.AttributeSelection \
     	-S  "weka.attributeSelection.Ranker -T -2.7976931348623157E308 -N -1"  \
     	-E  "weka.attributeSelection.InfoGainAttributeEval"                    \
     	-i  $1 -o tmp.arff
	cat tmp.arff
}
### learners
## classifiers
# rule-based classifiers
oner() {
  blab "1"
  $Weka weka.classifiers.rules.OneR \
  	-B 6 \
	-p 0 -t $1 -T $2
}
jrip() {
   blab "j"
   $Weka weka.classifiers.rules.JRip \
   		-F 3 -N 2.0 -O 2 -S 1 \
	    -p 0 -t $1 -T $2
}
jrip10() {
   blab "j"
   $Weka weka.classifiers.rules.JRip \
   		-F 3 -N 2.0 -O 2 -S 1 \
	    -t $1 
}
# bayesian classifiers
aode() {
	blab "a"
    $Weka weka.classifiers.bayes.AODE \
		"-F" 0 \
	  	-p 0 -t  $1 -T $2  
}
aode10() {
	blab "a"
    $Weka weka.classifiers.bayes.AODE \
		"-F" 0  \
		-t  $1 -T $2   
}
nbd() {
	blab "N"
	gawk -f nbd.awk Brief=1 Pass=1 $1 Pass=2 $2  	|
	gawk 'BEGIN {FS=","} {print "-",$1,"-",$2}'  
}
nba() {
	blab "A"
	gawk -f nba.awk Debug=1 Pass=1 $1 Pass=2 $1 Pass=3 $2  	
}
nb() {
	blab "n"
	$Weka weka.classifiers.bayes.NaiveBayes \
		-p 0 -t  $1 -T $2  
}
nb10() {
	blab "n"
	$Weka weka.classifiers.bayes.NaiveBayes \
		-i -t  $1   
}
nbk() {
	blab "k"
	$Weka weka.classifiers.bayes.NaiveBayes \
		-K \
		-p 0 -t  $1 -T $2  
}
# decision tree learners
j48() {
  	blab "c"
	$Weka weka.classifiers.trees.J48 \
		-C 0.25 -M 2 \
		-p 0 -t $1 -T $2
}
j4810() {
  	blab "c"
	$Weka weka.classifiers.trees.J48 \
		-C 0.25 -M 2 \
		-i -t $1 
}
j4810c() {
  	blab "c$2"
	$Weka weka.classifiers.trees.J48 \
		-C $2 -M 2 \
		-i -t $1 
}
## linear-model learners
lsr() {
	blab "L"
	$Weka weka.classifiers.functions.LinearRegression \
	     -S 0 -R 1.0E-8  \
	     -p 0 -t $1 -T $2
}
m5p() {
	blab "P"
	$Weka weka.classifiers.trees.M5P \
	     -p 0 -t $1 -T $2
}
## nearest neighbor
1Bkx() {
	blab "N"
	$Weka weka.classifiers.lazy.IBk \
     	-K 1 -W 0 -X -E \
	    -p 0 -t $1 -T $2
}
1Bk() {
   	blab "n"
	$Weka weka.classifiers.lazy.IBk \
		-K -1 -W 0 -E \
	    -p 0 -t $1 -T $2
}		
## association rule learners
apriori() {
	blab "A"
	$Weke weka.associations.Apriori \
		-N 10 -T 0 -C 0.9 -D 0.05 -U 1.0 -M 0.1 -S -1.0 \
	    -p 0 -t $1 -T $2
}
#### teaching demos
weather.nominal() {
	cat<<-EOF
	@relation weather.nominal
	
	@attribute outlook {sunny, overcast, rainy}
	@attribute temperature {hot, mild, cool}
	@attribute humidity {high, normal}
	@attribute windy {TRUE, FALSE}
	@attribute play {yes, no}
	
	@data
	sunny,hot,high,FALSE,no
	sunny,hot,high,TRUE,no
	overcast,hot,high,FALSE,yes
	rainy,mild,high,FALSE,yes
	rainy,cool,normal,FALSE,yes
	rainy,cool,normal,TRUE,no
	overcast,cool,normal,TRUE,yes
	sunny,mild,high,FALSE,no
	sunny,cool,normal,FALSE,yes
	rainy,mild,normal,FALSE,yes
	sunny,mild,normal,TRUE,yes
	overcast,mild,high,TRUE,yes
	overcast,hot,normal,FALSE,yes
	rainy,mild,high,TRUE,no
EOF
}
auto93() { cat<<-EOF
	@relation 'auto93.names'
	@attribute Manufacturer { Acura, Audi, BMW, Buick, Cadillac, Chevrolet, Chrysler, Dodge, Eagle, Ford, Geo, Honda, Hyundai, Infiniti, Lexus, Lincoln, Mazda, Mercedes-Benz, Mercury, Mitsubishi, Nissan, Oldsmobile, Plymouth, Pontiac, Saab, Saturn, Subaru, Suzuki, Toyota, Volkswagen, Volvo}
	@attribute Type { Small, Midsize, Compact, Large, Sporty, Van}
	@attribute City_MPG real
	@attribute Highway_MPG real
	@attribute Air_Bags_standard { 0, 2, 1}
	@attribute Drive_train_type { 1, 0, 2}
	@attribute Number_of_cylinders real
	@attribute Engine_size real
	@attribute Horsepower real
	@attribute RPM real
	@attribute Engine_revolutions_per_mile real
	@attribute Manual_transmission_available { 1, 0}
	@attribute Fuel_tank_capacity real
	@attribute Passenger_capacity real
	@attribute Length real
	@attribute Wheelbase real
	@attribute Width real
	@attribute U-turn_space real
	@attribute Rear_seat_room real
	@attribute Luggage_capacity real
	@attribute Weight real
	@attribute Domestic { 0, 1}
	@attribute class real
	@data
	Acura,Small,25,31,0,1,4,1.8,140,6300,2890,1,13.2,5,177,102,68,37,26.5,11,2705,0,15.9
	Acura,Midsize,18,25,2,1,6,3.2,200,5500,2335,1,18,5,195,115,71,38,30,15,3560,0,33.9
	Audi,Compact,20,26,1,1,6,2.8,172,5500,2280,1,16.9,5,180,102,67,37,28,14,3375,0,29.1
	Audi,Midsize,19,26,2,1,6,2.8,172,5500,2535,1,21.1,6,193,106,70,37,31,17,3405,0,37.7
	BMW,Midsize,22,30,1,0,4,3.5,208,5700,2545,1,21.1,4,186,109,69,39,27,13,3640,0,30
	Buick,Midsize,22,31,1,1,4,2.2,110,5200,2565,0,16.4,6,189,105,69,41,28,16,2880,1,15.7
	Buick,Large,19,28,1,1,6,3.8,170,4800,1570,0,18,6,200,111,74,42,30.5,17,3470,1,20.8
	Buick,Large,16,25,1,0,6,5.7,180,4000,1320,0,23,6,216,116,78,45,30.5,21,4105,1,23.7
	Buick,Midsize,19,27,1,1,6,3.8,170,4800,1690,0,18.8,5,198,108,73,41,26.5,14,3495,1,26.3
	Cadillac,Large,16,25,1,1,8,4.9,200,4100,1510,0,18,6,206,114,73,43,35,18,3620,1,34.7
	Cadillac,Midsize,16,25,2,1,8,4.6,295,6000,1985,0,20,5,204,111,74,44,31,14,3935,1,40.1
	Chevrolet,Compact,25,36,0,1,4,2.2,110,5200,2380,1,15.2,5,182,101,66,38,25,13,2490,1,13.4
	Chevrolet,Compact,25,34,1,1,4,2.2,110,5200,2665,1,15.6,5,184,103,68,39,26,14,2785,1,11.4
	Chevrolet,Sporty,19,28,2,0,6,3.4,160,4600,1805,1,15.5,4,193,101,74,43,25,13,3240,1,15.1
	Chevrolet,Midsize,21,29,0,1,4,2.2,110,5200,2595,0,16.5,6,198,108,71,40,28.5,16,3195,1,15.9
	Chevrolet,Van,18,23,0,1,6,3.8,170,4800,1690,0,20,7,178,110,74,44,30.5,?,3715,1,16.3
	Chevrolet,Van,15,20,0,2,6,4.3,165,4000,1790,0,27,8,194,111,78,42,33.5,?,4025,1,16.6
	Chevrolet,Large,17,26,1,0,8,5,170,4200,1350,0,23,6,214,116,77,42,29.5,20,3910,1,18.8
	Chevrolet,Sporty,17,25,1,0,8,5.7,300,5000,1450,1,20,2,179,96,74,43,?,?,3380,1,38
	Chrysler,Large,20,28,2,1,6,3.3,153,5300,1990,0,18,6,203,113,74,40,31,15,3515,1,18.4
	Chrysler,Compact,23,28,2,1,4,3,141,5000,2090,0,16,6,183,104,68,41,30.5,14,3085,1,15.8
	Chrysler,Large,20,26,1,1,6,3.3,147,4800,1785,0,16,6,203,110,69,44,36,17,3570,1,29.5
	Dodge,Small,29,33,0,1,4,1.5,92,6000,3285,1,13.2,5,174,98,66,32,26.5,11,2270,1,9.2
	Dodge,Small,23,29,1,1,4,2.2,93,4800,2595,1,14,5,172,97,67,38,26.5,13,2670,1,11.3
	Dodge,Compact,22,27,1,1,4,2.5,100,4800,2535,1,16,6,181,104,68,39,30.5,14,2970,1,13.3
	Dodge,Van,17,21,1,2,6,3,142,5000,1970,0,20,7,175,112,72,42,26.5,?,3705,1,19
	Dodge,Midsize,21,27,1,1,4,2.5,100,4800,2465,0,16,6,192,105,69,42,30.5,16,3080,1,15.6
	Dodge,Sporty,18,24,1,2,6,3,300,6000,2120,1,19.8,4,180,97,72,40,20,11,3805,1,25.8
	Eagle,Small,29,33,0,1,4,1.5,92,6000,2505,1,13.2,5,174,98,66,36,26.5,11,2295,1,12.2
	Eagle,Large,20,28,2,1,6,3.5,214,5800,1980,0,18,6,202,113,74,40,30,15,3490,1,19.3
	Ford,Small,31,33,0,1,4,1.3,63,5000,3150,1,10,4,141,90,63,33,26,12,1845,1,7.4
	Ford,Small,23,30,0,1,4,1.8,127,6500,2410,1,13.2,5,171,98,67,36,28,12,2530,1,10.1
	Ford,Compact,22,27,0,1,4,2.3,96,4200,2805,1,15.9,5,177,100,68,39,27.5,13,2690,1,11.3
	Ford,Sporty,22,29,1,0,4,2.3,105,4600,2285,1,15.4,4,180,101,68,40,24,12,2850,1,15.9
	Ford,Sporty,24,30,1,1,4,2,115,5500,2340,1,15.5,4,179,103,70,38,23,18,2710,1,14
	Ford,Van,15,20,1,2,6,3,145,4800,2080,1,21,7,176,119,72,45,30,?,3735,1,19.9
	Ford,Midsize,21,30,1,1,6,3,140,4800,1885,0,16,5,192,106,71,40,27.5,18,3325,1,20.2
	Ford,Large,18,26,1,0,8,4.6,190,4200,1415,0,20,6,212,114,78,43,30,21,3950,1,20.9
	Geo,Small,46,50,0,1,3,1,55,5700,3755,1,10.6,4,151,93,63,34,27.5,10,1695,0,8.4
	Geo,Sporty,30,36,1,1,4,1.6,90,5400,3250,1,12.4,4,164,97,67,37,24.5,11,2475,0,12.5
	Honda,Sporty,24,31,2,1,4,2.3,160,5800,2855,1,15.9,4,175,100,70,39,23.5,8,2865,0,19.8
	Honda,Small,42,46,1,1,4,1.5,102,5900,2650,1,11.9,4,173,103,67,36,28,12,2350,0,12.1
	Honda,Compact,24,31,2,1,4,2.2,140,5600,2610,1,17,4,185,107,67,41,28,14,3040,0,17.5
	Hyundai,Small,29,33,0,1,4,1.5,81,5500,2710,1,11.9,5,168,94,63,35,26,11,2345,0,8
	Hyundai,Small,22,29,0,1,4,1.8,124,6000,2745,1,13.7,5,172,98,66,36,28,12,2620,0,10
	Hyundai,Sporty,26,34,0,1,4,1.5,92,5550,2540,1,11.9,4,166,94,64,34,23.5,9,2285,0,10
	Hyundai,Midsize,20,27,0,1,4,2,128,6000,2335,1,17.2,5,184,104,69,41,31,14,2885,0,13.9
	Infiniti,Midsize,17,22,1,0,8,4.5,278,6000,1955,0,22.5,5,200,113,72,42,29,15,4000,0,47.9
	Lexus,Midsize,18,24,1,1,6,3,185,5200,2325,1,18.5,5,188,103,70,40,27.5,14,3510,0,28
	Lexus,Midsize,18,23,2,0,6,3,225,6000,2510,1,20.6,4,191,106,71,39,25,9,3515,0,35.2
	Lincoln,Midsize,17,26,2,1,6,3.8,160,4400,1835,0,18.4,6,205,109,73,42,30,19,3695,1,34.3
	Lincoln,Large,18,26,2,0,8,4.6,210,4600,1840,0,20,6,219,117,77,45,31.5,22,4055,1,36.1
	Mazda,Small,29,37,0,1,4,1.6,82,5000,2370,1,13.2,4,164,97,66,34,27,16,2325,0,8.3
	Mazda,Small,28,36,0,1,4,1.8,103,5500,2220,1,14.5,5,172,98,66,36,26.5,13,2440,0,11.6
	Mazda,Compact,26,34,1,1,4,2.5,164,5600,2505,1,15.5,5,184,103,69,40,29.5,14,2970,0,16.5
	Mazda,Van,18,24,0,2,6,3,155,5000,2240,0,19.6,7,190,110,72,39,27.5,?,3735,0,19.1
	Mazda,Sporty,17,25,1,0,?,1.3,255,6500,2325,1,20,2,169,96,69,37,?,?,2895,0,32.5
	Mercedes-Benz,Compact,20,29,1,0,4,2.3,130,5100,2425,1,14.5,5,175,105,67,34,26,12,2920,0,31.9
	Mercedes-Benz,Midsize,19,25,2,0,6,3.2,217,5500,2220,0,18.5,5,187,110,69,37,27,15,3525,0,61.9
	Mercury,Sporty,23,26,1,1,4,1.6,100,5750,2475,1,11.1,4,166,95,65,36,19,6,2450,1,14.1
	Mercury,Midsize,19,26,0,0,6,3.8,140,3800,1730,0,18,5,199,113,73,38,28,15,3610,1,14.9
	Mitsubishi,Small,29,33,0,1,4,1.5,92,6000,2505,1,13.2,5,172,98,67,36,26,11,2295,0,10.3
	Mitsubishi,Midsize,18,24,1,1,6,3,202,6000,2210,0,19,5,190,107,70,43,27.5,14,3730,0,26.1
	Nissan,Small,29,33,1,1,4,1.6,110,6000,2435,1,13.2,5,170,96,66,33,26,12,2545,0,11.8
	Nissan,Compact,24,30,1,1,4,2.4,150,5600,2130,1,15.9,5,181,103,67,40,28.5,14,3050,0,15.7
	Nissan,Van,17,23,0,1,6,3,151,4800,2065,0,20,7,190,112,74,41,27,?,4100,0,19.1
	Nissan,Midsize,21,26,1,1,6,3,160,5200,2045,0,18.5,5,188,104,69,41,28.5,14,3200,0,21.5
	Oldsmobile,Compact,24,31,0,1,4,2.3,155,6000,2380,0,15.2,5,188,103,67,39,28,14,2910,1,13.5
	Oldsmobile,Midsize,23,31,1,1,4,2.2,110,5200,2565,0,16.5,5,190,105,70,42,28,16,2890,1,16.3
	Oldsmobile,Van,18,23,0,1,6,3.8,170,4800,1690,0,20,7,194,110,74,44,30.5,?,3715,1,19.5
	Oldsmobile,Large,19,28,1,1,6,3.8,170,4800,1570,0,18,6,201,111,74,42,31.5,17,3470,1,20.7
	Plymouth,Sporty,23,30,0,2,4,1.8,92,5000,2360,1,15.9,4,173,97,67,39,24.5,8,2640,1,14.4
	Pontiac,Small,31,41,0,1,4,1.6,74,5600,3130,1,13.2,4,177,99,66,35,25.5,17,2350,1,9
	Pontiac,Compact,23,31,0,1,4,2,110,5200,2665,1,15.2,5,181,101,66,39,25,13,2575,1,11.1
	Pontiac,Sporty,19,28,2,0,6,3.4,160,4600,1805,1,15.5,4,196,101,75,43,25,13,3240,1,17.7
	Pontiac,Midsize,19,27,0,1,6,3.4,200,5000,1890,1,16.5,5,195,108,72,41,28.5,16,3450,1,18.5
	Pontiac,Large,19,28,2,1,6,3.8,170,4800,1565,0,18,6,177,111,74,43,30.5,18,3495,1,24.4
	Saab,Compact,20,26,1,1,4,2.1,140,6000,2910,1,18,5,184,99,67,37,26.5,14,2775,0,28.7
	Saturn,Small,28,38,1,1,4,1.9,85,5000,2145,1,12.8,5,176,102,68,40,26.5,12,2495,1,11.1
	Subaru,Small,33,37,0,2,3,1.2,73,5600,2875,1,9.2,4,146,90,60,32,23.5,10,2045,0,8.4
	Subaru,Small,25,30,0,2,4,1.8,90,5200,3375,1,15.9,5,175,97,65,35,27.5,15,2490,0,10.9
	Subaru,Compact,23,30,1,2,4,2.2,130,5600,2330,1,15.9,5,179,102,67,37,27,14,3085,0,19.5
	Suzuki,Small,39,43,0,1,3,1.3,70,6000,3360,1,10.6,4,161,93,63,34,27.5,10,1965,0,8.6
	Toyota,Small,32,37,1,1,4,1.5,82,5200,3505,1,11.9,5,162,94,65,36,24,11,2055,0,9.8
	Toyota,Sporty,25,32,1,1,4,2.2,135,5400,2405,1,15.9,4,174,99,69,39,23,13,2950,0,18.4
	Toyota,Midsize,22,29,1,1,4,2.2,130,5400,2340,1,18.5,5,188,103,70,38,28.5,15,3030,0,18.2
	Toyota,Van,18,22,1,2,4,2.4,138,5000,2515,1,19.8,7,187,113,71,41,35,?,3785,0,22.7
	Volkswagen,Small,25,33,0,1,4,1.8,81,5500,2550,1,12.4,4,163,93,63,34,26,10,2240,0,9.1
	Volkswagen,Van,17,21,0,1,5,2.5,109,4500,2915,1,21.1,7,187,115,72,38,34,?,3960,0,19.7
	Volkswagen,Compact,21,30,0,1,4,2,134,5800,2685,1,18.5,5,180,103,67,35,31.5,14,2985,0,20
	Volkswagen,Sporty,18,25,0,1,6,2.8,178,5800,2385,1,18.5,4,159,97,66,36,26,15,2810,0,23.3
	Volvo,Compact,21,28,1,0,4,2.3,114,5400,2215,1,15.8,5,190,104,67,37,29.5,14,2985,0,22.7
	Volvo,Midsize,20,28,2,1,5,2.4,168,6200,2310,1,19.3,5,184,105,69,38,30,15,3245,0,26.7
EOF
}
auto93discreteClass() {
	#some learners can't handle auto93's numeric class 
	#so we discretize the class. Note that this is a pretty
	# dumb discretizer.
	auto93 | gawk  'BEGIN         {IGNORECASE=1; OFS=","; Round=20}
	                In && NF > 1  {$NF= "_"int($NF/Round+0.5)*Round}
				    $2 =="class"  {$3 = "{_0,_20,_40,_60}"}
					/@data/       {In=1; FS=","}
	                              { print}'  
}
#### some workers
worker1001() {
	local learners1="j48 oner aode nb nbk jrip"
	local learners2="aode"
	local repeats=10;
	local bins=10;
	local datas="cm1 kc1 kc2 kc3_mod mc1_mod mc2_mod mw1_mod 
				 pc1 pc2_mod pc3_mod pc4_mod pc5_mod"
	for one in $data; do
		cp $one raw.arff
		stem=`basename $one`
		stem=${stem/.*/}

		logNumbers               raw.arff            > logged.arff
		discretizeViaFayyadIrani raw.arff            > discrete.arff
		discretizeViaFayyadIrani logged.arff         > loggedDiscrete.arff

		for x in raw discrete logged loggedDiscrete; do
			rankViaInfoGain $x.arff > ranked.arff
			for attrs in 4 7 13  16; do
				removeAttributes $attrs 16 $x.arff > ranked${attrs}.arff
				blab "$stem $x $attrs "
				echo "#file,x,attrs,bin,learner,a,b,c,d,acc,pd,pf,prec,g"
				for((r=1;r<=$repeats;r++)); do
					seed=$RANDOM
					for((bin=1; bin <= $bins ;  bin++)); do
						blab "$bin"
						makeTrainTest $seed $bins $bin ranked${attrs}.arff 
						for learner in $learners1; do
							$learner train.arff test.arff | 
							gotwant | 
							abcd "$stem,$x,$attrs,$Bin,$Learner"  
						done   
						if [ $x != "raw" ]; then
							$learner train.arff test.arff | 
							gotwant | 
							abcd "$stem,$x,$attrs,$Bin,$Learner"  
					   fi
					done
				done	| medians
				blabln
			done
		done  
	done | tee $Safe/worker1001.log  
}
worker1002() {
	for one in $Data; do
		cp $one raw.arff
		stem=`basename $one`
		stem=${stem/.*/}

		logNumbers               raw.arff            > logged.arff
		discretizeViaFayyadIrani raw.arff            > discrete.arff
		discretizeViaFayyadIrani logged.arff         > loggedDiscrete.arff

		for x in discrete loggedDiscrete; do
			rankViaInfoGain $x.arff > ranked.arff
			for Attrs in 4 7 13  16; do
				removeAttributes $Attrs 16 $x.arff > ranked${Attrs}.arff
				blab "$stem $x $Attrs "
				Seed=$RANDOM
				echo "#file,x,attrs,bin,learner,a,b,c,d,acc,pd,pf,prec,g"
				for((R=1;R<=$Repeats;R++)); do
					for((Bin=1; Bin <= $Bins ;  Bin++)); do
						blab "."
						makeTrainTest $Seed $Bins $Bin ranked${Attrs}.arff 
						for Learner in $Learners; do
							$Learner train.arff test.arff | 
							gotwant | 
							abcd "$stem,$x,$Attrs,$Bin,$Learner"  
						done   
					done
				done	| medians
				blabln
			done
		done  
	done 
}
#### some demos
demo3() {
	cd $Tmp
	weather.nominal > data.arff
	j4810 data.arff  
	cd $Here
}
demo4() {
	cd $Tmp
	weather.nominal > data.arff
	j4810 data.arff  | report 4 3
	cd $Here
}
demo5() {
	cd $Tmp
	weather.nominal > data.arff
	j4810 data.arff  | report 4 3,18,16
	cd $Here
}
demo5a() {
	j4810 $Ourmine/lib/arffs/uci/discrete/soybean.arff  
}
demo6() {
	cd $Tmp
	weather.nominal > data.arff
	nb10 data.arff  
	cd $Here
}
demo7() {
	cd $Tmp
	weather.nominal > data.arff
	nb10 data.arff | report 4 2,3,4,5
	cd $Here
}
demo8() {
	cd $Tmp
	weather.nominal > data.arff
	nb10 data.arff | report 4 18,16
	cd $Here
}
demo9() {
	cd $Tmp
	weather.nominal > data.arff
	j48 data.arff data.arff
	cd $Home
}
demo10() {
	demo9 | gotwant
}
demo11() {
	demo10 | 
	abcd --before "\na,b,c,d,acc,pd,pf,prec,bal\n" --decimals 1 |
	malign
}
demo12() {
	cd $Tmp
	auto93discreteClass  > data.arff
	j48 data.arff data.arff | gotwant 
	cd $Here
}
demo13() {
	demo12 |  gawk -F, '$1 != $2'
}
demo14() {
	demo12 |  
	for goal in _0 _20 _40 ; do
		abcd --goal "$goal" \
		     --prefix "auto93d,$goal" \
	         --before "\n#data,goal,a,b,c,d,acc,pd,pf,prec,bal\n" \
		 	 --decimals 1  
	done | malign
}
demo15() {
	cd $Tmp
	(	echo "#data,bin, a,b,c,d,acc,pd,pf,prec,bal" 
		seed=$RANDOM;	
		for((bin=1;bin<=10;bin++)); do
			blab "$bin"
			auto93discreteClass  | someArff --seed $seed --bins $Bins --bin $bin 
			j48 train.arff test.arff | gotwant | 
			abcd --goal "_20"  --prefix "auto93,$bin"  --decimals 1  
		done | sort -t, -n -k 11,11
    ) | malign > demo15.csv #each bin
	blabln " "
	echo ""; cat demo15.csv
	cp demo15.csv $Safe/demo15.csv
	cd $Here
}
demo16() {
	cd $Tmp
	(	echo "#data,repeat,bin,a,b,c,d,acc,pd,pf,prec,bal" 
		for((r=1;r<=2;r++)); do
			blab "repeat=$r "
			seed=$RANDOM;	
			for((bin=1;bin<=5;bin++)); do
				blab "$bin"
				auto93discreteClass  | someArff --seed $seed --bins $Bins --bin $bin 
				j48 train.arff test.arff | gotwant |
				abcd --goal "_20"  --prefix "auto93,$r,$bin" --decimals 1  
			done 
			blabln 
		done | sort -t, -n -k 12,12
    ) | malign > demo15.csv #each bin
	blabln " "
	echo ""; cat demo15.csv
	cp demo15.csv $Safe/demo15.csv
	cd $Here
}
demo17() {
	local me=demo17
	local bins=10
	local repeats=2
	local learners="oner nb j48"
	local datas="diabetes autos"
	cd $Tmp
	(echo "#data,repeat,bin,learner,goal,a,b,c,d,acc,pd,pf,prec,bal" 
	for data in $datas; do
		arff=$Ourmine/lib/arffs/uci/discrete/$data.arff
		for((r=1;r<=$repeats;r++)); do
			blab "data=$data repeat=$r "
			seed=$RANDOM;	
			for((bin=1;bin<=$bins;bin++)); do
				blab "$bin"
				cat $arff | someArff --seed $seed --bins $bins --bin $bin 
				goals=`cat $arff | classes --brief`
				for learner in $learners; do
					$learner train.arff test.arff | gotwant > results.dat 
					for goal in $goals; do
						cat results.dat |
						abcd --goal "$goal" \
	  				 	     --prefix "$data,$r,$bin,$learner,$goal" \
						     --decimals 1  
					done
				done				
			done 
			blabln 
		done 
	done				
	) | sort -t, -n -k 14,14 | malign > $me.csv #each bin
	blabln " "
	echo ""; cat $me.csv
	cp $me.csv $Safe/$me.csv
	cd $Here
}
demo18() {
	local stats="$Safe/demo17.csv"
	local learners="nb j48 oner"
	local datas="diabetes autos"
	[ ! -f "$stats" ] && demo17
	(echo "#data,learner,goal,a,b,c,d,acc,pd,pf,prec,bal" 
	for data in $datas; do
		for learner in $learners; do
			echo -n "$data,$learner, "
			grep $data $stats | grep $learner | medians --start 6 | grep "##" 
		done
	done ) | malign | sort -t, -n -k 12,12
}
demo19() {
	local stats="$Safe/demo17.csv"
	[ ! -f "$stats" ] && demo17
	winLossTie --input $stats --fields 14 --perform 14 --key 4  --95 --high
}
demo21() {
	local me=demo21
	local rs=10
	local bins=10
	local secrets=$HOME/svns/nextgen/trunk/doc/arffs/raw
	local attrs="classic_metrics inter_metrics intra_metrics"
	local arffs=`ls $secrets/function*.arff | grep -v pair`
	local arffs="$secrets/function_data.arff"
	cd $Tmp
	for arff in $arffs; do
		cat $arff | logNumbers > logged.arff
		for((r=1;r<=rs;r++));  do
			local seed=$RANDOM
			for((b=1;b<=bins;b++)); do
				cat logged.arff | someArff --bins $bins --bin $b --seed $seed
				for attr in $attrs; do
					local want=`cat $secrets/$attr; echo defects`
					some "$want" train.arff > trainSome.arff
					some "$want" test.arff  > testSome.arff
					nb  trainSome.arff  testSome.arff | 
					gotwant |
					abcd --goal "true" --decimals 2 \
					     --prefix "`basename $arff`,$attr,$r,$b"
				done
			done
		done
	done | tee $Safe/$me.log
	sort -t, -n -k 13,13 $Safe/$me.log | malign
}
demo22() {
		local attrs="classic_metrics inter_metrics intra_metrics"
		local log=$Safe/demo21.log
		[ ! -f $log ] && demo21
		echo ""
		(echo "#treatment,min,q1,median,q3,max,"
		for attr in $attrs; do
			echo -n "$attr,"
			grep $attr $log | cut -d, -f 13 | quartile | malign
		done | sort -t, -r -k 4,4
		) | malign
		echo ""
		winLossTie --input $log --fields 13 --perform 13 --key 2 --95 --high
		echo ""
		winLossTie --input $log --fields 13 --perform 13 --key 2 --99 --high
}
funs() {
	gawk 'In && NF>20 {print $1} /@data/ {In=1}' FS="," IGNORECASE=1 $1 | sort | uniq
}
# logNumbers miss row 1
# only work on the dynamic metrics
parts() {
	local me=parts
	local secrets=$HOME/svns/nextgen/trunk/doc/arffs/raw
	local all="$secrets/function_data.arff"
	local parts="`ls $secrets/function_[0-9]*.arff`";
	local inter=`echo function_name; cat $secrets/interClassic_metrics; echo defects`
	local inter1=`cat $secrets/interClassic_metrics; echo defects`
	cd $Tmp
	some "$inter" $all | logNumbers >  all_interLogged.arff
	for part in `ls $secrets/function_[0-9]*.arff`; do

		funs $part > funs.out
		some "$inter"  $part | logNumbers > isolated0.arff 
		some "$inter1" isolated0.arff > isolated.arff

		gawk 'BEGIN       { FS=","; while (getline want < "funs.out" ) Wants[want]=1; close("funs.out")}
			  /@/         { print; next }
		      $1 in Wants { print }' all_interLogged.arff > ensembled0.arff
		some "$inter1" ensembled0.arff > ensembled.arff

		gawk 'BEGIN       { FS=","; while (getline want < "funs.out" ) Wants[want]=1; close("funs.out")}
			  /@/         { print; next; }
		      (! ($1 in Wants)) { print }' all_interLogged.arff  > otherEnsembled0.arff
		some "$inter1" otherEnsembled0.arff > otherEnsembled.arff
	    
		nb otherEnsembled.arff ensembled.arff | gotwant | abcd --goal "true" --prefix "`basename $part`,ensemble"
		nb otherEnsembled.arff isolated.arff  | gotwant | abcd --goal "true" --prefix "`basename $part`,isolated"
	done > $Safe/$me.out
	cd $Here
}
demo23() {
	log=$Safe/parts.out
	[ ! -f "$log" ] && parts
	(echo  "#data,type,a,b,c,d,acc,pd,pf,precision,balance"
	cat $log) | malign 
}
demo24() {
	local me=demo24
	local datas="weather.nominal diabetes hypothyroid"
	cd $Tmp
	for data in $datas; do
		arff=$Ourmine/lib/arffs/uci/discrete/$data.arff
		printf "\n---| `basename $arff` |-----------\n\n"
		j4810 $arff | report 4 3
		cat $arff | gains | sort -n -t, -r -k 3,3
	done
}
demo25() {
	local me=demo25
	local datas="anneal audiology breast-cancer kr-vs-kp mushroom 
	            primary-tumor soybean splice vote weather.nominal"
	local repeats=10
	local bins=10
	local learners="j48 nb nbd"
	cd $Tmp
	(echo "#data,repeat,bin,learner,goal,a,b,c,d,acc,pd,pf,prec,bal" 
	for data in $datas; do
		arff=$Ourmine/lib/arffs/uci/discrete/$data.arff
		for((r=1;r<=$repeats;r++)); do
			blab "data=$data repeat=$r "
			seed=$RANDOM;	
			for((bin=1;bin<=$bins;bin++)); do
				blab "$bin"
				cat $arff | someArff --seed $seed --bins $bins --bin $bin 
				goals=`cat $arff | classes --brief`
			 	for learner in $learners; do
					$learner  train.arff test.arff  | gotwant >   results.dat 
					for goal in $goals; do
						cat results.dat |
						abcd --goal "$goal" \
	  				 	     --prefix "$data,$r,$bin,$learner,$goal" \
						     --decimals 1  
					done
				done				
			done 
			blabln 
		done 
	done				
	) | sort -t, -n -k 14,14 | malign > $me.csv 
	blabln " "
	echo ""; cat $me.csv
	cp $me.csv $Safe/$me.csv
	cd $Here
}
demo26() {
	local log=$Safe/demo25.csv
	[ ! -f $log ] && demo25
	local learners="nbd nb j48"
	local datas="anneal audiology breast-cancer kr-vs-kp mushroom 
			     primary-tumor soybean splice vote weather.nominal"
	cd $Tmp
	winLossTie --input $log --fields 14 --perform 14 --key 4 --95 --high
	for data in $datas; do
		printf "\n---| $data |-----------------\n\n";
		cat $log | grep $data > some.dat
		(echo "#learner,min,q1,median,q3,max,"
		for learner in $learners; do
			echo -n "$learner,";
			grep $learner some.dat | cut -d, -f 14 | quartile
		done
		) | malign
		echo ""
		winLossTie --input some.dat --fields 14 --perform 14 --key 4 --95 --high
	done
	cd $Here
}
demo27() {
	cd $Tmp
	local me=demo27
	local datas="anneal audiology breast-cancer kr-vs-kp mushroom 
				 primary-tumor soybean splice vote "
	for data in $datas; do
		arff=$Ourmine/lib/arffs/uci/discrete/$data.arff
	    cat $arff | someArff --seed $RANDOM --bins 10 --bin 1 
		nba train.arff test.arff > out
		cat out | gawk -F, 'BEGIN {FS=OFS=","} $2 == $NF {print $0}' | cut -d, -f 1 > good
		cat out | gawk -F, 'BEGIN {FS=OFS=","} $2 != $NF {print $0}' | cut -d, -f 1 > bad
		echo ""
		for i in good bad; do
			printf "\n ---| $data $i |-----------------------\n\n"
			cat $i | gawk '	
				function str(n,chr, out) {
				chr = chr ? chr : " ";
				while(n-- > 0) out= out chr;
					return out
				}
				{n[int($0)]++; N++} 
				END {
				for(i in n) {
					m = int(100*n[i]/N/3)
					if (m) print i "," m*3,  "," str(m,"X") str(33-m,".") 
					}
				}
			' | sort -r -n | malign 
		done
	done  | tee $Safe/$me.csv
	cd $Here
}
demo28() { # nick's stuff
	cat nick/3x10all.csv | 
	gawk -F, 'NR==1 {print $0 "," f;next} {print $0 "," 2*$11*$13/($11 + $13 + 0.0000001)}' > /tmp/f
   for i in a b c d e f g h i j k l m; do grep ",$i," /tmp/f |
	   cut -d, -f 11 |gawk 'NR==1 {next} {print}' > /tmp/$i.pd; done
   for i in a b c d e f g h i j k l m; do grep ",$i," /tmp/f |
	   cut -d, -f 13 |gawk 'NR==1 {next} {print}' > /tmp/$i.prec; done
   for i in a b c d e f g h i j k l m; do grep ",$i," /tmp/f  |
	   cut -d, -f 15 |gawk 'NR==1 {next} {print}' > /tmp/$i.f; done
	   echo
   (
    for i in a b c d e f g h i j k l m; do echo -n "pd,$i," ; cat  /tmp/$i.pd | quartile; done
   winLossTie --input /tmp/f --fields 15 --key 4 --perform 11 --95 --high 
   echo
   for i in a b c d e f g h i j k l m; do echo -n "prec,$i," ; cat  /tmp/$i.prec | quartile; done
   winLossTie --input /tmp/f --fields 15 --key 4 --perform 13 --95 --high 
   echo
   for i in a b c d e f g h i j k l m; do echo -n "f,$i," ; cat  /tmp/$i.f | quartile; done
   winLossTie --input /tmp/f --fields 15 --key 4 --perform 15 --95 --high 
   ) | tee $Safe/demo28.log
}
### stop reading. broken after this/
flip() {
	local data
	local key
	local performance
	while [ `echo $1 | grep "-"` ]; do
		case $1 in
			-d|--data) data="$2";;
			-k|--key) key="$2";;
			-p|--performance) performance=$3;;
			*)   blabln "'"$1"' unknown\n usage cat file | flip [options]"
			     return 1;;
    	esac
		shift 2
	done
	gawk  '
 	BEGIN {FS=OFS=","}
	NR==1 {
		split(DataStr,TheData,/,/);
		split(KeyStr,TheKeys,/,/);
		  }
	/^[ \t]*#[^[#]/   {next}
	      {   key=data="";
			  for(d in TheData) data = data "." $d;
			  for(k in TheKeys) key  = key "." $k;
			  Result[key,data]=$Performance;
			  if ($Performance > Max[data] ) { Max[data]=$Performance}
			  Keys[key]=key
			  Datas[data]=data
	      }
     END {printf "#data"
	      for(K in Keys) printf "," K ",max?"
		  print ""
		  exit
		  for(D in Datas) {
			  	printf D
				for(K in Keys) {
				  printf "," Result[K,D]
				printf (Result[K,D]== Max[D]) ? ",X" : ","
			}
		    print ""
		}}
	' DataStr=$data KeyStr=$key Performance=$performance  -
	#| medians | malign
}
summary() {
	cd $Tmp
	local stats="$Safe/demo17.csv"
	[ ! -f "$stats" ] && demo17
	demo18 | flip --data 1 --key 2 --performance 12
	printf "\n---| all |------\n\n"
	winLossTie --input $stats --fields 14 --perform 14 --key 4  --95 --high 
	for d in diabetes autos; do
		printf "\n---| $d |------\n\n"
		grep $d $stats  > $d.stats;
		winLossTie --input $d.stats --fields 14 --perform 14 --key 4  --95 --high 
	done

}
demo101() {
	local me=demo101
	local stats="$HOME/tmp/safe/demo2.log"
	local learners="aode j48 jrip nb oner"
	local preps="loggedDiscrete discrete"
	local datas="cm1 kc1 kc2 kc3_mod mc1_mod mc2_mod mw1_mod 
				 pc1 pc2_mod pc3_mod pc4_mod pc5_mod"
	(echo "#data,prep,attrs,bin,learner,a,b,c,d,acc,pd,pf,prec,bal" 
	for data in $datas; do
		for learner in $learners; do
			for prep in $preps; do
				cat $stats |
				grep -v '#' | 
				grep $data  | 
				grep $prep   | 
				grep $learner  | sort -t, -n -k 14,14 | medians --start 6 
			done 
		done
	done 
	) > $Safe/$me.log
	cat $Safe/$me.log 
}
demo102() {
	cd $Tmp
	local stats="$Safe/demo101.log"
	[ ! -f "$stats" ] && demo101
	cat $stats | grep "##" | flip --data 1 --key 2,5 --performance 14
}
demo103() { #zach's stuff
		local me=demo103
		local in=$HOME/wisp/var/Zach/var/whichOut/AUCwithRocky.csv
		cd $Tmp
		cat $in > ready.csv
		local data=`cut     -d, -f 1 ready.csv | sort | uniq` 
		local learners=`cut -d, -f 6 ready.csv | sort | uniq` 
		for d in $data; do
			printf "\n\n===| $d |=======\n"
			for l in $learners; do
					echo -n "$l ,"
					grep $l ready.csv | grep $d | cut -d, -f 7  | tee $d$l.done | quartile 
				done | malign | sort -n -t, +3
		done | tee $Safe/$me.out
		echo $Safe/$me.out
}
# manaul > anything else
# standard elarners worse
# which whins
#
demo104() { #zach's stuff
	    cd $Tmp
		local me=demo104
		local in1=$HOME/svns/wisp/var/Zach/var/whichOut/AUCwithMicro.csv
		local in2=$HOME/svns/wisp/var/Zach/var/whichOut/AUCwithTurkey.csv
	    in=$Tmp/in
        cat $in1 > $in
	    cat $in2 | sed 's/manual/manualDown/' | sed 's/launam/manualUp/' >> $in
	 	#local in=/srv/bronze/zach/wisp/var/Zach/var/whichOut/AUCfinitelist.csv
		#cd $Tmp
		cat $in  | grep -v rocky | grep -v micro10 | grep -v micro5 | 
                   grep -v micro30 | grep -v micro75 | grep -v loc  > ready.csv
		local data=`cut     -d, -f 1 ready.csv | grep -v data    | 
                    grep -v pc3 | sort | uniq` 
		local learners=`cut -d, -f 6 ready.csv | grep -v learner | sort | uniq` 
		for d in "," $data; do
			printf "\n\n===| $d |=======\n"
			grep $d ready.csv > ready1.csv
			for l in $learners  ; do
				echo -n "$l,"
				grep "$l," ready1.csv | cut -d, -f 7 |sort -n | quartile  
				     #gawk 'BEGIN {OFS=","}
				     #        	 {N++; F[N] =$1} 
					#	   END  {N1=int(N/2);
					#	        if (N % 2) { print N,int(F[N1]) 
					#			} else {    	
					#					N2 = N1+1;
					#					print N,int((F[N1] + F[N2])/2)
					#					}}'
				done | sort -r -t, -n -k 4  |malign
			echo ""
			winLossTie --input ready1.csv --fields 7 --perform 7 --key 6 --99 --high
		done >  $Safe/$me.out
		echo $Safe/$me.out
		cd $Here
}
demo104a() {
	local in=$Safe/demo104.out
    [ ! -f $in ] && demo104
	cd $Tmp
	cat $in | quartile2tex > $Safe/demo104a.out
	cd $Here
}
# number of controllables
demo105() {
		local me=demo105
		local src="$HOME/wisp/var/timm/08/data.csv"
		ls -lsa "$src"
		rm -f $Safe/$me_*
		gawk 'NR==1 {next} {print}'  "$src" > $Tmp/data.csv
		(cd $Tmp
		local projects=`cut     -d, -f 1 data.csv    | sort | uniq` 
		local policies=`cut     -d, -f 2 data.csv    | sort | uniq` 
		local scorings=`cut     -d, -f 3 data.csv    | sort | uniq` 
		local mutations=`cut     -d, -f 4 data.csv    | sort | uniq` 

		demo105selector project,policy,MinMedE  data.csv  | 
		gawk -F, '{OFS=","; $NF=100*$NF; print $0}'> testa 
		(printf "POLICIES\n\n`date`\n\n"
		for p in  overall $projects
		do	grep "$p," testa > relevant
			printf "\n\n----| $p |----------\n\n"
			for pol in $policies; do
						echo -n "$pol,"
						grep ",$pol," relevant | gawk -F, '{print $NF}' | 
							quartile |
							 sort -t, -n +2
			done | malign
			echo "" 
			winLossTie --input relevant --fields 4 --perform 4 --key "3" --99 --low
		done  ) > $Safe/$me_policyAbsoluteE.txt

		# changing policies rarely effects anything. the final numbers are so low. but Bug?

		
#		demo105selector project,policy,FirstMedThreat,MinMedThreat data.csv  | 
#		gawk -F, '{OFS=","; print $0,100*($NF/(0.0000000001 + $(NF-1)));}' >  testa 
#		printf "HOW MUCH THREAT CONTROL DO WE ACHIEVE?\n\n`date`\n\n"  
#		for p in  overall $projects
#		do	grep "$p," testa > relevant
#			printf "\n\n----| $p |----------\n\n"
#			for pol in $policies; do
#						echo -n "$pol,"
#						grep ",$pol," relevant | gawk -F, '{print $NF}' | quartile
#			done | malign
#			echo "" 
#			winLossTie --input relevant --fields 6 --perform 6 --key "3" --95 --low
#		done   >  $Safe/$me_reduceTHREATS.txt
#		# usually, healthy reducions in defects
#	
		demo105selector project,policy,FirstMedMonths,MinMedMonths data.csv  | 
		gawk -F, '{OFS=","; print $0,100*($NF/$(NF-1));}' >  testa 
		printf "HOW MUCH MONTHS CONTROL DO WE ACHIEVE?\n\n`date`\n\n"
		for p in  overall $projects
		do	grep "$p," testa > relevant
			printf "\n\n----| $p |----------\n\n"
			for pol in $policies; do
						echo -n "$pol,"
						grep ",$pol," relevant | gawk -F, '{print $NF}' | quartile
			done | malign | sort -n -t, -n +3 
			echo "" 
			winLossTie --input relevant --fields 6 --perform 6 --key "3" --99 --low
		done  >  $Safe/$me_reduceMonths.txt

		# usually, healthy reducions in defects
			demo105selector project,scoring,mutation,numPol data.csv > testa 
		printf "HOW MUCH important ins mutation? ?\n\n`date`\n\n"
		for p in  overall $projects
		do	grep "$p," testa > relevant
			printf "\n\n----| $p |----------\n\n"
				for score in $scorings; do
						for mut in $mutations; do
						grep ",$score,$mut," relevant | gawk -F, '{print $NF}' | quartile
							done
			done | malign | sort -n -t, -n +3  
			echo "" 
			winLossTie --input relevant --fields 5 --perform 5 --key "3,4" --99 --low
		done  | tee  $Safe/$me_mutValue.txt

		# usually, healthy reducions in defects
	
		exit	
	
		demo105selector project,policy,FirstMedDefects,MinMedDefects data.csv  | 
		gawk -F, '{OFS=","; print $0,100*($NF/$(NF-1));}' >  testa 
		printf "HOW MUCH DEFECTS CONTROL DO WE ACHIEVE?\n\n`date`\n\n"
		(printf "HOW MUCH DEFECTS CONTROL DO WE ACHIEVE?\n\n`date`\n\n"
		for p in  overall $projects
		do	grep "$p," testa > relevant
			printf "\n\n----| $p |----------\n\n"
			for pol in $policies; do
						echo -n "$pol,"
						grep ",$pol," relevant | gawk -F, '{print $NF}' | quartile
			done | malign
			echo "" 
			winLossTie --input relevant --fields 6 --perform 6 --key "3" --95 --low
		done  ) >  $Safe/$me_reduceEffort.txt

		# usually, healthy reducions in defects
	
			
		demo105selector project,policy,FirstMedEffort,MinMedEffort data.csv  | 
		gawk -F, '{OFS=","; print $0,100*($NF/$(NF-1));}' >  testa 
		printf "HOW MUCH EFFORT CONTROL DO WE ACHIEVE?\n\n`date`\n\n"
		(printf "HOW MUCH EFFORT CONTROL DO WE ACHIEVE?\n\n`date`\n\n"
		for p in  overall $projects
		do	grep "$p," testa > relevant
			printf "\n\n----| $p |----------\n\n"
			for pol in $policies; do
						echo -n "$pol,"
						grep ",$pol," relevant | gawk -F, '{print $NF}' | quartile
			done | malign
			echo "" 
			winLossTie --input relevant --fields 6 --perform 6 --key "3" --95 --low
		done  ) >  $Safe/$me_reduceEffort.txt

		# usually, healthy reducions in effort
	
#	
#		demo105selector project,policy,FirstMedE,MinMedE data.csv  | 
#		gawk -F, '{OFS=","; print $0,100*($NF/$(NF-1));}' >  testa 
#		(printf "HOW MUCH ENERGY CONTROL DO WE ACHIEVE?\n\n`date`\n\n"
#		for p in  overall $projects
#		do	grep "$p," testa > relevant
#			printf "\n\n----| $p |----------\n\n"
#			for pol in $policies; do
#						echo -n "$pol,"
#						grep ",$pol," relevant | gawk -F, '{print $NF}' | quartile
#			done | malign
#			echo "" 
#			winLossTie --input relevant --fields 6 --perform 6 --key "3" --95 --low
#		done  ) > tee  $Safe/$me_reduceEnergy.txt
#
#		# strange- often the energy reduction is close to 0	
#	
	#		demo105selector project,scoring,mutation,MinMedE,MinSpE  data.csv | 
#		gawk -F, '{OFS=",";print $1,$2, $3,$4,100*$5/($6+0.00000000001)}' >    testa
#		(printf "MUTATION SCORING VS RATIO MIN MEDIAN/SPREAD \n\n`date`\n\n"
#		for p in  overall $projects
#		do	grep "$p," testa > relevant
#			printf "\n\n----| $p |----------\n\n"
#			for score in $scorings; do
#				for mut in $mutations; do	
#						echo -n "$score,$mut,"
#						grep ",$score,$mut," relevant | gawk -F, '{print $NF}' | quartile
#				done
#			done | malign
#			echo "" 
#			winLossTie --input relevant --fields 5 --perform 5 --key "3,4" --95 --high
#		done  ) >  $Safe/$me_mutationScoringRatio.txt
#
#		# mutation and scoring policies do not effect variance reduction
#
#		demo105selector project,scoring,mutation,numPol  data.csv >  testa
#		(printf "MUTATION SCORING VS NUMBER OF pOLICIES\n\n`date`\n\n"
#		for p in  overall $projects
#		do	grep "$p," testa > relevant
#			printf "\n\n----| $p |----------\n\n"
#			for score in $scorings; do
#				for mut in $mutations; do	
#						echo -n "$score,$mut,"
#						grep ",$score,$mut," relevant | gawk -F, '{print $NF}' | quartile
#				done
#			done | malign
#			echo "" 
#			winLossTie --input relevant --fields 5 --perform 5 --key "3,4" --95 --low
#		done) >   $Safe/$me_mutationScoringPolicies.txt
#
#		# mutation and scoring policies do not effect # of policies
#
		demo105selector project,scoring,mutation,FirstMedThreat,MinMedThreat  data.csv | 
		gawk -F, '{print $0,",",100*$NF/$(NF-1)}' >   testa
		(printf "MUTATION SCORING VS THREAT REDUCTION\n\n`date`\n\n"
		for p in  overall $projects
		do	grep "$p," testa > relevant
			printf "\n\n----| $p |----------\n\n"
			for score in $scorings; do
				for mut in $mutations; do	
						echo -n "$score,$mut,"
						grep ",$score,$mut," relevant | gawk -F, '{print $NF}' | quartile
				done
			done | malign
			echo "" 
			winLossTie --input relevant --fields 7 --perform 7 --key "3,4" --95 --low
		done  ) >  $Safe/$me_mutationScoringThreat.txt

		# bore|extreme best at defect reduction

		demo105selector project,scoring,mutation,FirstMedMonths,MinMedMonths  data.csv | 
		gawk -F, '{print $0,",",100*$NF/$(NF-1)}' >   testa
		printf "MUTATION SCORING VS MONTHS REDUCTION\n\n`date`\n\n"
		(printf "MUTATION SCORING VS MONTHS REDUCTION\n\n`date`\n\n"
		for p in  overall $projects
		do	grep "$p," testa > relevant
			printf "\n\n----| $p |----------\n\n"
			for score in $scorings; do
				for mut in $mutations; do	
						echo -n "$score,$mut,"
						grep ",$score,$mut," relevant | gawk -F, '{print $NF}' | quartile
				done
			done | malign
			echo "" 
			winLossTie --input relevant --fields 7 --perform 7 --key "3,4" --95 --low
		done  ) >  $Safe/$me_mutationScoringMonths.txt

		# bore|extreme best at defect reduction

		demo105selector project,scoring,mutation,FirstMedDefects,MinMedDefects  data.csv | 
		gawk -F, '{print $0,",",100*$NF/$(NF-1)}' >   testa
		printf "MUTATION SCORING VS DEFECT REDUCTION\n\n`date`\n\n"
		(printf "MUTATION SCORING VS DEFECT REDUCTION\n\n`date`\n\n"
		for p in  overall $projects
		do	grep "$p," testa > relevant
			printf "\n\n----| $p |----------\n\n"
			for score in $scorings; do
				for mut in $mutations; do	
						echo -n "$score,$mut,"
						grep ",$score,$mut," relevant | gawk -F, '{print $NF}' | quartile
				done
			done | malign
			echo "" 
			winLossTie --input relevant --fields 7 --perform 7 --key "3,4" --95 --low
		done  ) >  $Safe/$me_mutationScoringDefects.txt

		# bore|extreme best at defect reduction

		demo105selector project,scoring,mutation,FirstMedEffort,MinMedEffort  data.csv | 
		gawk -F, '{print $0,",",100*$NF/$(NF-1)}' >   testa
		printf "MUTATION SCORING VS EFFORT REDUCTION\n\n`date`\n\n"
		(printf "MUTATION SCORING VS EFFORT REDUCTION\n\n`date`\n\n"
		for p in  overall $projects
		do	grep "$p," testa > relevant
			printf "\n\n----| $p |----------\n\n"
			for score in $scorings; do
				for mut in $mutations; do	
						echo -n "$score,$mut,"
						grep ",$score,$mut," relevant | gawk -F, '{print $NF}' | quartile
				done
			done | malign
			echo "" 
			winLossTie --input relevant --fields 7 --perform 7 --key "3,4" --95 --low
		done  ) >  $Safe/$me_mutationScoringEffort.txt

		# mutation and scoring policies do not effect effort reduction
		)
}
demo105selector() {
	cat $2 |
	gawk -F, -v Want=$1 'BEGIN {
			dd();
			args();
		
	}
	{printf "overall"; for(I=1;I<=N;I++) printf(",%s",$Goals[I]) ; print "";}
	function args( n,tmp) {
		N=split(Want,tmp,/,/);
		for(i=1;i<=N;i++)
			Goals[i]=Dd[tmp[i]]
	}
	function dd() {
	Dd["project"] = 1;
	Dd["policy"] = 2;
	Dd["scoring"] = 3;
	Dd["mutation"] = 4;
	Dd["alpha"] = 5;
	Dd["beta"] = 6;
	Dd["gamma"] = 7;
	Dd["delta"] = 8; 
	Dd["relydefect"] = 9;
	Dd["run"] = 10;
	Dd["N"] = 11;
	Dd["SANum"] = 12;
	Dd["SATime"] = 13;
	Dd["TotalTime"] = 14;
	Dd["minEnergy"] = 15;
	Dd["numPol"] = 16;
	Dd["FirstMedE"] = 17;
	Dd["FirstSpE"] = 18;
	Dd["FirstMedEffort"] = 19;
	Dd["FirstSpEffort"] = 20;
	Dd["FirstMedDefects"] = 21;
	Dd["FirstSpDefects"] = 22;
	Dd["FirstMedThreat"] = 23;
	Dd["FirstSpThreat"] = 24;
	Dd["FirstMedMonths"] = 25;
	Dd["FirstSpMonths"] = 26;
	Dd["MinMedE"] = 27;
	Dd["MinSpE"] = 28;
	Dd["MinMedEffort"] = 29
	Dd["MinSpEffort"] = 30;
	Dd["MinMedDefects"] = 31;
	Dd["MinSpDefects"] = 32;
	Dd["MinMedThreat"] = 33;
	Dd["MinSpThreat"] = 34;
	Dd["MinMedMonths"] = 35;
	Dd["MinSpMonths"] = 36;
	} '
}
lasttimes100() {
		gawk -F, '{OFS=","; $NF=100*$NF; print $0}' -
}
demo106() {
		local me=demo106
		local src="$HOME/wisp/var/timm/08/data-sampling.csv"
		ls -lsa "$src"
		rm -f $Safe/$me_*
		gawk 'NR==1 {next} {print}'  "$src" > $Tmp/data.csv
		cd $Tmp
		local projects=`cut     -d, -f 1 data.csv    | sort | uniq` 
		local policies=`cut     -d, -f 2 data.csv    | sort | uniq` 
		local scorings=`cut     -d, -f 3 data.csv    | sort | uniq` 
		local mutations=`cut     -d, -f 4 data.csv    | sort | uniq` 
		local        ns=`cut     -d, -f 11 data.csv    | sort | uniq` 
		local      sanums=`cut     -d, -f 12 data.csv    | sort | uniq` 
	echo "ns $ns"
	echo "sanums $sanums"
		#demo106selector project,SANum,N,MinSpE,MinMedE,MinSpEffort,MinMedEffort  data.csv  >  testa 

		demo106selector project,SANum,FirstMedEffort,MinMedEffort  data.csv  |
		gawk -F, '{OFS=","; print $0, 100*$(NF)/($(NF-1)+ 0.00000001)}'>  testa 
		for p in  overall $projects
		do	
				grep "$p," testa > relevant
			printf "\n\n----| $p |----------\n\n"
			for a in $sanums; do
						echo -n "$a," 
						grep ",$a," relevant | gawk -F, '{print $NF}' | 
							quartile |
							 sort -t, -n +2
			done | malign | sort -t, -n +3
			echo "" 
			echo "n"
			winLossTie --input relevant --fields 6 --perform 6 --key "3" --95 --low
		done   |tee $Safe/${me}_sa_Effort.txt


		demo106selector project,SANum,FirstMedDefects,MinMedDefects  data.csv  |
		gawk -F, '{OFS=","; print $0, 100*$(NF)/($(NF-1)+ 0.00000001)}'>  testa 
		for p in  overall $projects
		do	
				grep "$p," testa > relevant
			printf "\n\n----| $p |----------\n\n"
			for a in $sanums; do
						echo -n "$a," 
						grep ",$a," relevant | gawk -F, '{print $NF}' | 
							quartile |
							 sort -t, -n +2
			done | malign | sort -t, -n +3
			echo "" 
			echo "n"
			winLossTie --input relevant --fields 6 --perform 6 --key "3" --95 --low
		done   |tee $Safe/${me}_sa_Defects.txt


		demo106selector project,SANum,FirstMedMonths,MinMedMonths  data.csv  |
		gawk -F, '{OFS=","; print $0, 100*$(NF)/($(NF-1)+ 0.00000001)}'>  testa 
		for p in  overall $projects
		do	
				grep "$p," testa > relevant
			printf "\n\n----| $p |----------\n\n"
			for a in $sanums; do
						echo -n "$a," 
						grep ",$a," relevant | gawk -F, '{print $NF}' | 
							quartile |
							 sort -t, -n +2
			done | malign | sort -t, -n +3
			echo "" 
			echo "n"
			winLossTie --input relevant --fields 6 --perform 6 --key "3" --95 --low
		done   |tee $Safe/${me}_sa_Months.txt


		demo106selector project,SANum,FirstMedThreat,MinMedThreat  data.csv  |
		gawk -F, '{OFS=","; print $0, 100*$(NF)/($(NF-1)+ 0.00000001)}'>  testa 
		for p in  overall $projects
		do	
				grep "$p," testa > relevant
			printf "\n\n----| $p |----------\n\n"
			for a in $sanums; do
						echo -n "$a," 
						grep ",$a," relevant | gawk -F, '{print $NF}' | 
							quartile |
							 sort -t, -n +2
			done | malign | sort -t, -n +3
			echo "" 
			echo "n"
			winLossTie --input relevant --fields 6 --perform 6 --key "3" --95 --low
		done   |tee $Safe/${me}_sa_Threat.txt

return 0

		demo106selector project,N,MinMedThreat,MinSpThreat  data.csv  |
		gawk -F, '{OFS=","; print $0, 100*$(NF)/$(NF-1)}'>  testa 
		for p in  overall $projects
		do	
				grep "$p," testa > relevant
			printf "\n\n----| $p |----------\n\n"
			for n in $ns; do
						echo -n "$n," 
						grep ",$n," relevant | gawk -F, '{print $NF}' | 
							quartile |
							 sort -t, -n +2
			done | malign | sort -t, -n +3
			echo "" 
			echo "n"
			winLossTie --input relevant --fields 6 --perform 6 --key "3" --95 --low
		done   > $Safe/${me}_n_Threat.txt


		demo106selector project,N,MinMedEffort,MinSpEffort  data.csv  |
		gawk -F, '{OFS=","; print $0, 100*$(NF)/$(NF-1)}'>  testa 
		for p in  overall $projects
		do	
				grep "$p," testa > relevant
			printf "\n\n----| $p |----------\n\n"
			for n in $ns; do
						echo -n "$n," 
						grep ",$n," relevant | gawk -F, '{print $NF}' | 
							quartile |
							 sort -t, -n +2
			done | malign | sort -t, -n +3
			echo "" 
			echo "n"
			winLossTie --input relevant --fields 6 --perform 6 --key "3" --95 --low
		done   > $Safe/${me}_n_effort.txt


		demo106selector project,N,MinMedDefects,MinSpDefects  data.csv  |
		gawk -F, '{OFS=","; print $0, 100*$(NF)/$(NF-1)}'>  testa 
		for p in  overall $projects
		do	
				grep "$p," testa > relevant
			printf "\n\n----| $p |----------\n\n"
			for n in $ns; do
						echo -n "$n," 
						grep ",$n," relevant | gawk -F, '{print $NF}' | 
							quartile |
							 sort -t, -n +2
			done | malign | sort -t, -n +3
			echo "" 
			echo "n"
			winLossTie --input relevant --fields 6 --perform 6 --key "3" --95 --low
		done   >  $Safe/${me}_n_Defects.txt


		demo106selector project,N,MinMedMonths,MinSpMonths  data.csv  |
		gawk -F, '{OFS=","; print $0, 100*$(NF)/$(NF-1)}'>  testa 
		for p in  overall $projects
		do	
				grep "$p," testa > relevant
			printf "\n\n----| $p |----------\n\n"
			for n in $ns; do
						echo -n "$n," 
						grep ",$n," relevant | gawk -F, '{print $NF}' | 
							quartile |
							 sort -t, -n +2
			done | malign | sort -t, -n +3
			echo "" 
			echo "n"
			winLossTie --input relevant --fields 6 --perform 6 --key "3" --95 --low
		done   > $Safe/${me}_n_Months.txt

	}
demo106selector() {
	cat $2 |
	gawk -F, -v Want=$1 'BEGIN {
			dd();
			args();
		
	}
	{printf "overall"; for(I=1;I<=N;I++) printf(",%s",$Goals[I]) ; print "";}
	function args( n,tmp) {
		N=split(Want,tmp,/,/);
		for(i=1;i<=N;i++)
			Goals[i]=Dd[tmp[i]]
	}
	function dd() {
	Dd["project"] = 1;
	Dd["policy"] = 2;
	Dd["scoring"] = 3;
	Dd["mutation"] = 4;
	Dd["alpha"] = 5;
	Dd["beta"] = 6;
	Dd["gamma"] = 7;
	Dd["delta"] = 8; 
	Dd["relydefect"] = 9;
	Dd["run"] = 10;
	Dd["N"] = 11;
	Dd["SANum"] = 12;
	Dd["SATime"] = 13;
	Dd["TotalTime"] = 14;
	Dd["minEnergy"] = 15;
	Dd["numPol"] = 16;
	Dd["attNumber"] = 17;
	Dd["FirstMedE"] = 18;
	Dd["FirstSpE"] = 19;
	Dd["FirstMedEffort"] = 20;
	Dd["FirstSpEffort"] = 21;
	Dd["FirstMedDefects"] = 22;
	Dd["FirstSpDefects"] = 23;
	Dd["FirstMedThreat"] = 24;
	Dd["FirstSpThreat"] = 25;
	Dd["FirstMedMonths"] = 26;
	Dd["FirstSpMonths"] = 27;
	Dd["MinMedE"] = 28;
	Dd["MinSpE"] = 29;
	Dd["MinMedEffort"] = 30
	Dd["MinSpEffort"] = 31;
	Dd["MinMedDefects"] = 32;
	Dd["MinSpDefects"] = 33;
	Dd["MinMedThreat"] = 34;
	Dd["MinSpThreat"] = 35;
	Dd["MinMedMonths"] = 36;
	Dd["MinSpMonths"] = 37;
	} '
}


#please add columns for:
#a1) the #of decisions required to reach minimum point
#a2) the number of variables in "a1". e.g. if "a1"= acap=hi and
#acap=lo then "a2" is only "1".
#b) the max possible energy (which is always, 1, right?)
#c) the min energy reached during SA (so we can see how well our
#policies do)
#d) bore vs energy scoring
#e) number of runs in the SA
#f) number of runs for each point in the back select
#g) sa runtime
#h) total run time (only the "C" not the shell scripts)
#i) policy: all, strategic, tactical, hohin's 8 different ideas.
#j) spreadE/medianE
#i) spreadE and medianE see at the FIRST step of the back select
#
#have we got the ttests going to allow early stopping? that would
#effect (a)
#
#have we got those new threat tables going so we can avoid dumb ass
#mistakes like high tool and low acap?
#
#what else? we want to say
#- that we can do well with a few decision ("a1" and "a2" and "i")
#- that the spread of the final results is very small (j)
#- that sa is an adequate (if "c" is very low);
#- that back select is adequate (medianE/"c")
#- that bore is good (that's "d")
#- that smaller runs are as good as larger runs ("e" and "f")
#- that our tool is fast "g"
#- that our "do anything policies" is as good as anything "hohin"
#offers ("i")
#}
#          oner   nb     j48
#auto       56.6   60.4   85.9*
#diabetes   57.2   68.5   69.3*
# 
#demo10() {
#	demo9 | gawk -F, '/@/   {next} 
#	                  NF>1  {print $NF}' | sort | uniq -c
#}
#demo11() {
#	setup; cd $Tmp
#   	demo9 > data.arff
#
#	c=0.1
#	printf "confidence limit for pruning = $c (very selective)\n\n"
#	j4810c data.arff $c  | report 0 3,18,16
#
#	c=0.25
#	printf "confidence limit for pruning = $c (default, less selective)\n\n"
#	j4810c data.arff $c  | report 0 3,18,16
#	cd $Here
#}
#demo1001() {
#	setUpVars
#	setUpDirs
#	setUpSeds
#	prep
#	cd $Tmp
#	pwd
#	makeshare
#	worker1001 > log
#	cp log $Safe/demo1.log
#	winLossTie log | tee $Safe/demo1.winLossTie
#}
#demo1002() {
#	setUpVars
#	setUpDirs
#	setUpSeds
#	prep
#	cd $Tmp
#	pwd
#	makeshare
#	Learners="j48 jrip oner nb aode"
#	worker1002 > log
#	cp log $Safe/demo1.log
#	winLossTie log | tee $Safe/demo1.winLossTie
#}
#### start up
setup
build
blabln "OurMine version v0.2 (alpha) (c)2007 tim@menzies.us under GPLv3"
blabln "Too many doings, not enough learnings.\n"