`rm cluster.txt`;
`rm dist.txt`;

# www.datashaping.com/regress.shtml for details

$cluster=0;
&seed(1,1);

$cluster++;
&seed(-25,-25);

&distance();

#--------------------------------------------------------------------
sub distance {


@px=();
@py=();
@pz=();

open (IN,"<cluster.txt");
while ($i=<IN>) {
  $i=~s/\n//g;
  @lu=split(/\t/,$i);
  $px[$k]=$lu[1];
  $py[$k]=$lu[2];
  $pz[$k]=$lu[0];
  $k++;
}
close(IN);
$kmax=$k;

for ($i=0; $i<100; $i++) {
  # pick up 2 points k1, k2
  $k1=int(rand($kmax));
  $k2=int(rand($kmax));
  #compute distance
  $dist=sqrt(($px[$k1]-$px[$k2])**2 + ($py[$k1]-$py[$k2])**2);
  if ($pz[$k1]==$pz[$k2]) { $dclass=0; } else { $dclass=1; }
  print "$dclass\t$dist\n";
  $qdist[$i]=$dist;
  $qclass[$i]=$dclass;
}

open(OUT,">dist.txt");
for ($i=0; $i<100; $i++) {
  print OUT "$qclass[$i]\t$qdist[$i]\n";
}
close(OUT);
}


#--------------------------------------------------------------------
sub seed {

local($x,$y)=@_;

$kmax=1000;

$x=rand($x)-0.5;
$y=rand($y)-0.5;
#print "==$x == $y\n";
for ($k=0; $k<$kmax; $k++) {
  $x=$x+rand($1)-0.5;
  $y=$y+rand($1)-0.5;
  $px[$k]=$x;
  $py[$k]=$y;
  # print "$x === $y\n";
}

open(OUT,">>cluster.txt");
for ($k=0; $k<$kmax; $k++) {
  print OUT "$cluster\t$px[$k]\t$py[$k]\n";
}
close(OUT);

}