#! perl -slw
use strict;
use Data::Dump qw[ pp ];
use List::Util qw[ reduce ];
use GD;

use constant {
    WHITE => 16777215,
    MinX => 10.318842, MaxX => 14.124424,
    MinY => 21.097507, MaxY => 24.912207,
};
use constant {
    SpanX => MaxX - MinX, SpanY => MaxY - MinY,
};

sub rgb2n{ unpack 'N', pack 'CCCC', 0, @_ }
sub n2rgb{ unpack 'xCCC', pack 'N', $_[0] }

our $POINTS ||= 300_000;

my @points = map [ MinX + rand( SpanX ), MinY + rand( SpanY ) ], 1 .. $POINTS;

## Normalise to our grid, scale by 1000 and integerise
my @scaled = map [
    int( ( $_->[ 0 ] - MinX ) * 1000 ),
    int( ( $_->[ 1 ] - MinY ) * 1000 ),
], @points;

my( $sizeX, $sizeY ) = ( int( SpanX * 1000 ), int( SpanY * 1000 ) );
my $img = GD::Image->new( $sizeX, $sizeY , 1 );
$img->filledRectangle( 0, 0, $sizeX, $sizeY, rgb2n( 255, 255, 255 ) );


my %groups;
for my $i ( 0 .. $#scaled ) {
    my $color = $img->getPixel( @{ $scaled[ $i ] } );
    if( $color != WHITE ) {
        push @{ $groups{ $color } }, $i;
    }
    else {
        $color = $i;
    }
    $img->filledEllipse( @{ $scaled[ $i ] }, 20, 20, $i );
}

## Save the image showing all points/circles
open IMG, '>:raw', '694790all.png' or die $!;
print IMG $img->png;
close IMG;
system 1, '694790all.png';

undef $img;

## Produce a file of clusters of points
open OUT, '>', '694790.groups' or die $!;
for my $key ( sort { $a <=> $b } keys %groups ) {
    print OUT "[ @{ $points[ $_ ] } ]" for $key, @{ $groups{ $key } };
    print OUT "------";
}
close OUT;

## Produce second image showing just the clustered points.
$img = GD::Image->new( $sizeX, $sizeY , 1 );
$img->filledRectangle( 0, 0, $sizeX, $sizeY, rgb2n( 255, 255, 255 ) );

for my $key ( sort { $a <=> $b } keys %groups ) {
    $img->filledEllipse( @{ $scaled[ $key ] }, 20, 20, $key );
    $img->filledEllipse( @{ $scaled[ $_ ] }, 20, 20, $key ) for @{ $groups{ $key } };
}

open IMG, '>:raw', '694790grouped.png' or die $!;
print IMG $img->png;
close IMG;
system 1, '694790grouped.png';


__END__
Latitude stats:
Minimum: 10.318842
Maximum: 14.124424
Mean: 11.24719
Standard Deviation: 0.805771


Longitude stats:
Minimum: 21.097507
Maximum: 24.912207
Mean: 22.474358
Standard Deviation: 0.974835