File Coverage

blib/lib/AI/NeuralNet/FastSOM/Rect.pm

Criterion	Covered	Total	%
statement	45	49	91.8
branch	1	4	25.0
condition	2	2	100.0
subroutine	7	9	77.7
pod	1	3	33.3
total	56	67	83.5

package AI::NeuralNet::FastSOM::Rect;

use strict;
use warnings;

use AI::NeuralNet::FastSOM;
our @ISA = qw/AI::NeuralNet::FastSOM/;

our $VERSION = '0.19';

sub _old_radius { shift->{_R} }

sub initialize {
    my $self = shift;
    my @data = @_;

    my $i = 0;

    my $get_from_stream = sub {
        $i = 0 if $i > $#data;
        return [ @{ $data[$i++] } ];  # cloning !
    } if @data;

    $get_from_stream ||= sub {
        return [ map { rand( 1 ) - 0.5 } 1..$self->{_Z} ];
    };

    for my $x (0 .. $self->{_X}-1) {
        for my $y (0 .. $self->{_Y}-1) {
            $self->{map}->[$x]->[$y] = &$get_from_stream;
        }
    }
}

sub as_string {
    my $self = shift;
    my $s = '';

    $s .= "    ";
    for my $y (0 .. $self->{_Y}-1){
        $s .= sprintf("   %02d ",$y);
    }
    $s .= "\n" . "-"x107 . "\n";

    my $dim = scalar @{ $self->{map}->[0]->[0] };

    for my $x (0 .. $self->{_X}-1) {
        for my $w ( 0 .. $dim-1 ){
            $s .= sprintf("%02d | ",$x);
            for my $y (0 .. $self->{_Y}-1){
                $s .= sprintf("% 2.2f ", $self->{map}->[$x]->[$y]->[$w]);
            }
            $s .= "\n";
        }
        $s .= "\n";
    }
    return $s;
}

sub as_data {
    my $self = shift;
    my $s = '';

    my $dim = scalar @{ $self->{map}->[0]->[0] };
    for my $x (0 .. $self->{_X}-1) {
        for my $y (0 .. $self->{_Y}-1){
            for my $w ( 0 .. $dim-1 ){
                $s .= sprintf("\t%f", $self->{map}->[$x]->[$y]->[$w]);
            }
            $s .= "\n";
        }
    }
    return $s;
}

1;

__END__