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lib/AI/NeuralNet/SOM/Rect.pm  view on Meta::CPAN

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

sub bmu {
    my $self = shift;
    my $sample = shift;

    my $closest;                                                               # [x,y, distance] value and co-ords of closest match
    for my $x (0 .. $self->{_X}-1) {
        for my $y (0 .. $self->{_Y}-1){
	    my $distance = AI::NeuralNet::SOM::Utils::vector_distance ($self->{map}->[$x]->[$y], $sample);   # || Vi - Sample ||
#warn "distance to $x, $y : $distance";
	    $closest = [0,  0,  $distance] unless $closest;
	    $closest = [$x, $y, $distance] if $distance < $closest->[2];
	}
    }
    return @$closest;
}


sub neighbors {                                                               # http://www.ai-junkie.com/ann/som/som3.html
    my $self = shift;
    my $sigma = shift;
    my $X     = shift;
    my $Y     = shift;     

    my @neighbors;
    for my $x (0 .. $self->{_X}-1) {
        for my $y (0 .. $self->{_Y}-1){
            my $distance = sqrt ( ($x - $X) * ($x - $X) + ($y - $Y) * ($y - $Y) );
	    next if $distance > $sigma;
	    push @neighbors, [ $x, $y, $distance ];                                    # we keep the distances
	}
    }
    return \@neighbors;
}

=pod

=cut

sub radius {
    my $self = shift;
    return $self->{_R};
}

=pod

=over

=item I<map>

I<$m> = I<$nn>->map

This method returns the 2-dimensional array of vectors in the grid (as a reference to an array of
references to arrays of vectors). The representation of the 2-dimensional array is straightforward.

Example:

   my $m = $nn->map;
   for my $x (0 .. 5) {
       for my $y (0 .. 4){
           warn "vector at $x, $y: ". Dumper $m->[$x]->[$y];
       }
   }

=cut

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

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

=pod

=item I<as_data>

print I<$nn>->as_data

This methods creates a string containing the raw vector data, row by
row. This can be fed into gnuplot, for instance.

=cut

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 .= sprintf "\n";
	}