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

package AI::NeuralNet::SOM::Hexa;

use strict;
use warnings;

use AI::NeuralNet::SOM;
use Data::Dumper;
use base qw(AI::NeuralNet::SOM);

use AI::NeuralNet::SOM::Utils;

=pod

=head1 NAME

AI::NeuralNet::SOM::Hexa - Perl extension for Kohonen Maps (hexagonal topology)

=head1 SYNOPSIS

  use AI::NeuralNet::SOM::Hexa;
  my $nn = new AI::NeuralNet::SOM::Hexa (output_dim => 6,
                                         input_dim  => 3);
  # ... see also base class AI::NeuralNet::SOM

=head1 INTERFACE

=head2 Constructor

The constructor takes the following arguments (additionally to those in the base class):

=over

=item C<output_dim> : (mandatory, no default)

A positive, non-zero number specifying the diameter of the hexagonal. C<1> creates one with a single
hexagon, C<2> one with 4, C<3> one with 9. The number plays the role of a diameter.

=back

Example:

    my $nn = new AI::NeuralNet::SOM::Hexa (output_dim => 6,
                                           input_dim  => 3);

=cut

sub new {
    my $class = shift;
    my %options = @_;
    my $self = bless { %options }, $class;

    if ($self->{output_dim} > 0) {
	$self->{_D} = $self->{output_dim};
    } else {
	die "output dimension must be positive integer";
    }
    if ($self->{input_dim} > 0) {
	$self->{_Z} = $self->{input_dim};
    } else {
	die "input dimension must be positive integer";
    }

    $self->{_R}      = $self->{_D} / 2;
    $self->{_Sigma0} = $options{sigma0}        || $self->{_R};                                  # impact distance, start value
    $self->{_L0}     = $options{learning_rate} || 0.1;                                       # learning rate, start value

    return $self;