AI-NeuralNet-SOM

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examples/eigenvector_initialization.pl  view on Meta::CPAN

use strict;
use Data::Dumper;

use AI::NeuralNet::SOM::Rect;

my @vs  = ([ 3, 2, 4 ], [ -1, -1, -1 ], [ 0, 4, -3]);
my $dim = 3;

#my @vs  = ([1,-0.5],    [0,1]);
#my $dim = 2;

my $epsilon = 0.001;

examples/load_save.pl  view on Meta::CPAN

use strict;
use Data::Dumper;

use AI::NeuralNet::SOM::Rect;

{
    my $nn = new AI::NeuralNet::SOM::Rect (output_dim => "5x6",
					   input_dim  => 3);
    $nn->initialize;
    $nn->train (400, ([ 3, 2, 4 ], [ -1, -1, -1 ], [ 0, 4, -3]));

    # now we freeze the thing

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

package AI::NeuralNet::SOM;

use strict;
use warnings;

require Exporter;
use base qw(Exporter);

use Data::Dumper;

=pod

=head1 NAME

AI::NeuralNet::SOM - Perl extension for Kohonen Maps

=head1 SYNOPSIS

  use AI::NeuralNet::SOM::Rect;

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)

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

package AI::NeuralNet::SOM::Rect;

use strict;
use warnings;

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

=pod

=head1 NAME

AI::NeuralNet::SOM::Rect - Perl extension for Kohonen Maps (rectangular topology)

=head1 SYNOPSIS

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

package AI::NeuralNet::SOM::Torus;

use strict;
use warnings;

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

=pod

=head1 NAME

AI::NeuralNet::SOM::Torus - Perl extension for Kohonen Maps (torus topology)

=head1 SYNOPSIS

t/hexa.t  view on Meta::CPAN

#########################

# change 'tests => 1' to 'tests => last_test_to_print';

use Test::More qw(no_plan);
BEGIN { use_ok('AI::NeuralNet::SOM::Hexa') };

######

use Data::Dumper;

{
    my $nn = new AI::NeuralNet::SOM::Hexa (output_dim => 6,
					   input_dim  => 3);
    ok ($nn->isa ('AI::NeuralNet::SOM::Hexa'), 'class');
    is ($nn->{_R}, 3, 'R');
    is ($nn->radius, 3, 'radius');
}

{

t/rect.t  view on Meta::CPAN

#########################

# change 'tests => 1' to 'tests => last_test_to_print';

use Test::More qw(no_plan);
BEGIN { use_ok('AI::NeuralNet::SOM::Rect') };

######
use Data::Dumper;

{
    my $nn = new AI::NeuralNet::SOM::Rect (output_dim => "5x6",
					   input_dim  => 3);
    ok ($nn->isa ('AI::NeuralNet::SOM::Rect'), 'class');
    is ($nn->{_X}, 5, 'X');
    is ($nn->{_Y}, 6, 'Y');
    is ($nn->{_Z}, 3, 'Z');
    is ($nn->radius, 2.5, 'radius');
    is ($nn->output_dim, "5x6", 'output dim');

t/som.t  view on Meta::CPAN

#########################

# Change 'tests => 1' to 'tests => last_test_to_print';

use Test::More qw(no_plan);
BEGIN { use_ok('AI::NeuralNet::SOM') };

######
use Data::Dumper;

{
    use AI::NeuralNet::SOM::Rect;    # any non-abstract subclass should do
    my $nn = new AI::NeuralNet::SOM::Rect (output_dim => "5x6",
					   input_dim  => 3,
					   );
    $nn->value ( 1, 1, [ 1, 1, 1 ] );
    ok (eq_array ($nn->value ( 1, 1),
		  [ 1, 1, 1 ]), 'value set/get');
    $nn->label ( 1, 1, 'rumsti' );

t/torus.t  view on Meta::CPAN

#########################

# change 'tests => 1' to 'tests => last_test_to_print';

use Test::More qw(no_plan);
BEGIN { use_ok('AI::NeuralNet::SOM::Torus') };

######
use Data::Dumper;

{
    my $nn = new AI::NeuralNet::SOM::Torus (output_dim => "5x6",
					    input_dim  => 3);
    ok ($nn->isa ('AI::NeuralNet::SOM::Torus'), 'class');
    is ($nn->{_X}, 5, 'X');
    is ($nn->{_Y}, 6, 'Y');
    is ($nn->{_Z}, 3, 'Z');
    is ($nn->radius, 2.5, 'radius');
    is ($nn->output_dim, "5x6", 'output dim');

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