AI-NeuralNet-FastSOM

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FastSOM.h  view on Meta::CPAN

 *                               \--Vector---+---NV
 *                                            \--NV
 * 
 * References
 * ==========
 * 
 * Each of Rect, Map, Array, and Vector contains a member 'ref' which is
 * an SV* pointing to an RV. The RV can be returned directly to perl-land
 * after being blessed into its respective class.
 * 
 * The RV references an SV containing an IV. The IV is set to the base
 * address of its component structure. This is so the class code can know
 * which instance of the class is being referred to on callback.
 * 
 * The reference count of the SV has its initial reference count set to one,
 * representing its parents ownership. If a parent dies or a perl-land
 * reference is taken of any componenet, its reference count should
 * be adjusted accordingly.
 * 
 * When the count reaches zero perl will call the classes DESTROY method,
 * at which point we can decrease the reference count on each child and
 * free the component structure.
 * 
 * The intent of all this reference count tom-foolery is to keep the
 * component structures from disappearing from underneath perl-land

t/orig/som.t  view on Meta::CPAN

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

{
    use AI::NeuralNet::FastSOM::Rect;    # any non-abstract subclass should do
    my $nn = new AI::NeuralNet::FastSOM::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');
    $nn->label ( 1, 1, 'rumsti' );
    is ($nn->label ( 1, 1), 'rumsti', 'label set/get');

    is ($nn->label ( 1, 0), undef, 'label set/get');
}

{
    my $nn = new AI::NeuralNet::FastSOM::Rect (output_dim => "5x6",
					   input_dim  => 3);
    $nn->initialize;

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

    my $me = $nn->mean_error (@vs);

t/orig/torus.t  view on Meta::CPAN

    is ($nn->{_Y}, 6, 'Y');
    is ($nn->{_Z}, 3, 'Z');
    is ($nn->radius, 2.5, 'radius');
    is ($nn->output_dim, "5x6", 'output dim');
}

{
    my $nn = new AI::NeuralNet::FastSOM::Torus (output_dim => "5x6",
					    input_dim  => 3);

    ok (eq_set ( $nn->neighbors (1, 0, 0),
		   [
		    [ 0, 0, '0' ],
		    [ 0, 1, '1' ],
		    [ 0, 5, '1' ],
		    [ 1, 0, '1' ],
		    [ 4, 0, '1' ]
		   ]), 'neighbors 4+1');

    ok (eq_set ( $nn->neighbors (1, 3, 2),
		   [
		    [ 2, 2, '1' ],
		    [ 3, 1, '1' ],
		    [ 3, 2, '0' ],
		    [ 3, 3, '1' ],
		    [ 4, 2, '1' ]
		   ]), 'neighbors 4+1');
}

{

t/rect.t  view on Meta::CPAN

    ok( $v != $a, 'vector unique' );

    my $v2 = $nn3->map->[0]->[0];
    is( $v, $v2, 'vector eq' );

    my $v3 = $nn2->map->[0][0];
    is( $v, $v3, 'vector shorter' );

    my $m = $nn->map;
    $m->[0][0][0] = 3.245;
    is( $m->[0][0][0], 3.245, 'element set' );
    $m->[0][0][0] = 1.25;
    is( $m->[0][0][0], 1.25, 'element reset' );
    $m->[0][0][1] = 4.8;
    is( $m->[0][0][1], 4.8, 'element set z' );
    $m->[0][0][1] = 2.6;
    is( $m->[0][0][1], 2.6, 'element reset z' );
    $m->[0][1][0] = 8.9;
    is( $m->[0][1][0], 8.9, 'element set y' );
    $m->[0][1][0] = 1.2;
    is( $m->[0][1][0], 1.2, 'element reset y' );
    $m->[1][0][0] = 5.4;
    is( $m->[1][0][0], 5.4, 'element set z' );
    $m->[1][0][0] = 3.23;
    is( $m->[1][0][0], 3.23, 'element reset z');

    $m->[4][5][2] = 2.29;
    is( $m->[4][5][2], 2.29, 'last element set' );
    is( $m->[-1][5][2], 2.29, 'negative x' );
    is( $m->[4][-1][2], 2.29, 'negative y' );
    is( $m->[4][5][-1], 2.29, 'negative z' );
    is( $m->[-1][-1][-1], 2.29, 'negative all' );
}

{
    my $nn = AI::NeuralNet::FastSOM::Rect->new(
        output_dim => '5x6',
        input_dim  => 3

t/som.t  view on Meta::CPAN

    my $nn = AI::NeuralNet::FastSOM::Rect->new(
        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'
    );

# unsupported, for now (rik)
#    $nn->label ( 1, 1, 'rumsti' );
#    is ($nn->label ( 1, 1), 'rumsti', 'label set/get');
#
#    is ($nn->label ( 1, 0), undef, 'label set/get');
}

{
    my $nn = AI::NeuralNet::FastSOM::Rect->new(
        output_dim => "5x6",
        input_dim  => 3,
    );
    $nn->initialize;

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

t/torus.t  view on Meta::CPAN

    is( $nn->output_dim, "5x6", 'output dim' );
}

{
    my $nn = AI::NeuralNet::FastSOM::Torus->new(
        output_dim => "5x6",
        input_dim  => 3,
    );

    ok(
        eq_set(
            $nn->neighbors(1, 0, 0),
            [
                [ 0, 0, '0' ],
                [ 0, 1, '1' ],
                [ 0, 5, '1' ],
                [ 1, 0, '1' ],
                [ 4, 0, '1' ]
            ]
        ),
        'neighbors 4+1'
    );

    ok(
        eq_set(
            $nn->neighbors(1, 3, 2),
            [
                [ 2, 2, '1' ],
                [ 3, 1, '1' ],
                [ 3, 2, '0' ],
                [ 3, 3, '1' ],
                [ 4, 2, '1' ]
            ]
        ),
        'neighbors 4+1'