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print I<$nn>->as_string

This methods creates a pretty-print version of the current vectors.

=cut

sub as_string { die; }

=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 { die; }

=pod

=back

=head1 HOWTOs

=over

=item I<using Eigenvectors to initialize the SOM>

See the example script in the directory C<examples> provided in the
distribution. It uses L<PDL> (for speed and scalability, but the
results are not as good as I had thought).

=item I<loading and saving a SOM>

See the example script in the directory C<examples>. It uses
C<Storable> to directly dump the data structure onto disk. Storage and
retrieval is quite fast.

=back

=head1 FAQs

=over

=item I<I get 'uninitialized value ...' warnings, many of them>

There is most likely something wrong with the C<input_dim> you
specified and your vectors should be having.

=back

=head1 TODOs

=over

=item maybe implement the SOM on top of PDL?

=item provide a ::SOM::Compat to have compatibility with the original AI::NeuralNet::SOM?

=item implement different window forms (bubble/gaussian), linear/random

=item implement the format mentioned in the original AI::NeuralNet::SOM

=item add methods as_html to individual topologies

=item add iterators through vector lists for I<initialize> and I<train>

=back

=head1 SUPPORT

Bugs should always be submitted via the CPAN bug tracker 
L<https://rt.cpan.org/Dist/Display.html?Status=Active&Queue=AI-NeuralNet-SOM>

=head1 SEE ALSO

Explanation of the algorithm:

L<http://www.ai-junkie.com/ann/som/som1.html>

Old version of AI::NeuralNet::SOM from Alexander Voischev:

L<http://backpan.perl.org/authors/id/V/VO/VOISCHEV/>

Subclasses:

L<AI::NeuralNet::Hexa>
L<AI::NeuralNet::Rect>
L<AI::NeuralNet::Torus>


=head1 AUTHOR

Robert Barta, E<lt>rho@devc.atE<gt>

=head1 COPYRIGHT AND LICENSE

Copyright (C) 200[78] by Robert Barta

This library is free software; you can redistribute it and/or modify
it under the same terms as Perl itself, either Perl version 5.8.8 or,
at your option, any later version of Perl 5 you may have available.

=cut

our $VERSION = '0.07';

1;

__END__


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

    my $closest;                                                               # [x,y, distance] value and co-ords of closest match
    foreach my $coor ($self->_get_coordinates) {                               # generate all coord pairs, not overly happy with that
	my ($x, $y) = @$coor;
	my $distance = _vector_distance ($self->{map}->[$x]->[$y], $sample);   # || Vi - Sample ||
	$closest = [0,  0,  $distance] unless $closest;
	$closest = [$x, $y, $distance] if $distance < $closest->[2];