AI-NeuralNet-Kohonen

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

=head1 CONSTRUCTOR new

Instantiates object fields:

=over 4

=item input_file

A I<SOM_PAK> training file to load. This does not prevent
other input methods (C<input>, C<table>) being processed, but
it does over-ride any specifications (C<weight_dim>) which may
have been explicitly handed to the constructor.

See also L</FILE FORMAT> and L</METHOD load_input>.

=item input

A reference to an array of training vectors, within which each vector
is represented by an array:

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

=back

=cut

sub new {
	my $class					= shift;
	my %args					= @_;
	my $self 					= bless \%args,$class;

	$self->{missing_mask}		= 'x' unless defined $self->{missing_mask};
	$self->_process_table if defined $self->{table};	# Creates {input}
	$self->load_input($self->{input_file}) if defined $self->{input_file};	# Creates {input}
	if (not defined $self->{input}){
		cluck "No {input} supplied!";
		return undef;
	}

	$self->{map_dim_x}			= 19 unless defined $self->{map_dim_x};
	$self->{map_dim_y}			= 19 unless defined $self->{map_dim_y};
	# Legacy from...yesterday
	if ($self->{map_dim}){

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

=cut

sub load_input { my ($self,$path) = (shift,shift);
	local *IN;
	if (not open IN,$path){
		warn "Could not open file <$path>: $!";
		return undef;
	}
	@_ = <IN>;
	close IN;
	$self->_process_input_text(\@_);
	return 1;
}


=head1 METHOD save_file

Saves the map file in I<SOM_PAK> format (see L<METHOD load_input>)
at the path specified in the first argument.

Return C<undef> on failure, a true value on success.

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

	print OUT chr 26;
	close OUT;
	return 1;
}


#
# Process ASCII from table field or input file
# Accepts: ASCII as array or array ref
#
sub _process_input_text { my ($self) = (shift);
	if (not defined $_[1]){
		if (ref $_[0] eq 'ARRAY'){
			@_ = @{$_[0]};
		} else {
			@_ = split/[\n\r\f]+/,$_[0];
		}
	}
	chomp @_;
	my @specs = split/\s+/,(shift @_);
	#- Dimensionality of the vectors (integer, compulsory).

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

	$args{fixed} = $i[$self->{weight_dim}+1] if $i[$self->{weight_dim}+3];
	push @{$self->{input}}, new AI::NeuralNet::Kohonen::Input(%args);

	return 1;
}


#
# Processes the 'table' paramter to the constructor
#
sub _process_table { my $self = shift;
	$_ = $self->_process_input_text( $self->{table} );
	undef $self->{table};
	return $_;
}


__END__
1;

=head1 FILE FORMAT

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

Subsequent lines consist of n floating-point numbers followed by an
optional class label (that can be any string) and two optional
qualifiers (see below) that determine the usage of the corresponding
data entry in training programs.  The data files can also contain an
arbitrary number of comment lines that begin with '#', and are
ignored. (One '#' for each comment line is needed.)

If some components of some data vectors are missing (due to data
collection failures or any other reason) those components should be
marked with 'x'...[in processing, these] are ignored.

...

Each data line may have two optional qualifiers that determine the
usage of the data entry during training. The qualifiers are of the
form codeword=value, where spaces are not allowed between the parts of
the qualifier. The optional qualifiers are the following:

=over 4