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#		}
#	}
#	if ($#neurons < $#neuronweights) {
#		foreach my $i ($#neurons+1..$#neuronweights) {
#			$neurons[$i]=0;
#		}
#	}
#print STDERR $self->{'id'}."\n";
#print STDERR join(',', @inputs)."\n";
#print STDERR join(',', @neurons)."\n";
#print STDERR join(',', @inputweights)."\n";
#print STDERR join(',', @neuronweights)."\n";
	my $output = 0;
	if ($self->{'inline_c'}) {
		$output = _execute_internals( \@inputs, \@neurons, \@inputweights, \@neuronweights );
	} else {
		foreach my $id (0..$#inputweights) {
			$output += ($inputweights[$id] || 0 ) * ($inputs[$id] || 0);
		}
		foreach my $id (0..$#neuronweights) {
			$output += ($neuronweights[$id] || 0) * ($neurons[$id] || 0);
		}
	}
	return $output;
}

__PACKAGE__->meta->make_immutable;

1;


__END__
=pod

=head1 NAME

AI::ANN::Neuron - a neuron for an artificial neural network simulator

=head1 VERSION

version 0.008

=head1 METHODS

=head2 new

AI::ANN::Neuron->new( $neuronid, {$inputid => $weight, ...}, {$neuronid => $weight} )

Weights may be whatever the user chooses. Note that packages that use this 
one may place their own restructions. Neurons and inputs are assumed to be 
zero-indexed.

eta_inputs and eta_neurons are optional, required only if you wish to use the 
Gaussian mutation in AI::ANN::Evolver.

=head2 ready

$neuron->ready( [$input0, $input1, ...], [$neuronvalue0, ...] )

All inputs must be provided or you're insane.
If a neuron is not yet available, make it undef, not zero.
Returns 1 if ready, 0 otherwise.

=head2 execute

$neuron->execute( [$input0, $input1, ...], {$neuronid => $neuronvalue, ...} )

You /must/ pass the correct number of inputs and neurons, and undefined values
    /must/ be zeros, not undef.
Returns raw value (linear potential)

=head1 AUTHOR

Dan Collins <DCOLLINS@cpan.org>

=head1 COPYRIGHT AND LICENSE

This software is Copyright (c) 2011 by Dan Collins.

This is free software, licensed under:

  The GNU General Public License, Version 3, June 2007

=cut