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#					added NNFlex::datasets
#
# 0.12 20050116		CColbourn	Fixed reinforce.pm bug
# 					Added call into datasets
#					in ::run to offer alternative
#					syntax
#
# 0.13 20050121		CColbourn	Created momentum learning module
#
# 0.14 20050201		CColbourn	Abstracted derivatiive of activation
#					function into a separate function call
#					instead of hardcoded 1-y*y in backprop
#					tanh, linear & momentum
#
# 0.15 20050206		CColbourn	Fixed a bug in feedforward.pm. Stopped
#					calling dbug unless scalar debug > 0
#					in a lot of calls
#
# 0.16 20050218		CColbourn	Changed from a hash of weights to an
# 					array of weights, to make it easier
# 					to adapt the code to PDL
#
# 0.17 20050302		CColbourn	Changed input params to ::output to
#					be param=>parameter not anon hash
#					Included round parameter in output
#
# 0.20 20050307		CColbourn	Modified for inheritance to simplify
#					future network types
#
# 0.21 20050316		CColbourn	Rewrote perldocs, implemented fahlman
#					constant, chopped out old legacy stuff
#					put math functions in mathlib, etc etc
#
# 0.22 20050317		CColbourn	Implemented ::connect method
#
# 0.23 20050424		CColbourn	Included Hopfield module in dist.
#
# 0.24 20050620		CColbourn	Corrected a bug in the bias weight
#					calculation
#
#
###############################################################################
# ToDo
# ====
#
# Modify init to allow recurrent layer/node connections
# write cmd & gui frontends
# Speed the bugger up!
#
# Odd thought - careful coding of a network would allow grafting of
# two different network types or learning algorithms, like an effectve
# single network with 2 layers unsupervised and 2 layers supervised
#
# Clean up the perldocs
#
###############################################################################
$VERSION = "0.24";


###############################################################################
my @DEBUG; 	# a single, solitary, shameful global variable. Couldn't
		#avoid it really. It allows correct control of debug
		#information before the $network object is created
		# (in ::layer->new & ::node->new for  example).


###############################################################################
###############################################################################
# package NNFlex
###############################################################################
###############################################################################
package AI::NNFlex;
use AI::NNFlex::Mathlib;
use base qw(AI::NNFlex::Mathlib);





###############################################################################
# AI::NNFlex::new
###############################################################################
sub new
{
	my $class = shift;
	my $network={};
	bless $network,$class;

	# intercept the new style 'empty network' constructor call
	# Maybe I should deprecate the old one, but its convenient, provided you
	# can follow the mess of hashes
	
	if (!grep /HASH/,@_)
	{
		my %config = @_;
		foreach (keys %config)
		{
			$network->{$_} = $config{$_};
		}

		return $network;
	}

	# Otherwise, continue assuming that the whole network is defined in 
	# a pair of anonymous hashes	



	my $params = shift;
	my $netParams = shift;
	my @layers;
	dbug ($netParams,"Entered AI::NNFlex::new with params $params $netParams",2);


	# clean up case & spaces in layer defs from pre 0.14 constructor calls:
	my $cleanParams;
	foreach my $layer(@{$params})
	{
		my %cleanLayer;
		foreach (keys %$layer)
		{