backpropagationalgo.h

/********************************************************************************
 *  Neural Network Framework.                                                   *
 *  Copyright (C) 2005-2011 Gianluca Massera <emmegian@yahoo.it>                *
 *                                                                              *
 *  This program is free software; you can redistribute it and/or modify        *
 *  it under the terms of the GNU General Public License as published by        *
 *  the Free Software Foundation; either version 2 of the License, or           *
 *  (at your option) any later version.                                         *
 *                                                                              *
 *  This program is distributed in the hope that it will be useful,             *
 *  but WITHOUT ANY WARRANTY; without even the implied warranty of              *
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the               *
 *  GNU General Public License for more details.                                *
 *                                                                              *
 *  You should have received a copy of the GNU General Public License           *
 *  along with this program; if not, write to the Free Software                 *
 *  Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA  *
 ********************************************************************************/

#ifndef BACKPROPAGATIONALGO_H
#define BACKPROPAGATIONALGO_H

#include "nnfwconfig.h"
#include "learningalgorithm.h"
#include "biasedcluster.h"
#include "matrixlinker.h"
#include <QMap>
#include <QVector>

namespace farsa {

class FARSA_NNFW_API BackPropagationAlgo : public LearningAlgorithm {
public:
    BackPropagationAlgo( NeuralNet *n_n, UpdatableList update_order, double l_r = 0.1 );
    BackPropagationAlgo();

    ~BackPropagationAlgo( );

    void setUpdateOrder( const UpdatableList& update_order );
    
    UpdatableList updateOrder() const {
        return update_order;
    };
    void setTeachingInput( Cluster* output, const DoubleVector& ti );

    virtual void learn();

    virtual void learn( const Pattern& );

    virtual double calculateMSE( const Pattern& );

    void setRate( double newrate ) {
        learn_rate = newrate;
    };

    double rate() const {
        return learn_rate;
    };

    void setMomentum( double newmom ) {
        momentumv = newmom;
    };

    double momentum() const {
        return momentumv;
    };

    void enableMomentum();

    void disableMomentum() {
        useMomentum = false;
    };

    DoubleVector getError( Cluster* );
    virtual void configure(ConfigurationParameters& params, QString prefix);
    virtual void save(ConfigurationParameters& params, QString prefix);
    static void describe( QString type );
protected:
    virtual void neuralNetChanged();
private:
    double learn_rate;
    double momentumv;
    double useMomentum;
    UpdatableList update_order;

    class FARSA_NNFW_API cluster_deltas {
    public:
        BiasedCluster* cluster;
        bool isOutput;
        DoubleVector deltas_outputs;
        DoubleVector deltas_inputs;
        DoubleVector last_deltas_inputs;
        QList<MatrixLinker*> incoming_linkers_vec;
        QVector<DoubleVector> incoming_last_outputs;
    };
    QMap<Cluster*, int> mapIndex;
    QVector<cluster_deltas> cluster_deltas_vec;
    // --- propagate delta through the net
    void propagDeltas();
    // --- add a Cluster into the structures above
    void addCluster( Cluster*, bool );
    // --- add a Linker into the structures above
    void addLinker( Linker* );

};

}

#endif