outputfunction.h

Go to the documentation of this file.

/********************************************************************************
 *  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 OUTPUTFUNCTION_H
#define OUTPUTFUNCTION_H

#include "nnfwconfig.h"
#include <parametersettable.h>
#include <configurationparameters.h>
#include <QRegExp>

namespace farsa {

class FARSA_NNFW_TEMPLATE OutputFunction : public ParameterSettableWithConfigureFunction {
public:
    OutputFunction() : clusterv(NULL), tmp1(1), tmp2(1) { /*nothing to do*/ };
    virtual ~OutputFunction() { /*nothing to do*/ };
    virtual void apply( DoubleVector& inputs, DoubleVector& outputs ) = 0;
    double apply( double input ) {
        tmp1[0] = input;
        apply( tmp1, tmp2 );
        return tmp2[0];
    };
    virtual bool derivate( const DoubleVector& inputs, const DoubleVector& outputs, DoubleVector& derivates ) const {
        Q_UNUSED( inputs );
        Q_UNUSED( outputs );
        Q_UNUSED( derivates );
        return false;
    };
    void setCluster( Cluster* cl ) {
        if ( clusterv != NULL ) throw OutputFunctionSetClusterException();
        clusterv = cl;
        clusterSetted();
    };
protected:
    virtual void clusterSetted() { /* nothing to do */ };
    Cluster* clusterv;
private:
    DoubleVector tmp1;
    DoubleVector tmp2;
};

}

#endif