som.h

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/***************************************************************************
 *
 * Authors:     Alberto Pascual Montano (pascual@cnb.csic.es)
 *
 * Unidad de  Bioinformatica of Centro Nacional de Biotecnologia , CSIC
 *
 * 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., 59 Temple Place, Suite 330, Boston, MA
 * 02111-1307  USA
 *
 *  All comments concerning this program package may be sent to the
 *  e-mail address 'xmipp@cnb.csic.es'
 ***************************************************************************/

//-----------------------------------------------------------------------------
// SOM.hh
// Implements Kohonen Self-Organizing Feature Maps
//-----------------------------------------------------------------------------

#ifndef XMIPPSOM_H
#define XMIPPSOM_H

#include "base_algorithm.h"
#include "map.h"

//---------------------------------------------------------------------------
// Class Descent
//---------------------------------------------------------------------------
class Descent
{
public:
    Descent(const double _initial = 1, const double _final = 0)
            : initial(_initial), final(_final)
    {}
    ;

    virtual ~Descent() {}

    virtual double operator()(const unsigned _step, const unsigned _nSteps)
    const;


    virtual void printSelf(std::ostream& _os) const;

    virtual void readSelf(std::istream& _is);

    virtual void saveObject(std::ostream& _os) const;


    virtual void loadObject(std::istream& _is);


    friend std::ostream& operator << (std::ostream& _os, const Descent& _desc)
    {
        _desc.printSelf(_os);
        return _os;
    };

    friend std::istream& operator >> (std::istream& _is, Descent& _desc)
    {
        _desc.readSelf(_is);
        return _is;
    };


protected:
    double initial;
    double final;
};

//---------------------------------------------------------------------------

class SOM : public ClassificationAlgorithm<ClassificationMap>
{
public:
    typedef enum { GAUSSIAN = 0, BUBBLE = 1} neighType;

    SOM(Descent& _alpha, Descent& _radius,  neighType _neighType, unsigned long _nSteps)
            : ClassificationAlgorithm<ClassificationMap>(), somAlpha(_alpha),
              somRadius(_radius), somNeigh(_neighType), somNSteps(_nSteps)
    {}
    ;

    SOM(std::istream& _is);

    virtual ~SOM()
    {}

    SOM(const SOM &)=delete; // Remove default copy constructor because Sonarcloud complains

    void alpha(Descent _alpha);

    void radius(Descent _radius);

    void nSteps(const unsigned long& _nSteps);


    virtual void train(ClassificationMap& _som, ClassicTrainingVectors& _ts) const;

    virtual double test(const ClassificationMap& _som, const TS& _examples) const;


    virtual void clear();

    virtual void printSelf(std::ostream& _os) const;

    virtual void readSelf(std::istream& _is);

    virtual void saveObject(std::ostream& _os) const;


    virtual void loadObject(std::istream& _is);

    friend std::ostream& operator << (std::ostream& _os, const SOM& _som)
    {
        _som.printSelf(_os);
        return _os;
    };

    friend std::istream& operator >> (std::istream& _is, SOM& _som)
    {
        _som.readSelf(_is);
        return _is;
    };


    SOM& operator= (const SOM &op1)
    {
        std::stringstream _str;
        op1.printSelf(_str);
        readSelf(_str);
        return *this;
    }


protected:
    Descent somAlpha;          
    Descent somRadius;         
    neighType somNeigh;       
    unsigned long somNSteps;   

private:
    /*
      * Trains the SOM (never used)
      * Parameter: _som  The som to train
      * Parameter: _ts   The training set
      */
    virtual void train(ClassificationMap& _som, const TS& _ts) const
        {}
    ;
};
#endif