fuzzy_code_book.cpp

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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'
 ***************************************************************************/
//-----------------------------------------------------------------------------
// xmippFuzzyCodeBook.cc
// Implements a set of fuzzy code vectors, that is a Fuzzy code book.
//-----------------------------------------------------------------------------

#include "fuzzy_code_book.h"

FuzzyCodeBook::FuzzyCodeBook(unsigned _n, unsigned _size, unsigned _data,
                   bool _cal): CodeBook(_n, _size, _cal)
{

    // Initialize Fuzzy membership Matrix

    numClusters = _n;
    numVectors = _data;
    memb.resize(numVectors);
    for (unsigned k = 0; k < numVectors; k++)
    {
        std::vector <floatFeature> v;
        v.resize(numClusters, 0);
        memb[k] = v;
    } // for k

}


FuzzyCodeBook::FuzzyCodeBook(unsigned _n, unsigned _size, unsigned _data, double _lower, double _upper,
                   bool _cal): CodeBook(_n, _size, _lower, _upper, _cal)
{

    // Initialize Fuzzy membership Matrix

    numClusters = _n;
    numVectors = _data;
    memb.resize(numVectors);
    for (unsigned k = 0; k < numVectors; k++)
    {
        std::vector <floatFeature> v;
        v.resize(numClusters, 0);
        memb[k] = v;
    } // for k

}

/* Part of this code were developed by Lorenzo Zampighi and Nelson Tang
   of the department of Physiology of the David Geffen School of Medistd::cine,
   University of California, Los Angeles
*/

FuzzyCodeBook::FuzzyCodeBook(unsigned _n, const ClassicTrainingVectors& _ts,
        const bool _use_rand_cvs) : CodeBook(_n, _ts, _use_rand_cvs)
{
    // Initialize Fuzzy membership Matrix

    numClusters = _n;
    numVectors = _ts.size();
    memb.resize(numVectors);
    std::vector <floatFeature> v;
    v.resize(numClusters, 0);
    for (unsigned k = 0; k < numVectors; k++)
    {
        memb[k] = v;
    } // for k
}

FuzzyCodeBook::FuzzyCodeBook(std::istream& _is, const unsigned _size)
{
    readSelf(_is);
    // Initialize Fuzzy membership Matrix

    numClusters = theItems.size();
    numVectors = _size;
    memb.clear();
    memb.resize(numVectors);
    for (unsigned k = 0; k < numVectors; k++)
    {
        std::vector <floatFeature> v;
        v.resize(numClusters, 0);
        memb[k] = v;
    } // for k
}


#ifdef UNUSED // detected as unused 29.6.2018

floatFeature FuzzyCodeBook::membAt(unsigned _di, unsigned _ci) const
{
    std::ostringstream msg;
    if ((_di >= membVectors()) || (_ci >= membClusters()))
    {
        msg << "Out of range. No item at position " << _di << "," << _ci << std::endl;
        throw std::out_of_range(msg.str());
    }

    return memb[_di][_ci];
}
#endif

floatFeature& FuzzyCodeBook::membAt(unsigned _di, unsigned _ci)
{
    std::ostringstream msg;
    if ((_di >= membVectors()) || (_ci >= membClusters()))
    {
        msg << "Out of range. No item at position " << _di << "," << _ci << std::endl;
        throw std::out_of_range(msg.str());
    }

    return memb[_di][_ci];
}


unsigned FuzzyCodeBook::membClusters() const
{
    return numClusters;
}
unsigned FuzzyCodeBook::membVectors() const
{
    return numVectors;
}


FeatureVector& FuzzyCodeBook::fuzzyTest(unsigned _in) const
{
    double maxMemb = 0;
    unsigned best = 0;

    for (unsigned c = 0; c < membClusters(); c++)
    {
        if (maxMemb < memb[_in][c])
        {
            maxMemb = (double) memb[_in][c];
            best = c;
        } //if
    } // for i

    return (FeatureVector&) theItems[best];
}

unsigned FuzzyCodeBook::fuzzyTestIndex(unsigned _in) const
{
    double maxMemb = 0;
    unsigned best = 0;

    for (unsigned c = 0; c < membClusters(); c++)
    {
        if (maxMemb < memb[_in][c])
        {
            maxMemb = (double) memb[_in][c];
            best = c;
        } //if
    } // for i

    return best;
}

#ifdef UNUSED // detected as unused 29.6.2018

Label FuzzyCodeBook::fuzzyApply(unsigned _in) const
{
    return theTargets[fuzzyTestIndex(_in)];
}

void FuzzyCodeBook::fuzzyCalibrate(ClassicTrainingVectors& _ts, Label _def)
{
    // set the default label
    for (std::vector<FeatureVector>::const_iterator i = itemsBegin();
         i < itemsEnd() ; i++)
        theTargets[i - itemsBegin()] = _def;

    if (_ts.calibrated())
    {
        for (unsigned j = 0 ; j < _ts.size() ; j++)
            theTargets[fuzzyTestIndex(j)] = _ts.theTargets[j];
        calibrated(true);
    }
    else
        calibrated(false);
}
#endif

unsigned FuzzyCodeBook::fuzzyWinner(unsigned _in) const
{
    return fuzzyTestIndex(_in);
}

unsigned FuzzyCodeBook::fuzzyOutput(unsigned _in) const
{
    return fuzzyTestIndex(_in);
}


void FuzzyCodeBook::classify(const ClassicTrainingVectors* _ts)
{
    classifVectors.clear(); // clear previous classification.
    classifVectors.resize(size());
    aveDistances.clear(); // clear previous classification.
    aveDistances.resize(size());

    for (unsigned j = 0 ; j < _ts->size() ; j++)
        classifVectors[fuzzyTestIndex(j)].push_back(j);

    for (unsigned i = 0 ; i < size() ; i++)
    {
        double aveDist = 0;
        for (unsigned j = 0 ; j < classifVectors[i].size() ; j++)
            aveDist += euclideanDistance(theItems[i], _ts->theItems[classifVectors[i][j]]);
        if (classifVectors[i].size() != 0)
            aveDist /= (double) classifVectors[i].size();
        aveDistances[i] = (double) aveDist;
    }

}

#ifdef UNUSED // detected as unused 29.6.2018

void FuzzyCodeBook::hardPartition()
{

    for (unsigned k = 1; k < membVectors(); k++)
    {    // Number of input vectors
        double maxMemb = 0;
        unsigned maxIndex = membClusters();         // Impossible cluster index
        for (unsigned i = 0; i < membClusters(); i++)
        { // Number of clusters
            if (maxMemb < memb[k][i])
            {     // Always find the maximum
                if (maxIndex != membClusters())
                    memb[k][maxIndex] = 0.0;    // Previous maximum index set to 0
                maxMemb = memb[k][i];
                maxIndex = i;
                memb[k][i] = 1.0;  // Assume this is the maximum
            }
            else // if maxMemb
                memb[k][i] = 0.0;
        } // for i
    } // for k
}
#endif

FuzzyCodeBook::TS FuzzyCodeBook::alphaCore(TS _ts, double _alpha, unsigned _cluster) const
{
    FuzzyCodeBook::TS _alphaSet(0, _ts.calibrated());

    _alphaSet.theItems.resize(membVectors());
    if (_ts.calibrated())
        _alphaSet.theTargets.resize(membVectors());

    if ((_alpha < 0) || (_alpha > 1))
    {
        std::ostringstream msg;
        msg << "threshold must be in [0,1]";
        throw std::runtime_error(msg.str());
    }

    if ((_cluster < 0) || (_cluster >= membClusters()))
    {
        std::ostringstream msg;
        msg << "Invalid cluster number";
        throw std::runtime_error(msg.str());
    }
    for (unsigned k = 1; k < membVectors(); k++)
    {     // Number of input vectors

        double maxMemb = memb[k][_cluster];
        unsigned maxIndex = _cluster;                 // Impossible cluster index
        for (unsigned i = 0; i < membClusters(); i++)
        {   // Number of clusters
            if (i != _cluster)
                if (maxMemb < memb[k][i])
                {      // Always find the maximum
                    maxMemb = memb[k][i];
                    maxIndex = i;
                }
        } // for i

        if (maxIndex == _cluster && maxMemb >= _alpha)        // If above threshold
            _alphaSet.theItems[k] = _ts.theItems[k];
        if (_ts.calibrated())
            _alphaSet.theTargets[k] =  _ts.theTargets[k];

    } // for k

    return _alphaSet;
}


void FuzzyCodeBook::writeMembership(std::ostream& _os) const
{
    _os << membVectors() << std::endl;
    for (unsigned k = 0; k < numVectors; k++)   // Number of input vectors
        _os << memb[k] << std::endl;
}


void FuzzyCodeBook::readMembership(std::istream& _is)
{
    _is >> numVectors;
    memb.resize(numVectors);
    for (unsigned k = 0; k < numVectors; k++)    // Number of input vectors
        _is >> memb[k];
    numClusters = memb[0].size();
}


void FuzzyCodeBook::saveObject(std::ostream& _os) const
{
    writeMembership(_os);
    CodeBook::saveObject(_os);
}


void FuzzyCodeBook::readSelf(std::istream& _is, const unsigned _size)
{
    CodeBook::readSelf(_is);
    // Initialize Fuzzy membership Matrix
    numClusters = theItems.size();
    numVectors = _size;
    memb.clear();
    memb.resize(numVectors);
    for (size_t k = 0; k < numVectors; k++)
    {
        std::vector <floatFeature> v;
        v.resize(numClusters, 0);
        memb[k] = v;
    } // for k
}



void FuzzyCodeBook::loadObject(std::istream& _is)
{
    clear();
    readMembership(_is);
    CodeBook::loadObject(_is);
}

#ifdef UNUSED // detected as unused 29.6.2018

void FuzzyCodeBook::printDensity(std::ostream& _os) const
{
    _os << "1" << std::endl;
    for (size_t j = 0; j < numClusters; j++)
    {
        double sumDens = 0;
        for (size_t i = 0; i < numVectors; i++)
            sumDens += (double) memb[i][j];
        _os << j << " " << sumDens << std::endl;
    }
}
#endif

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