basic_pca.h

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/***************************************************************************
 *
 * Authors:     Carlos Oscar Sorzano (coss@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'
 ***************************************************************************/
/* This file contains functions related to the SAMPLING Transform */

#ifndef _CORE_BASICPCA_HH
#define _CORE_BASICPCA_HH

#include <vector>
#include "core/multidim_array.h"


class PCAMahalanobisAnalyzer
{
public:
    // Set of images assigned to the class
    std::vector< MultidimArray<float> > v;

    // Set of basis functions
    std::vector< MultidimArray<double> > PCAbasis;

    // The average of the vectors
    MultidimArray<double> avg;

    // Set of basis functions
    MultidimArray<double> Zscore;

    // Indexes to access in a sorted way
    MultidimArray<int> idx;

    // Matrix for the Eigen values
    Matrix1D<double> w;
public:
    inline void clear()
    {
        v.clear();
        PCAbasis.clear();
        Zscore.clear();
        idx.clear();
        avg.clear();
    }

    inline void reserve(int newSize)
    {
        v.reserve(newSize);
    }

    inline void addVector(const MultidimArray<float> &_v)
    {
        v.push_back(_v);
    }

    void computeStatistics(MultidimArray<double> &avg,
                           MultidimArray<double> &stddev);

    void subtractAvg();

    void gramSchmidt();

    void standardarizeVariables();

    void learnPCABasis(size_t NPCA, size_t Niter);

    void projectOnPCABasis(Matrix2D<double> &CtY);

    void reconsFromPCA(const Matrix2D<double> &CtY, std::vector< MultidimArray<float> > &recons);

    void evaluateZScore(int NPCA, int Niter, bool trained=false,
        const char* filename="temp.txt", int numdesc=0);

    inline double getZscore(int n)
    {
        return Zscore(n);
    }

    inline double getSortedZscore(int n)
    {
        return Zscore(idx(n)-1);
    }

    inline int getSorted(int n)
    {
        return idx(n)-1;
    }
};

class PCAonline {
public:
    MultidimArray<double> ysum;
    MultidimArray<double> yxt;
    MultidimArray<double> c1;
    MultidimArray<double> ycentered;
    double zn;
    double xxt;
    int N;
    double maxzn;
public:
    PCAonline();

    void addVector(MultidimArray<double> &y);

    MultidimArray<double> & getCurrentPCA() {
        return c1;
    }

    double getCurrentProjection() {
        return zn;
    }
};
#endif