STK_DiagGaussianParameters.h

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/*--------------------------------------------------------------------*/
/*     Copyright (C) 2004-2016 Serge Iovleff
 
    This program is free software; you can redistribute it and/or modify
    it under the terms of the GNU Lesser 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 Lesser General Public License for more details.
 
    You should have received a copy of the GNU Lesser 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
 
    Contact : S..._DOT_I..._AT_stkpp.org (see copyright for ...)
*/
 
/*
 * Project:  stkpp::Clustering
 * created on: Oct 24, 2013
 * Author:   Serge Iovleff
 **/
 
#ifndef STK_DIAGGAUSSIANPARAMETERS_H
#define STK_DIAGGAUSSIANPARAMETERS_H
 
#include "../STK_Clust_Util.h"
 
#include <Arrays/include/STK_Array1D.h>
#include <Arrays/include/STK_CArray.h> // for Gaussian_sksj model
#include <Arrays/include/STK_CArrayPoint.h>
#include <Arrays/include/STK_CArrayVector.h>
 
#include <STatistiK/include/STK_Stat_Online.h>
#include <STatistiK/include/STK_Stat_Functors.h>
 
namespace STK
{
 
template<>
struct ModelParameters<Clust::Gaussian_sjk_>
{
  Array1D<CPointX> mean_;
  Array1D<CPointX> sigma_;
  Array1D< Stat::Online<CPointX, Real> > stat_mean_;
  Array1D< Stat::Online<CPointX, Real> > stat_sigma_;
 
  ModelParameters(int nbCluster);
  ModelParameters( ModelParameters const& param);
  ~ModelParameters();
  ModelParameters& operator=( ModelParameters const& param);
 
  inline Real const& mean(int k, int j) const { return mean_[k][j];}
  inline Real const& sigma(int k, int j) const { return sigma_[k][j];}
 
  void resize(Range const& range);
 
  void updateStatistics();
  void setStatistics();
  void releaseStatistics();
 
  template<class Array>
  void setParameters( ExprBase<Array> const& params)
  {
    for(int k=mean_.begin(), kp= params.beginRows(); k<mean_.end(); ++k, kp+=2)
    {
      mean_[k] = params.row(kp);
      sigma_[k] = params.row(kp+1);
    }
  }
};
 
template<>
struct ModelParameters<Clust::Gaussian_sk_>
{
  Array1D<CPointX> mean_;
  Array1D<Real> sigma_;
  Array1D< Stat::Online<CPointX, Real> > stat_mean_;
  Array1D< Stat::Online<Real, Real> > stat_sigma_;
 
  ModelParameters(int nbCluster);
  ModelParameters( ModelParameters const& param);
  ~ModelParameters();
  ModelParameters& operator=( ModelParameters const& param);
 
  inline Real const& mean(int k, int j) const { return mean_[k][j];}
  inline Real const& sigma(int k, int j) const { return sigma_[k];}
 
  void resize(Range const& range);
 
  void updateStatistics();
  void setStatistics();
  void releaseStatistics();
 
  template<class Array>
  void setParameters( ExprBase<Array> const& params)
  {
    for(int k=mean_.begin(), kp= params.beginRows(); k<mean_.end(); ++k, kp+=2)
    {
      mean_[k] = params.row(kp);
      sigma_[k] = params.row(kp+1).mean();
    }
  }
};
 
template<>
struct ModelParameters<Clust::Gaussian_sj_>
{
  Array1D<CPointX> mean_;
  CPointX sigma_;
  Array1D< Stat::Online<CPointX, Real> > stat_mean_;
  Stat::Online<CPointX, Real> stat_sigma_;
 
  ModelParameters(int nbCluster);
  ModelParameters( ModelParameters const& param);
  ~ModelParameters();
  ModelParameters& operator=( ModelParameters const& param);
 
  inline Real const& mean(int k, int j) const { return mean_[k][j];}
  inline Real const& sigma(int k, int j) const { return sigma_[j];}
 
  void resize(Range const& range);
 
  void updateStatistics();
  void setStatistics();
  void releaseStatistics();
 
  template<class Array>
  void setParameters( ExprBase<Array> const& params)
  {
    sigma_ =0.;
    for(int k=mean_.begin(), kp= params.beginRows(); k<mean_.end(); ++k, kp+=2)
    {
      mean_[k] = params.row(kp);
      sigma_ += params.row(kp+1);
    }
    sigma_ /= mean_.size();
  }
};
 
template<>
struct ModelParameters<Clust::Gaussian_s_>
{
  Array1D<CPointX> mean_;
  Real sigma_;
  Array1D< Stat::Online<CPointX, Real> > stat_mean_;
  Stat::Online<Real, Real> stat_sigma_;
 
  ModelParameters(int nbCluster);
  ModelParameters( ModelParameters const& param);
  ~ModelParameters();
  ModelParameters& operator=( ModelParameters const& param);
 
  inline Real const& mean(int k, int j) const { return mean_[k][j];}
  inline Real const& sigma(int k, int j) const { return sigma_;}
 
  void resize(Range const& range);
 
  void updateStatistics();
  void setStatistics();
  void releaseStatistics();
 
  template<class Array>
  void setParameters( ExprBase<Array> const& params)
  {
    sigma_ =0.;
    for(int k=mean_.begin(), kp= params.beginRows(); k<mean_.end(); ++k, kp+=2)
    {
      mean_[k] = params.row(kp);
      sigma_ += params.row(kp+1).mean();
    }
    sigma_ /= mean_.size();
  }
};
 
template<>
struct ModelParameters<Clust::Gaussian_sjsk_>
{
    Array1D<CPointX> mean_;
    CVectorX sigmak_;
    CPointX sigmaj_;
    Array1D< Stat::Online<CPointX, Real> > stat_mean_;
    Stat::Online<Real, Real> stat_sigmak_;
    Stat::Online<CPointX, Real> stat_sigmaj_;
 
    ModelParameters(int nbCluster);
    ModelParameters( ModelParameters const& param);
    ~ModelParameters();
 
    inline Real const& mean(int k, int j) const { return mean_[k][j];}
    inline Real sigma(int k, int j) const { return sigmak_[k] * sigmaj_[j];}
 
    void resize(Range const& range);
 
    void updateStatistics();
    void setStatistics();
    void releaseStatistics();
 
    template<class Array>
    void setParameters( ExprBase<Array> const& params)
    {
      CArrayXX sigma(mean_.range(), params.cols());
      for(int k=mean_.begin(), kp= params.beginRows(); k<mean_.end(); ++k, kp+=2)
      {
          mean_[k]     = params.row(kp);
          sigma.row(k) = params.row(kp+1);
      }
      sigmak_ = Stat::meanByRow(sigma.asDerived());
      sigmaj_ = Stat::meanByCol(sigma.asDerived());
      Real cte = std::sqrt((sigma/(sigmak_ * sigmaj_)).mean());
      sigmak_ *= cte;
      sigmaj_ *= cte;
    }
};
 
} // namespace STK
 
#endif /* STK_DIAGGAUSSIANPARAMETERS_H */