softDecSimilarityCompAnalysis.h

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#ifndef SOFT_DECISION_SIMILAR_COMPONENT_H
#define SOFT_DECISION_SIMILAR_COMPONENT_H

#include <aims/data/data.h>
#include <vector>
#include <string.h>


class SoftDecisionSimilarComponent
{
public:
  SoftDecisionSimilarComponent( int nbClasses, int nbVar ) ;
  ~SoftDecisionSimilarComponent() ;

  void init( ) ;
  
  double doIt( const AimsData<float>& indivMatrix ) ;
  
  const AimsData<double>& getRnk() const 
  {
    return _Rnk ;
  }
  
  std::vector<short> getSegmentationResult() const 
  {
    if( (!_isInit) || _An.size() == 0 )
      throw std::runtime_error( "Should doIt before getting result !" ) ;
    
    std::vector<short> segRes( _nbInd ) ;
    
    for( int ind = 0 ; ind < _nbInd ; ++ind ){
      if( _valids[ind ] ){
        short bestClass = 0 ;
        for( int k = 1 ; k < _nbClasses ; ++k ){
          if( _Rnk(ind, k) > _Rnk(ind, bestClass) )
            bestClass = k ;
        }
      
        segRes[ind] = bestClass ;
      } else
        segRes[ind] = -1 ;
    }
    
    return segRes ;
  }
  
private:
  int _nbClasses ;
  int _nbVar ;
  int _nbInd ;
  bool _isInit ;
  int _corrNbInd ;
  
  std::vector<short> _labels ;
  std::vector<bool> _valids ;
  
  double lnLikelyhood( const AimsData<float>& indivMatrix ) ;
  void expectationStep( const AimsData<float>& indivMatrix ) ;
  void maximisationStep( const AimsData<float>& indivMatrix ) ;

  bool stopCriterion( double threshold ) ;

  inline double similarity( const AimsData<float>& indivMatrix, int ind, int k ) ;
  inline double projection( const AimsData<float>& indivMatrix, int ind, int k, 
                            const AimsData<double>& newek ) ;
  std::vector<double> _pk ; // class weight
  std::vector< AimsData<double> > _ek ; // class mean normalized vect
  std::vector<double> _An ;
  std::vector<double> _newpk ; // class weight
  std::vector< AimsData<double> > _newek ; // class mean normalized vect
  std::vector<double> _newAn ;

  AimsData<double> _Rnk ; // posterior proba of classes regarding to data
} ;

double 
SoftDecisionSimilarComponent::similarity( const AimsData<float>& indivMatrix, int ind, int k )
{
  double norm = 0., sim = 0. ;
  for( int t = 0 ; t < _nbVar ; ++t ){
    norm += indivMatrix( ind, t ) * indivMatrix( ind, t ) ;
    sim += indivMatrix( ind, t ) * _ek[k](t) ;
  }
  if( norm <= 0. )
    return 0. ;
  return sim / sqrt(norm) ;
}

double 
SoftDecisionSimilarComponent::projection( const AimsData<float>& indivMatrix,
                                          int ind, int /* k */,
                                          const AimsData<double>& newek )
{
  double proj = 0. ;
  for( int t = 0 ; t < _nbVar ; ++t ){
    proj += indivMatrix( ind, t ) * newek(t) ;
    //std::cout << "proj : " << proj << " with indMat = " << indivMatrix( ind, t ) << " && newek[k](t) = " << newek(t) << std::endl ;
  }
  
  return proj ;
}


#endif