aimsalgo  5.0.5
Neuroimaging image processing
kmeansstrategy.h
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33 
34 
35 
36 #ifndef KMEANSSTRATEGY_H
37 #define KMEANSSTRATEGY_H
38 
42 #include <aims/vector/vector.h>
43 #include <vector>
44 #include <list>
45 
46 namespace aims{
52  };
53 
54  template<class T>
55  class KmeansStrategy : public ClassifStrategy<T>{
56  public:
57 
58  KmeansStrategy( const KmeansStrategy<T>& kmeanStrat ) ;
59 
60  // L'initialisation de la classification par des vecteurs code
61  // est prioritaire sur le don de classes initiales.
62  KmeansStrategy( int nbIterations = 50,
63  DistanceType distanceType = NORM2SQR,
64  int beginIndex = 0, int endIndex = -1,
65  const std::vector< Individuals<T> >& codeVector = std::vector< Individuals<T> >() ) ;
66  virtual ~KmeansStrategy() ;
67  virtual ClassifStrategy<T> * clone() const ;
68 
69 /* virtual double iterate ( int & nbOfIterations, */
70 /* std::vector< std::list< Individuals<T> > >* classes ) ; */
71  virtual double iterate ( int& nbOfIterations,
72  std::vector< std::list< Individuals<T> > >& classes ) ;
73  virtual void init( std::string initializationType, int nbOfClasses,
74  std::vector< std::list< Individuals<T> > >& classes ) ;
75  virtual void analyse( const std::vector< std::list< Individuals<T> > >& classes ) ;
76  virtual int aggregate( const Individuals<T>& individual ) ;
77 
78  virtual Individuals<T> getMeanValue( int classe ) { return myMeanVector[classe] ; }
79  virtual std::vector< Individuals<T> > getMeanVector() { return myMeanVector ; }
80 
81  virtual double globInertia( const std::vector< std::list< Individuals<T> > >& classes ) ;
82 
83  protected:
84  virtual float distance( const Individuals<T>& individual, int classe ) ;
85 /* float (Distance<T>:: * myDistance)( const std::vector<T>& ind1, const std::vector<T>& ind2, */
86 /* unsigned int beginIndex, unsigned int endIndex ) ; */
87  float ( * myDistance )( const std::vector<T>& ind1, const std::vector<T>& ind2,
88  unsigned int beginIndex, unsigned int endIndex ) ;
89  std::vector< Individuals<T> > myMeanVector ;
90  std::vector< Individuals<T> > myVarianceVector ;
92  } ;
93 }
94 
95 #endif
virtual double globInertia(const std::vector< std::list< Individuals< T > > > &classes)
virtual ClassifStrategy< T > * clone() const
KmeansStrategy(const KmeansStrategy< T > &kmeanStrat)
virtual void init(std::string initializationType, int nbOfClasses, std::vector< std::list< Individuals< T > > > &classes)
std::vector< Individuals< T > > myMeanVector
virtual std::vector< Individuals< T > > getMeanVector()
virtual Individuals< T > getMeanValue(int classe)
float(* myDistance)(const std::vector< T > &ind1, const std::vector< T > &ind2, unsigned int beginIndex, unsigned int endIndex)
virtual void analyse(const std::vector< std::list< Individuals< T > > > &classes)
virtual float distance(const Individuals< T > &individual, int classe)
std::vector< Individuals< T > > myVarianceVector
virtual int aggregate(const Individuals< T > &individual)
virtual double iterate(int &nbOfIterations, std::vector< std::list< Individuals< T > > > &classes)