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itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector Class Template Reference

#include <itkKdTreeBasedKmeansEstimator.h>

List of all members.

Public Methods

 CandidateVector ()
virtual ~CandidateVector ()
int Size ()
Candidateoperator[] (int index)
void SetCenteroids (InternalParametersType &centeroids)
void GetCenteroids (InternalParametersType &centeroids)
void UpdateCenteroids ()


Detailed Description

template<class TKdTree>
class itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector

vector of k-means candidates

Definition at line 141 of file itkKdTreeBasedKmeansEstimator.h.


Constructor & Destructor Documentation

template<class TKdTree>
itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::CandidateVector   [inline]
 

Definition at line 144 of file itkKdTreeBasedKmeansEstimator.h.

template<class TKdTree>
virtual itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::~CandidateVector   [inline, virtual]
 

Definition at line 153 of file itkKdTreeBasedKmeansEstimator.h.


Member Function Documentation

template<class TKdTree>
void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::GetCenteroids InternalParametersType   centeroids [inline]
 

gets the centeroids (k-means)

Definition at line 176 of file itkKdTreeBasedKmeansEstimator.h.

References itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Candidate::Centeroid.

template<class TKdTree>
Candidate& itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::operator[] int    index [inline]
 

gets the index-th candidates

Definition at line 208 of file itkKdTreeBasedKmeansEstimator.h.

template<class TKdTree>
void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::SetCenteroids InternalParametersType   centeroids [inline]
 

Initialize the centeroids with the argument. At each iteration, this should be called before filtering

Definition at line 161 of file itkKdTreeBasedKmeansEstimator.h.

References itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Candidate::Centeroid, itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Candidate::Size, and itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Candidate::WeightedCenteroid.

template<class TKdTree>
int itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Size void    [inline]
 

returns the number of candidate = k

Definition at line 156 of file itkKdTreeBasedKmeansEstimator.h.

template<class TKdTree>
void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::UpdateCenteroids   [inline]
 

updates the centeroids using the vector sum of measurement vectors that belongs to each centeroid and the number of measurement vectors

Definition at line 189 of file itkKdTreeBasedKmeansEstimator.h.


The documentation for this class was generated from the following file:
Generated at Wed Mar 12 01:22:41 2003 for ITK by doxygen 1.2.15 written by Dimitri van Heesch, © 1997-2000