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

#include <itkKdTreeBasedKmeansEstimator.h>

List of all members.

Classes
struct	Candidate
Public Member Functions
	CandidateVector ()
	CandidateVector ()
Candidate &	operator[] (int index)
Candidate &	operator[] (int index)
int	Size () const
int	Size () const
virtual	~CandidateVector ()
virtual	~CandidateVector ()
void	GetCentroids (InternalParametersType &centroids)
void	GetCentroids (InternalParametersType &centroids)
void	SetCentroids (InternalParametersType &centroids)
void	SetCentroids (InternalParametersType &centroids)
void	UpdateCentroids ()
void	UpdateCentroids ()

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Detailed Description

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

vector of k-means candidates

Definition at line 163 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.

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Constructor & Destructor Documentation

template<class TKdTree >

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

(

)

[inline]

Definition at line 166 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.

template<class TKdTree >

virtual itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::~CandidateVector

(

)

[inline, virtual]

Definition at line 175 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.

template<class TKdTree >

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

(

)

[inline]

Definition at line 173 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.

template<class TKdTree >

virtual itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::~CandidateVector

(

)

[inline, virtual]

Definition at line 181 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.

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Member Function Documentation

template<class TKdTree >

void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::GetCentroids

(

InternalParametersType &

centroids

)

[inline]

gets the centroids (k-means)

Definition at line 208 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.

template<class TKdTree >

void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::GetCentroids

(

InternalParametersType &

centroids

)

[inline]

gets the centroids (k-means)

Definition at line 200 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.

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

template<class TKdTree >

Candidate& itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::operator[]

(

int

index

)

[inline]

gets the index-th candidates

Definition at line 240 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.

template<class TKdTree >

Candidate& itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::operator[]

(

int

index

)

[inline]

gets the index-th candidates

Definition at line 232 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.

template<class TKdTree >

void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::SetCentroids

(

InternalParametersType &

centroids

)

[inline]

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

Definition at line 191 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.

References itk::Statistics::MeasurementVectorTraits::GetLength(), and itk::Statistics::MeasurementVectorTraits::SetLength().

template<class TKdTree >

void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::SetCentroids

(

InternalParametersType &

centroids

)

[inline]

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

Definition at line 183 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.

References itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Candidate::Centroid, itk::Statistics::MeasurementVectorTraits::GetLength(), itk::Statistics::MeasurementVectorTraits::SetLength(), itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Candidate::Size, and itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Candidate::WeightedCentroid.

template<class TKdTree >

int itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Size

(

void

)

const [inline]

returns the number of candidate = k

Definition at line 184 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.

template<class TKdTree >

int itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::Size

(

void

)

const [inline]

returns the number of candidate = k

Definition at line 178 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.

template<class TKdTree >

void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::UpdateCentroids

(

)

[inline]

updates the centroids using the vector sum of measurement vectors that belongs to each centroid and the number of measurement vectors

Definition at line 221 of file Review/Statistics/itkKdTreeBasedKmeansEstimator.h.

template<class TKdTree >

void itk::Statistics::KdTreeBasedKmeansEstimator< TKdTree >::CandidateVector::UpdateCentroids

(

)

[inline]

updates the centroids using the vector sum of measurement vectors that belongs to each centroid and the number of measurement vectors

Definition at line 213 of file Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h.

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The documentation for this class was generated from the following files:

• Numerics/Statistics/itkKdTreeBasedKmeansEstimator.h
• Review/Statistics/itkKdTreeBasedKmeansEstimator.h