itk::Statistics::Algorithm Namespace Reference

Functions
template<class TSubsample >
void	DownHeap (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex, int node)
template<class TSample >
void	FindSampleBound (const TSample *sample, typename TSample::ConstIterator begin, typename TSample::ConstIterator end, typename TSample::MeasurementVectorType &min, typename TSample::MeasurementVectorType &max)
template<class TSubsample >
void	FindSampleBoundAndMean (const TSubsample *sample, int beginIndex, int endIndex, typename TSubsample::MeasurementVectorType &min, typename TSubsample::MeasurementVectorType &max, typename TSubsample::MeasurementVectorType &mean)
template<class TSize >
TSize	FloorLog (TSize size)
template<class TSubsample >
void	HeapSort (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex)
template<class TSubsample >
void	InsertSort (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex)
template<class TSubsample >
void	IntrospectiveSort (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex, int sizeThreshold)
template<class TSubsample >
void	IntrospectiveSortLoop (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex, int depthLimit, int sizeThreshold)
template<class TValue >
TValue	MedianOfThree (const TValue a, const TValue b, const TValue c)
template<class TSubsample >
TSubsample::MeasurementType	NthElement (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex, int nth)
template<class TSubsample >
int	Partition (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex, const typename TSubsample::MeasurementType partitionValue)
template<class TSubsample >
TSubsample::MeasurementType	QuickSelect (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex, int kth, typename TSubsample::MeasurementType medianGuess)
template<class TSubsample >
TSubsample::MeasurementType	QuickSelect (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex, int kth)

Function Documentation

template<class TSubsample >

void itk::Statistics::Algorithm::DownHeap	(	TSubsample *	sample,
		unsigned int	activeDimension,
		int	beginIndex,
		int	endIndex,
		int	node
	)

template<class TSample >

void itk::Statistics::Algorithm::FindSampleBound	(	const TSample *	sample,
		typename TSample::ConstIterator	begin,
		typename TSample::ConstIterator	end,
		typename TSample::MeasurementVectorType &	min,
		typename TSample::MeasurementVectorType &	max
	)

template<class TSubsample >

void itk::Statistics::Algorithm::FindSampleBoundAndMean	(	const TSubsample *	sample,
		int	beginIndex,
		int	endIndex,
		typename TSubsample::MeasurementVectorType &	min,
		typename TSubsample::MeasurementVectorType &	max,
		typename TSubsample::MeasurementVectorType &	mean
	)

template<class TSize >

TSize itk::Statistics::Algorithm::FloorLog

(

TSize

size

)

template<class TSubsample >

void itk::Statistics::Algorithm::HeapSort	(	TSubsample *	sample,
		unsigned int	activeDimension,
		int	beginIndex,
		int	endIndex
	)

template<class TSubsample >

void itk::Statistics::Algorithm::InsertSort	(	TSubsample *	sample,
		unsigned int	activeDimension,
		int	beginIndex,
		int	endIndex
	)

template<class TSubsample >

void itk::Statistics::Algorithm::IntrospectiveSort	(	TSubsample *	sample,
		unsigned int	activeDimension,
		int	beginIndex,
		int	endIndex,
		int	sizeThreshold
	)

template<class TSubsample >

void itk::Statistics::Algorithm::IntrospectiveSortLoop	(	TSubsample *	sample,
		unsigned int	activeDimension,
		int	beginIndex,
		int	endIndex,
		int	depthLimit,
		int	sizeThreshold
	)

template<class TValue >

TValue itk::Statistics::Algorithm::MedianOfThree	(	const TValue	a,
		const TValue	b,
		const TValue	c
	)

template<class TSubsample >

TSubsample::MeasurementType itk::Statistics::Algorithm::NthElement	(	TSubsample *	sample,
		unsigned int	activeDimension,
		int	beginIndex,
		int	endIndex,
		int	nth
	)

NthElement is an algorithm for finding the n-th largest element of a list. In this case, only one of the components of the measurement vectors is considered. This component is defined by the argument activeDimension. The search is restricted to the range between the index begin and end, also passed as arguments. This algorithm was based on the procedure used in the STL nth_element method.

template<class TSubsample >

int itk::Statistics::Algorithm::Partition	(	TSubsample *	sample,
		unsigned int	activeDimension,
		int	beginIndex,
		int	endIndex,
		const typename TSubsample::MeasurementType	partitionValue
	)

The Partition algorithm performs partial sorting in a sample. Given a partitionValue, the algorithm moves to the beginning of the sample all MeasurementVectors whose component activeDimension is smaller than the partitionValue. In this way, the sample is partially sorted in two groups. First the group with activeDimension component smaller than the partitionValue, then the group of MeasurementVectors with activeDimension component larger than the partitionValue. The Partition algorithm takes as input a sample, and a range in that sample defined by [beginIndex,endIndex]. Only the activeDimension components of the MeasurementVectors in the sample will be considered by the algorithm. The Algorithm return an index in the range of [beginIndex,endIndex] pointing to the element with activeDimension component closest to the partitionValue.

template<class TSubsample >

TSubsample::MeasurementType itk::Statistics::Algorithm::QuickSelect	(	TSubsample *	sample,
		unsigned int	activeDimension,
		int	beginIndex,
		int	endIndex,
		int	kth,
		typename TSubsample::MeasurementType	medianGuess
	)

QuickSelect is an algorithm for finding the k-th largest element of a list. In this case, only one of the components of the measurement vectors is considered. This component is defined by the argument activeDimension. The search is rectricted to the range between the index begin and end, also passed as arguments. In this version, a guess value for the median index is provided in the argument medianGuess. The algorithm returns the value of the activeDimension component in the MeasurementVector located in the kth position. http://en.wikipedia.org/wiki/Selection_algorithm

template<class TSubsample >

TSubsample::MeasurementType itk::Statistics::Algorithm::QuickSelect	(	TSubsample *	sample,
		unsigned int	activeDimension,
		int	beginIndex,
		int	endIndex,
		int	kth
	)

QuickSelect is an algorithm for finding the k-th largest element of a list. In this case, only one of the components of the measurement vectors is considered. This component is defined by the argument activeDimension. The search is rectricted to the range between the index begin and end, also passed as arguments. http://en.wikipedia.org/wiki/Selection_algorithm.