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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)
template<class TSubsample>
TSubsample::MeasurementType QuickSelect (TSubsample *sample, unsigned int activeDimension, int beginIndex, int endIndex, int kth, typename TSubsample::MeasurementType medianGuess)


Function Documentation

template<class TSubsample>
void itk::Statistics::Algorithm::DownHeap ( TSubsample *  sample,
unsigned int  activeDimension,
int  beginIndex,
int  endIndex,
int  node 
) [inline]

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 
) [inline]

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 
) [inline]

template<class TSize>
TSize itk::Statistics::Algorithm::FloorLog ( TSize  size  )  [inline]

template<class TSubsample>
void itk::Statistics::Algorithm::HeapSort ( TSubsample *  sample,
unsigned int  activeDimension,
int  beginIndex,
int  endIndex 
) [inline]

template<class TSubsample>
void itk::Statistics::Algorithm::InsertSort ( TSubsample *  sample,
unsigned int  activeDimension,
int  beginIndex,
int  endIndex 
) [inline]

template<class TSubsample>
void itk::Statistics::Algorithm::IntrospectiveSort ( TSubsample *  sample,
unsigned int  activeDimension,
int  beginIndex,
int  endIndex,
int  sizeThreshold 
) [inline]

template<class TSubsample>
void itk::Statistics::Algorithm::IntrospectiveSortLoop ( TSubsample *  sample,
unsigned int  activeDimension,
int  beginIndex,
int  endIndex,
int  depthLimit,
int  sizeThreshold 
) [inline]

template<class TValue>
TValue itk::Statistics::Algorithm::MedianOfThree ( const TValue  a,
const TValue  b,
const TValue  c 
) [inline]

template<class TSubsample>
TSubsample::MeasurementType itk::Statistics::Algorithm::NthElement ( TSubsample *  sample,
unsigned int  activeDimension,
int  beginIndex,
int  endIndex,
int  nth 
) [inline]

NthElement is an algorithm for finding the n-th largest element of a list. In this case, only 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. 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 
) [inline]

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 
) [inline]

QuickSelect is an algorithm for finding the k-th largest element of a list. In this case, only 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.

template<class TSubsample>
TSubsample::MeasurementType itk::Statistics::Algorithm::QuickSelect ( TSubsample *  sample,
unsigned int  activeDimension,
int  beginIndex,
int  endIndex,
int  kth,
typename TSubsample::MeasurementType  medianGuess 
) [inline]

QuickSelect is an algorithm for finding the k-th largest element of a list. In this case, only 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 algoritm returns the value of the activeDimension component in the MeasurementVector located in the kth position. http://en.wikipedia.org/wiki/Selection_algorithm


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