itk::Statistics::KdTreeGenerator< TSample > Class Template Reference

This class generates a KdTree object without centroid information. More...

#include <itkKdTreeGenerator.h>

Inheritance diagram for itk::Statistics::KdTreeGenerator:

[legend]Collaboration diagram for itk::Statistics::KdTreeGenerator< TSample >:

[legend]List of all members.

Public Types
typedef KdTreeGenerator	Self
typedef Object	Superclass
typedef SmartPointer< Self >	Pointer
typedef TSample::MeasurementVectorType	MeasurementVectorType
typedef TSample::MeasurementType	MeasurementType
typedef KdTree< TSample >	KdTreeType
typedef KdTreeType	OutputType
typedef KdTreeType::Pointer	OutputPointer
typedef KdTreeType::KdTreeNodeType	KdTreeNodeType
typedef Subsample< TSample >	SubsampleType
typedef SubsampleType::Pointer	SubsamplePointer
Public Methods
virtual const char *	GetClassName () const
	itkStaticConstMacro (MeasurementVectorSize, unsigned int, TSample::MeasurementVectorSize)
void	SetSample (TSample *sample)
void	SetBucketSize (int size)
OutputPointer	GetOutput ()
void	Update ()
void	GenerateData ()
Static Public Methods
Pointer	New ()
Public Attributes
unsigned int	TotalInstance
Protected Methods
	KdTreeGenerator ()
virtual	~KdTreeGenerator ()
void	PrintSelf (std::ostream &os, Indent indent) const
SubsamplePointer	GetSubsample ()
virtual KdTreeNodeType *	GenerateNonterminalNode (int beginIndex, int endIndex, MeasurementVectorType &lowerBound, MeasurementVectorType &upperBound, int level)
KdTreeNodeType *	GenerateTreeLoop (int beginIndex, int endIndex, MeasurementVectorType &lowerBound, MeasurementVectorType &upperBound, int level)

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Detailed Description

template<class TSample>
class itk::Statistics::KdTreeGenerator< TSample >

This class generates a KdTree object without centroid information.

The KdTree object stores measurment vectors in a k-d tree structure that is a binary tree. The partition value is the median value of one of the k dimension (partition dimension). The partition dimension is determined by the spread of measurement values in each dimension. The partition dimension is the dimension has the widest spread. Our implementation of k-d tree doesn't have any construction or insertion logic. Users should use this class or the WeightedCentroidKdTreeGenerator class.

The number of the measurement vectors in a terminal node is set by the SetBucketSize method. If we use too small number for this, it might cause computational overhead to calculate bound conditions. However, too large number will cause more distance calculation between the measurement vectors in a terminal node and the query point.

To run this generator, users should provides the bucket size (SetBucketSize method) and the input sample (SetSample method). The Update method will run this generator. To get the resulting KdTree object, call the GetOutput method.

See also:

KdTree, KdTreeNode, KdTreeNonterminalNode, KdTreeTerminalNode, WeightedCentroidKdTreeGenerator

Definition at line 63 of file itkKdTreeGenerator.h.

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Member Typedef Documentation

template<class TSample> typedef KdTreeType::KdTreeNodeType itk::Statistics::KdTreeGenerator< TSample >::KdTreeNodeType

Typedef for the k-d tree node type Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >. Definition at line 94 of file itkKdTreeGenerator.h.

template<class TSample> typedef KdTree< TSample > itk::Statistics::KdTreeGenerator< TSample >::KdTreeType

Typedef for the k-d tree Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >. Definition at line 85 of file itkKdTreeGenerator.h.

template<class TSample> typedef TSample::MeasurementType itk::Statistics::KdTreeGenerator< TSample >::MeasurementType

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >. Definition at line 79 of file itkKdTreeGenerator.h.

template<class TSample> typedef TSample::MeasurementVectorType itk::Statistics::KdTreeGenerator< TSample >::MeasurementVectorType

typedef alias for the source data container Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >. Definition at line 78 of file itkKdTreeGenerator.h.

template<class TSample> typedef KdTreeType::Pointer itk::Statistics::KdTreeGenerator< TSample >::OutputPointer

Typedef for the smart pointer to the k-d tree Definition at line 91 of file itkKdTreeGenerator.h.

template<class TSample> typedef KdTreeType itk::Statistics::KdTreeGenerator< TSample >::OutputType

Type alias for the k-d tree type Definition at line 88 of file itkKdTreeGenerator.h.

template<class TSample> typedef SmartPointer<Self> itk::Statistics::KdTreeGenerator< TSample >::Pointer

Reimplemented from itk::Object. Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >. Definition at line 69 of file itkKdTreeGenerator.h.

template<class TSample> typedef KdTreeGenerator itk::Statistics::KdTreeGenerator< TSample >::Self

Standard class typedefs Reimplemented from itk::Object. Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >. Definition at line 67 of file itkKdTreeGenerator.h.

template<class TSample> typedef SubsampleType::Pointer itk::Statistics::KdTreeGenerator< TSample >::SubsamplePointer

Typedef for the smart pointer to the Subsample Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >. Definition at line 100 of file itkKdTreeGenerator.h.

template<class TSample> typedef Subsample< TSample > itk::Statistics::KdTreeGenerator< TSample >::SubsampleType

Typedef for the internal Subsample Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >. Definition at line 97 of file itkKdTreeGenerator.h.

template<class TSample> typedef Object itk::Statistics::KdTreeGenerator< TSample >::Superclass

Reimplemented from itk::Object. Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >. Definition at line 68 of file itkKdTreeGenerator.h.

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Constructor & Destructor Documentation

template<class TSample> itk::Statistics::KdTreeGenerator< TSample >::KdTreeGenerator (    )  [protected]

Constructor

template<class TSample> virtual itk::Statistics::KdTreeGenerator< TSample >::~KdTreeGenerator (    )  [inline, protected, virtual]

Destructor Definition at line 128 of file itkKdTreeGenerator.h.

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Member Function Documentation

template<class TSample> void itk::Statistics::KdTreeGenerator< TSample >::GenerateData (    )

Runs this k-d tree construction algorithm.

template<class TSample> virtual KdTreeNodeType* itk::Statistics::KdTreeGenerator< TSample >::GenerateNonterminalNode (  int    beginIndex, int    endIndex, MeasurementVectorType &    lowerBound, MeasurementVectorType &    upperBound, int    level )  [protected, virtual]

Nonterminal node generation routine Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

template<class TSample> KdTreeNodeType* itk::Statistics::KdTreeGenerator< TSample >::GenerateTreeLoop (  int    beginIndex, int    endIndex, MeasurementVectorType &    lowerBound, MeasurementVectorType &    upperBound, int    level )  [protected]

Tree generation loop

template<class TSample> virtual const char* itk::Statistics::KdTreeGenerator< TSample >::GetClassName (    )  const [virtual]

Run-time type information (and related methods) Reimplemented from itk::Object. Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

template<class TSample> OutputPointer itk::Statistics::KdTreeGenerator< TSample >::GetOutput (  void    )  [inline]

Returns the pointer to the generated k-d tree. Definition at line 110 of file itkKdTreeGenerator.h.

template<class TSample> SubsamplePointer itk::Statistics::KdTreeGenerator< TSample >::GetSubsample (    )  [inline, protected]

Returns the smart pointer to the internal Subsample object. Definition at line 133 of file itkKdTreeGenerator.h.

template<class TSample> itk::Statistics::KdTreeGenerator< TSample >::itkStaticConstMacro (  MeasurementVectorSize   , unsigned    int, TSample::MeasurementVectorSize    )

Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

template<class TSample> Pointer itk::Statistics::KdTreeGenerator< TSample >::New (    )  [static]

Method for creation through the object factory. Reimplemented from itk::Object. Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

template<class TSample> void itk::Statistics::KdTreeGenerator< TSample >::PrintSelf (  std::ostream &    os, Indent    indent )  const [protected, virtual]

Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes. Reimplemented from itk::Object. Reimplemented in itk::Statistics::WeightedCentroidKdTreeGenerator< TSample >.

template<class TSample> void itk::Statistics::KdTreeGenerator< TSample >::SetBucketSize (  int    size )

Sets the number of measurement vectors that can be stored in a terminal node.

template<class TSample> void itk::Statistics::KdTreeGenerator< TSample >::SetSample (  TSample *    sample )

Sets the input sample that provides the measurement vectors.

template<class TSample> void itk::Statistics::KdTreeGenerator< TSample >::Update (  void    )  [inline]

Runs this k-d tree construction algorithm. Definition at line 114 of file itkKdTreeGenerator.h. References HardConnectedComponentImageFilter::GenerateData().

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Member Data Documentation

template<class TSample> unsigned int itk::Statistics::KdTreeGenerator< TSample >::TotalInstance

The number of measurement vectors in an object of this class. Definition at line 121 of file itkKdTreeGenerator.h.

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

• itkKdTreeGenerator.h

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