#include <itkMahalanobisDistanceMetric.h>

Inheritance diagram for itk::Statistics::MahalanobisDistanceMetric< TVector >:

Collaboration diagram for itk::Statistics::MahalanobisDistanceMetric< TVector >:

Public Types
using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = MahalanobisDistanceMetric

using	Superclass = DistanceMetric< TVector >

Public Types inherited from itk::Statistics::DistanceMetric< TVector >
using	ConstPointer = SmartPointer< const Self >

using	MeasurementVectorSizeType = unsigned int

using	MeasurementVectorType = TVector

using	OriginType = Array< double >

using	Pointer = SmartPointer< Self >

using	Self = DistanceMetric

using	Superclass = FunctionBase< TVector, double >

Public Types inherited from itk::FunctionBase< TVector, double >
using	ConstPointer = SmartPointer< const Self >

using	InputType = TVector

using	OutputType = double

using	Pointer = SmartPointer< Self >

using	Self = FunctionBase

using	Superclass = Object

Public Types inherited from itk::Object
using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = Object

using	Superclass = LightObject

Public Types inherited from itk::LightObject
using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = LightObject

using	MeasurementVectorType = typename Superclass::MeasurementVectorType

using	MeasurementVectorSizeType = typename Superclass::MeasurementVectorSizeType

using	MeanVectorType = typename Superclass::OriginType

using	CovarianceMatrixType = vnl_matrix< double >

MeanVectorType	m_Mean

CovarianceMatrixType	m_Covariance

CovarianceMatrixType	m_InverseCovariance

double	m_Epsilon { 1e-100 }

double	m_DoubleMax { 1e+20 }

virtual const char *	GetNameOfClass () const

virtual ::itk::LightObject::Pointer	CreateAnother () const

void	SetMeasurementVectorSize (MeasurementVectorSizeType) override

void	SetMean (const MeanVectorType &mean)

const MeanVectorType &	GetMean () const

void	SetCovariance (const CovarianceMatrixType &cov)

virtual const CovarianceMatrixType &	GetCovariance () const

void	SetInverseCovariance (const CovarianceMatrixType &invcov)

virtual const CovarianceMatrixType &	GetInverseCovariance () const

double	Evaluate (const MeasurementVectorType &measurement) const override

double	Evaluate (const MeasurementVectorType &x1, const MeasurementVectorType &x2) const override

virtual void	SetEpsilon (double _arg)

virtual double	GetEpsilon () const

virtual void	SetDoubleMax (double _arg)

virtual double	GetDoubleMax () const

static Pointer	New ()

	MahalanobisDistanceMetric ()

	~MahalanobisDistanceMetric () override=default

void	PrintSelf (std::ostream &os, Indent indent) const override

void	CalculateInverseCovariance ()

Additional Inherited Members
Public Member Functions inherited from itk::Statistics::DistanceMetric< TVector >
virtual MeasurementVectorSizeType	GetMeasurementVectorSize () const

virtual const OriginType &	GetOrigin () const

void	SetOrigin (const OriginType &x)

Public Member Functions inherited from itk::Object
unsigned long	AddObserver (const EventObject &event, Command *)

unsigned long	AddObserver (const EventObject &event, Command *) const

unsigned long	AddObserver (const EventObject &event, std::function< void(const EventObject &)> function) const

virtual void	DebugOff () const

virtual void	DebugOn () const

Command *	GetCommand (unsigned long tag)

bool	GetDebug () const

MetaDataDictionary &	GetMetaDataDictionary ()

const MetaDataDictionary &	GetMetaDataDictionary () const

virtual ModifiedTimeType	GetMTime () const

virtual const TimeStamp &	GetTimeStamp () const

bool	HasObserver (const EventObject &event) const

void	InvokeEvent (const EventObject &)

void	InvokeEvent (const EventObject &) const

virtual void	Modified () const

void	Register () const override

void	RemoveAllObservers ()

void	RemoveObserver (unsigned long tag)

void	SetDebug (bool debugFlag) const

void	SetReferenceCount (int) override

void	UnRegister () const noexcept override

void	SetMetaDataDictionary (const MetaDataDictionary &rhs)

void	SetMetaDataDictionary (MetaDataDictionary &&rrhs)

virtual void	SetObjectName (std::string _arg)

virtual const std::string &	GetObjectName () const

Public Member Functions inherited from itk::LightObject
Pointer	Clone () const

virtual void	Delete ()

virtual int	GetReferenceCount () const

void	Print (std::ostream &os, Indent indent=0) const

Static Public Member Functions inherited from itk::Object
static bool	GetGlobalWarningDisplay ()

static void	GlobalWarningDisplayOff ()

static void	GlobalWarningDisplayOn ()

static Pointer	New ()

static void	SetGlobalWarningDisplay (bool val)

Static Public Member Functions inherited from itk::LightObject
static void	BreakOnError ()

static Pointer	New ()

Protected Member Functions inherited from itk::Statistics::DistanceMetric< TVector >
	DistanceMetric ()

	~DistanceMetric () override=default

Protected Member Functions inherited from itk::FunctionBase< TVector, double >
	FunctionBase ()=default

	~FunctionBase () override=default

Protected Member Functions inherited from itk::Object
	Object ()

	~Object () override

bool	PrintObservers (std::ostream &os, Indent indent) const

virtual void	SetTimeStamp (const TimeStamp &timeStamp)

Protected Member Functions inherited from itk::LightObject
virtual LightObject::Pointer	InternalClone () const

	LightObject ()

virtual void	PrintHeader (std::ostream &os, Indent indent) const

virtual void	PrintTrailer (std::ostream &os, Indent indent) const

virtual	~LightObject ()

Protected Attributes inherited from itk::LightObject
std::atomic< int >	m_ReferenceCount

Detailed Description

template<typename TVector>
class itk::Statistics::MahalanobisDistanceMetric< TVector >

MahalanobisDistanceMetric class computes a Mahalanobis distance given a mean and covariance.

See also: DistanceMetric; EuclideanDistanceMetric; EuclideanSquareDistanceMetric

Definition at line 47 of file itkMahalanobisDistanceMetric.h.

Member Typedef Documentation

◆ ConstPointer

template<typename TVector >

using itk::Statistics::MahalanobisDistanceMetric< TVector >::ConstPointer = SmartPointer<const Self>

Definition at line 54 of file itkMahalanobisDistanceMetric.h.

◆ CovarianceMatrixType

template<typename TVector >

using itk::Statistics::MahalanobisDistanceMetric< TVector >::CovarianceMatrixType = vnl_matrix<double>

Type used for representing the covariance matrix

Definition at line 71 of file itkMahalanobisDistanceMetric.h.

◆ MeanVectorType

template<typename TVector >

using itk::Statistics::MahalanobisDistanceMetric< TVector >::MeanVectorType = typename Superclass::OriginType

Type used for representing the mean vector

Definition at line 68 of file itkMahalanobisDistanceMetric.h.

◆ MeasurementVectorSizeType

template<typename TVector >

using itk::Statistics::MahalanobisDistanceMetric< TVector >::MeasurementVectorSizeType = typename Superclass::MeasurementVectorSizeType

Typedef to represent the length of measurement vectors

Definition at line 65 of file itkMahalanobisDistanceMetric.h.

◆ MeasurementVectorType

template<typename TVector >

using itk::Statistics::MahalanobisDistanceMetric< TVector >::MeasurementVectorType = typename Superclass::MeasurementVectorType

Typedef to represent the measurement vector type

Definition at line 62 of file itkMahalanobisDistanceMetric.h.

◆ Pointer

template<typename TVector >

using itk::Statistics::MahalanobisDistanceMetric< TVector >::Pointer = SmartPointer<Self>

Definition at line 53 of file itkMahalanobisDistanceMetric.h.

◆ Self

template<typename TVector >

using itk::Statistics::MahalanobisDistanceMetric< TVector >::Self = MahalanobisDistanceMetric

Standard class type aliases

Definition at line 51 of file itkMahalanobisDistanceMetric.h.

◆ Superclass

template<typename TVector >

using itk::Statistics::MahalanobisDistanceMetric< TVector >::Superclass = DistanceMetric<TVector>

Definition at line 52 of file itkMahalanobisDistanceMetric.h.

Constructor & Destructor Documentation

◆ MahalanobisDistanceMetric()

template<typename TVector >

itk::Statistics::MahalanobisDistanceMetric< TVector >::MahalanobisDistanceMetric ( )

protected

Typedef to represent the measurement vector type

◆ ~MahalanobisDistanceMetric()

template<typename TVector >

itk::Statistics::MahalanobisDistanceMetric< TVector >::~MahalanobisDistanceMetric ( )

overrideprotecteddefault

Typedef to represent the measurement vector type

Member Function Documentation

◆ CalculateInverseCovariance()

template<typename TVector >

void itk::Statistics::MahalanobisDistanceMetric< TVector >::CalculateInverseCovariance ( )

private

Typedef to represent the measurement vector type

◆ CreateAnother()

template<typename TVector >

virtual::itk::LightObject::Pointer itk::Statistics::MahalanobisDistanceMetric< TVector >::CreateAnother ( ) const

virtual

Typedef to represent the measurement vector type

Reimplemented from itk::Object.

◆ Evaluate() [1/2]

template<typename TVector >

double itk::Statistics::MahalanobisDistanceMetric< TVector >::Evaluate ( const MeasurementVectorType & measurement ) const

overridevirtual

Method to get probability of an instance. The return value is the value of the density function, not probability.

Implements itk::Statistics::DistanceMetric< TVector >.

◆ Evaluate() [2/2]

template<typename TVector >

double itk::Statistics::MahalanobisDistanceMetric< TVector >::Evaluate	(	const MeasurementVectorType &	x1,
		const MeasurementVectorType &	x2
	)		const

overridevirtual

Gets the distance between x1 and x2.

Implements itk::Statistics::DistanceMetric< TVector >.

◆ GetCovariance()

template<typename TVector >

virtual const CovarianceMatrixType& itk::Statistics::MahalanobisDistanceMetric< TVector >::GetCovariance ( ) const

virtual

Method to get covariance matrix

◆ GetDoubleMax()

template<typename TVector >

virtual double itk::Statistics::MahalanobisDistanceMetric< TVector >::GetDoubleMax ( ) const

virtual

Typedef to represent the measurement vector type

◆ GetEpsilon()

template<typename TVector >

virtual double itk::Statistics::MahalanobisDistanceMetric< TVector >::GetEpsilon ( ) const

virtual

Typedef to represent the measurement vector type

◆ GetInverseCovariance()

template<typename TVector >

virtual const CovarianceMatrixType& itk::Statistics::MahalanobisDistanceMetric< TVector >::GetInverseCovariance ( ) const

virtual

Method to get covariance matrix

◆ GetMean()

template<typename TVector >

const MeanVectorType& itk::Statistics::MahalanobisDistanceMetric< TVector >::GetMean ( ) const

Method to get mean

◆ GetNameOfClass()

template<typename TVector >

virtual const char* itk::Statistics::MahalanobisDistanceMetric< TVector >::GetNameOfClass ( ) const

virtual

Strandard macros

Reimplemented from itk::Statistics::DistanceMetric< TVector >.

◆ New()

template<typename TVector >

static Pointer itk::Statistics::MahalanobisDistanceMetric< TVector >::New ( )

static

Typedef to represent the measurement vector type

◆ PrintSelf()

template<typename TVector >

void itk::Statistics::MahalanobisDistanceMetric< TVector >::PrintSelf	(	std::ostream &	os,
		Indent	indent
	)		const

overrideprotectedvirtual

Typedef to represent the measurement vector type

Reimplemented from itk::Statistics::DistanceMetric< TVector >.

◆ SetCovariance()

template<typename TVector >

void itk::Statistics::MahalanobisDistanceMetric< TVector >::SetCovariance ( const CovarianceMatrixType & cov )

Method to set covariance matrix Also, this function calculates inverse covariance and pre factor of MahalanobisDistance Distribution to speed up GetProbability

◆ SetDoubleMax()

template<typename TVector >

virtual void itk::Statistics::MahalanobisDistanceMetric< TVector >::SetDoubleMax ( double _arg )

virtual

Typedef to represent the measurement vector type

◆ SetEpsilon()

template<typename TVector >

virtual void itk::Statistics::MahalanobisDistanceMetric< TVector >::SetEpsilon ( double _arg )

virtual

Set/Get tolerance values

◆ SetInverseCovariance()

template<typename TVector >

void itk::Statistics::MahalanobisDistanceMetric< TVector >::SetInverseCovariance ( const CovarianceMatrixType & invcov )

Method to set inverse covariance matrix

◆ SetMean()

template<typename TVector >

void itk::Statistics::MahalanobisDistanceMetric< TVector >::SetMean ( const MeanVectorType & mean )

Method to set mean

◆ SetMeasurementVectorSize()

template<typename TVector >

void itk::Statistics::MahalanobisDistanceMetric< TVector >::SetMeasurementVectorSize ( MeasurementVectorSizeType )

overridevirtual

Set the length of each measurement vector.

Reimplemented from itk::Statistics::DistanceMetric< TVector >.

Member Data Documentation

◆ m_Covariance

template<typename TVector >

CovarianceMatrixType itk::Statistics::MahalanobisDistanceMetric< TVector >::m_Covariance

private

Typedef to represent the measurement vector type

Definition at line 128 of file itkMahalanobisDistanceMetric.h.

◆ m_DoubleMax

template<typename TVector >

double itk::Statistics::MahalanobisDistanceMetric< TVector >::m_DoubleMax { 1e+20 }

private

Typedef to represent the measurement vector type

Definition at line 135 of file itkMahalanobisDistanceMetric.h.

◆ m_Epsilon

template<typename TVector >

double itk::Statistics::MahalanobisDistanceMetric< TVector >::m_Epsilon { 1e-100 }

private

Typedef to represent the measurement vector type

Definition at line 134 of file itkMahalanobisDistanceMetric.h.

◆ m_InverseCovariance

template<typename TVector >

CovarianceMatrixType itk::Statistics::MahalanobisDistanceMetric< TVector >::m_InverseCovariance

private

Typedef to represent the measurement vector type

Definition at line 132 of file itkMahalanobisDistanceMetric.h.

◆ m_Mean

template<typename TVector >

MeanVectorType itk::Statistics::MahalanobisDistanceMetric< TVector >::m_Mean

private

Typedef to represent the measurement vector type

Definition at line 127 of file itkMahalanobisDistanceMetric.h.

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

itkMahalanobisDistanceMetric.h

Public Types

Additional Inherited Members

Detailed Description

template<typename TVector> class itk::Statistics::MahalanobisDistanceMetric< TVector >

Member Typedef Documentation

◆ ConstPointer

◆ CovarianceMatrixType

◆ MeanVectorType

◆ MeasurementVectorSizeType

◆ MeasurementVectorType

◆ Pointer

◆ Self

◆ Superclass

Constructor & Destructor Documentation

◆ MahalanobisDistanceMetric()

◆ ~MahalanobisDistanceMetric()

Member Function Documentation

◆ CalculateInverseCovariance()

◆ CreateAnother()

◆ Evaluate() [1/2]

◆ Evaluate() [2/2]

◆ GetCovariance()

◆ GetDoubleMax()

◆ GetEpsilon()

◆ GetInverseCovariance()

◆ GetMean()

◆ GetNameOfClass()

◆ New()

◆ PrintSelf()

◆ SetCovariance()

◆ SetDoubleMax()

◆ SetEpsilon()

◆ SetInverseCovariance()

◆ SetMean()

◆ SetMeasurementVectorSize()

Member Data Documentation

◆ m_Covariance

◆ m_DoubleMax

◆ m_Epsilon

◆ m_InverseCovariance

◆ m_Mean

template<typename TVector>
class itk::Statistics::MahalanobisDistanceMetric< TVector >