#include <itkGaussianMixtureModelComponent.h>

Inheritance diagram for itk::Statistics::GaussianMixtureModelComponent< TSample >:

Collaboration diagram for itk::Statistics::GaussianMixtureModelComponent< TSample >:

Public Types
using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = GaussianMixtureModelComponent

using	Superclass = MixtureModelComponentBase< TSample >

Public Types inherited from itk::Statistics::MixtureModelComponentBase< TSample >
using	ConstPointer = SmartPointer< const Self >

using	MeasurementVectorSizeType = typename TSample::MeasurementVectorSizeType

using	MeasurementVectorType = typename TSample::MeasurementVectorType

using	MembershipFunctionType = MembershipFunctionBase< MeasurementVectorType >

using	ParametersType = Array< double >

using	Pointer = SmartPointer< Self >

using	Self = MixtureModelComponentBase

using	Superclass = Object

using	WeightArrayType = Array< double >

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	MembershipFunctionType = typename Superclass::MembershipFunctionType

using	WeightArrayType = typename Superclass::WeightArrayType

using	ParametersType = typename Superclass::ParametersType

using	NativeMembershipFunctionType = GaussianMembershipFunction< MeasurementVectorType >

using	MeanEstimatorType = WeightedMeanSampleFilter< TSample >

using	CovarianceEstimatorType = WeightedCovarianceSampleFilter< TSample >

using	MeanVectorType = typename MeanEstimatorType::OutputType

using	CovarianceMatrixType = typename CovarianceEstimatorType::OutputType

NativeMembershipFunctionType::Pointer	m_GaussianMembershipFunction

MeanEstimatorType::MeasurementVectorType	m_Mean

CovarianceEstimatorType::MatrixType	m_Covariance

MeanEstimatorType::Pointer	m_MeanEstimator

CovarianceEstimatorType::Pointer	m_CovarianceEstimator

virtual const char *	GetNameOfClass () const

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

void	SetSample (const TSample *sample) override

void	SetParameters (const ParametersType &parameters) override

static Pointer	New ()

	GaussianMixtureModelComponent ()

	~GaussianMixtureModelComponent () override=default

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

double	CalculateParametersChange ()

void	GenerateData () override

Additional Inherited Members
Public Member Functions inherited from itk::Statistics::MixtureModelComponentBase< TSample >
bool	AreParametersModified ()

void	AreParametersModified (bool flag)

double	Evaluate (MeasurementVectorType &measurements)

virtual ParametersType	GetFullParameters ()

MembershipFunctionType *	GetMembershipFunction ()

double	GetMinimalParametersChange ()

const TSample *	GetSample () const

double	GetWeight (unsigned int index) const

virtual const WeightArrayType &	GetWeights () const

void	SetMinimalParametersChange (double change)

virtual void	SetParameters (const ParametersType &parameters)

void	SetWeight (unsigned int index, double value)

virtual void	Update ()

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::MixtureModelComponentBase< TSample >
	MixtureModelComponentBase ()

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

void	SetMembershipFunction (MembershipFunctionType *function)

	~MixtureModelComponentBase () 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 TSample>
class itk::Statistics::GaussianMixtureModelComponent< TSample >

is a component (derived from MixtureModelComponentBase) for Gaussian class. This class is used in ExpectationMaximizationMixtureModelEstimator.

On every iteration of EM estimation, this class's GenerateData method is called to compute the new distribution parameters.

Recent API changes: The static const macro to get the length of a measurement vector, MeasurementVectorSize has been removed to allow the length of a measurement vector to be specified at run time. It is now obtained at run time from the sample set as input. Please use the function GetMeasurementVectorSize() to get the length.

See also: MixtureModelComponentBase, ExpectationMaximizationMixtureModelEstimator

Examples: Examples/Statistics/ExpectationMaximizationMixtureModelEstimator.cxx, SphinxExamples/src/Numerics/Statistics/2DGaussianMixtureModelExpectMax/Code.cxx, SphinxExamples/src/Numerics/Statistics/DistributeSamplingUsingGMM/Code.cxx, and SphinxExamples/src/Numerics/Statistics/DistributionOfPixelsUsingGMM/Code.cxx.

Definition at line 51 of file itkGaussianMixtureModelComponent.h.

Member Typedef Documentation

◆ ConstPointer

template<typename TSample >

using itk::Statistics::GaussianMixtureModelComponent< TSample >::ConstPointer = SmartPointer<const Self>

Definition at line 58 of file itkGaussianMixtureModelComponent.h.

◆ CovarianceEstimatorType

template<typename TSample >

using itk::Statistics::GaussianMixtureModelComponent< TSample >::CovarianceEstimatorType = WeightedCovarianceSampleFilter<TSample>

Typedefs from the superclass

Definition at line 78 of file itkGaussianMixtureModelComponent.h.

◆ CovarianceMatrixType

template<typename TSample >

using itk::Statistics::GaussianMixtureModelComponent< TSample >::CovarianceMatrixType = typename CovarianceEstimatorType::OutputType

Type of the covariance matrix

Definition at line 84 of file itkGaussianMixtureModelComponent.h.

◆ MeanEstimatorType

template<typename TSample >

using itk::Statistics::GaussianMixtureModelComponent< TSample >::MeanEstimatorType = WeightedMeanSampleFilter<TSample>

Types of the mean and the covariance calculator that will update this component's distribution parameters

Definition at line 77 of file itkGaussianMixtureModelComponent.h.

◆ MeanVectorType

template<typename TSample >

using itk::Statistics::GaussianMixtureModelComponent< TSample >::MeanVectorType = typename MeanEstimatorType::OutputType

Type of the mean vector

Definition at line 81 of file itkGaussianMixtureModelComponent.h.

◆ MeasurementVectorSizeType

template<typename TSample >

using itk::Statistics::GaussianMixtureModelComponent< TSample >::MeasurementVectorSizeType = typename Superclass::MeasurementVectorSizeType

Typedefs from the superclass

Definition at line 67 of file itkGaussianMixtureModelComponent.h.

◆ MeasurementVectorType

template<typename TSample >

using itk::Statistics::GaussianMixtureModelComponent< TSample >::MeasurementVectorType = typename Superclass::MeasurementVectorType

Typedefs from the superclass

Definition at line 66 of file itkGaussianMixtureModelComponent.h.

◆ MembershipFunctionType

template<typename TSample >

using itk::Statistics::GaussianMixtureModelComponent< TSample >::MembershipFunctionType = typename Superclass::MembershipFunctionType

Typedefs from the superclass

Definition at line 68 of file itkGaussianMixtureModelComponent.h.

◆ NativeMembershipFunctionType

template<typename TSample >

using itk::Statistics::GaussianMixtureModelComponent< TSample >::NativeMembershipFunctionType = GaussianMembershipFunction<MeasurementVectorType>

Type of the membership function. Gaussian density function

Definition at line 73 of file itkGaussianMixtureModelComponent.h.

◆ ParametersType

template<typename TSample >

using itk::Statistics::GaussianMixtureModelComponent< TSample >::ParametersType = typename Superclass::ParametersType

Typedefs from the superclass

Definition at line 70 of file itkGaussianMixtureModelComponent.h.

◆ Pointer

template<typename TSample >

using itk::Statistics::GaussianMixtureModelComponent< TSample >::Pointer = SmartPointer<Self>

Definition at line 57 of file itkGaussianMixtureModelComponent.h.

◆ Self

template<typename TSample >

using itk::Statistics::GaussianMixtureModelComponent< TSample >::Self = GaussianMixtureModelComponent

Standard class type aliases.

Definition at line 55 of file itkGaussianMixtureModelComponent.h.

◆ Superclass

template<typename TSample >

using itk::Statistics::GaussianMixtureModelComponent< TSample >::Superclass = MixtureModelComponentBase<TSample>

Definition at line 56 of file itkGaussianMixtureModelComponent.h.

◆ WeightArrayType

template<typename TSample >

using itk::Statistics::GaussianMixtureModelComponent< TSample >::WeightArrayType = typename Superclass::WeightArrayType

Typedefs from the superclass

Definition at line 69 of file itkGaussianMixtureModelComponent.h.

Constructor & Destructor Documentation

◆ GaussianMixtureModelComponent()

template<typename TSample >

itk::Statistics::GaussianMixtureModelComponent< TSample >::GaussianMixtureModelComponent ( )

protected

Typedefs from the superclass

◆ ~GaussianMixtureModelComponent()

template<typename TSample >

itk::Statistics::GaussianMixtureModelComponent< TSample >::~GaussianMixtureModelComponent ( )

overrideprotecteddefault

Typedefs from the superclass

Member Function Documentation

◆ CalculateParametersChange()

template<typename TSample >

double itk::Statistics::GaussianMixtureModelComponent< TSample >::CalculateParametersChange ( )

protected

Returns the sum of squared changes in parameters between iterations

◆ CreateAnother()

template<typename TSample >

virtual::itk::LightObject::Pointer itk::Statistics::GaussianMixtureModelComponent< TSample >::CreateAnother ( ) const

virtual

Typedefs from the superclass

Reimplemented from itk::Object.

◆ GenerateData()

template<typename TSample >

void itk::Statistics::GaussianMixtureModelComponent< TSample >::GenerateData ( )

overrideprotectedvirtual

Computes the new distribution parameters

Implements itk::Statistics::MixtureModelComponentBase< TSample >.

◆ GetNameOfClass()

template<typename TSample >

virtual const char* itk::Statistics::GaussianMixtureModelComponent< TSample >::GetNameOfClass ( ) const

virtual

Standard Macros

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >.

◆ New()

template<typename TSample >

static Pointer itk::Statistics::GaussianMixtureModelComponent< TSample >::New ( )

static

Typedefs from the superclass

◆ PrintSelf()

template<typename TSample >

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

overrideprotectedvirtual

Typedefs from the superclass

Reimplemented from itk::Object.

◆ SetParameters()

template<typename TSample >

void itk::Statistics::GaussianMixtureModelComponent< TSample >::SetParameters ( const ParametersType & parameters )

override

Sets the component's distribution parameters.

◆ SetSample()

template<typename TSample >

void itk::Statistics::GaussianMixtureModelComponent< TSample >::SetSample ( const TSample * sample )

overridevirtual

Sets the input sample

Reimplemented from itk::Statistics::MixtureModelComponentBase< TSample >.

Member Data Documentation

◆ m_Covariance

template<typename TSample >

CovarianceEstimatorType::MatrixType itk::Statistics::GaussianMixtureModelComponent< TSample >::m_Covariance

private

Typedefs from the superclass

Definition at line 114 of file itkGaussianMixtureModelComponent.h.

◆ m_CovarianceEstimator

template<typename TSample >

CovarianceEstimatorType::Pointer itk::Statistics::GaussianMixtureModelComponent< TSample >::m_CovarianceEstimator

private

Typedefs from the superclass

Definition at line 118 of file itkGaussianMixtureModelComponent.h.

◆ m_GaussianMembershipFunction

template<typename TSample >

NativeMembershipFunctionType::Pointer itk::Statistics::GaussianMixtureModelComponent< TSample >::m_GaussianMembershipFunction

private

Typedefs from the superclass

Definition at line 110 of file itkGaussianMixtureModelComponent.h.

◆ m_Mean

template<typename TSample >

MeanEstimatorType::MeasurementVectorType itk::Statistics::GaussianMixtureModelComponent< TSample >::m_Mean

private

Typedefs from the superclass

Definition at line 112 of file itkGaussianMixtureModelComponent.h.

◆ m_MeanEstimator

template<typename TSample >

MeanEstimatorType::Pointer itk::Statistics::GaussianMixtureModelComponent< TSample >::m_MeanEstimator

private

Typedefs from the superclass

Definition at line 116 of file itkGaussianMixtureModelComponent.h.

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

itkGaussianMixtureModelComponent.h

Public Types

Additional Inherited Members

Detailed Description

template<typename TSample> class itk::Statistics::GaussianMixtureModelComponent< TSample >

Member Typedef Documentation

◆ ConstPointer

◆ CovarianceEstimatorType

◆ CovarianceMatrixType

◆ MeanEstimatorType

◆ MeanVectorType

◆ MeasurementVectorSizeType

◆ MeasurementVectorType

◆ MembershipFunctionType

◆ NativeMembershipFunctionType

◆ ParametersType

◆ Pointer

◆ Self

◆ Superclass

◆ WeightArrayType

Constructor & Destructor Documentation

◆ GaussianMixtureModelComponent()

◆ ~GaussianMixtureModelComponent()

Member Function Documentation

◆ CalculateParametersChange()

◆ CreateAnother()

◆ GenerateData()

◆ GetNameOfClass()

◆ New()

◆ PrintSelf()

◆ SetParameters()

◆ SetSample()

Member Data Documentation

◆ m_Covariance

◆ m_CovarianceEstimator

◆ m_GaussianMembershipFunction

◆ m_Mean

◆ m_MeanEstimator

template<typename TSample>
class itk::Statistics::GaussianMixtureModelComponent< TSample >