ITK  5.2.0
Insight Toolkit
Public Types | List of all members
itk::Statistics::GaussianMembershipFunction< TMeasurementVector > Class Template Reference

#include <itkGaussianMembershipFunction.h>

+ Inheritance diagram for itk::Statistics::GaussianMembershipFunction< TMeasurementVector >:
+ Collaboration diagram for itk::Statistics::GaussianMembershipFunction< TMeasurementVector >:

Public Types

using ConstPointer = SmartPointer< const Self >
 
using Pointer = SmartPointer< Self >
 
using Self = GaussianMembershipFunction
 
using Superclass = MembershipFunctionBase< TMeasurementVector >
 
- Public Types inherited from itk::Statistics::MembershipFunctionBase< TMeasurementVector >
using ConstPointer = SmartPointer< const Self >
 
using MeasurementVectorSizeType = unsigned int
 
using MeasurementVectorType = TMeasurementVector
 
using Pointer = SmartPointer< Self >
 
using Self = MembershipFunctionBase
 
using Superclass = FunctionBase< TMeasurementVector, double >
 
- Public Types inherited from itk::FunctionBase< TMeasurementVector, double >
using ConstPointer = SmartPointer< const Self >
 
using InputType = TMeasurementVector
 
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 MembershipFunctionPointer = typename Superclass::Pointer
 
using MeasurementVectorType = TMeasurementVector
 
using MeasurementVectorSizeType = typename Superclass::MeasurementVectorSizeType
 
using MeasurementVectorRealType = typename itk::NumericTraits< MeasurementVectorType >::RealType
 
using MeanVectorType = MeasurementVectorRealType
 
using CovarianceMatrixType = VariableSizeMatrix< double >
 
MeanVectorType m_Mean
 
CovarianceMatrixType m_Covariance
 
CovarianceMatrixType m_InverseCovariance
 
double m_PreFactor
 
bool m_CovarianceNonsingular
 
virtual const char * GetNameOfClass () const
 
virtual ::itk::LightObject::Pointer CreateAnother () const
 
void SetMean (const MeanVectorType &mean)
 
virtual const MeanVectorTypeGetMean () const
 
void SetCovariance (const CovarianceMatrixType &cov)
 
virtual const CovarianceMatrixTypeGetCovariance () const
 
virtual const CovarianceMatrixTypeGetInverseCovariance () const
 
double Evaluate (const MeasurementVectorType &measurement) const override
 
LightObject::Pointer InternalClone () const override
 
static Pointer New ()
 
 GaussianMembershipFunction ()
 
 ~GaussianMembershipFunction () override=default
 
void PrintSelf (std::ostream &os, Indent indent) const override
 

Additional Inherited Members

- Public Member Functions inherited from itk::Statistics::MembershipFunctionBase< TMeasurementVector >
virtual MeasurementVectorSizeType GetMeasurementVectorSize () const
 
virtual void SetMeasurementVectorSize (MeasurementVectorSizeType s)
 
- 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
 
CommandGetCommand (unsigned long tag)
 
bool GetDebug () const
 
MetaDataDictionaryGetMetaDataDictionary ()
 
const MetaDataDictionaryGetMetaDataDictionary () const
 
virtual ModifiedTimeType GetMTime () const
 
virtual const TimeStampGetTimeStamp () 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
virtual void Delete ()
 
virtual int GetReferenceCount () const
 
 itkCloneMacro (Self)
 
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 flag)
 
- Static Public Member Functions inherited from itk::LightObject
static void BreakOnError ()
 
static Pointer New ()
 
- Protected Member Functions inherited from itk::Statistics::MembershipFunctionBase< TMeasurementVector >
 MembershipFunctionBase ()
 
void PrintSelf (std::ostream &os, Indent indent) const override
 
 ~MembershipFunctionBase () override=default
 
- Protected Member Functions inherited from itk::FunctionBase< TMeasurementVector, 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 &time)
 
- Protected Member Functions inherited from itk::LightObject
 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 TMeasurementVector>
class itk::Statistics::GaussianMembershipFunction< TMeasurementVector >

GaussianMembershipFunction models class membership through a multivariate Gaussian function.

GaussianMembershipFunction is a subclass of MembershipFunctionBase that models class membership (or likelihood) using a multivariate Gaussian function. The mean and covariance structure of the Gaussian are established using the methods SetMean() and SetCovariance(). The mean is a vector-type that is the same vector-type as the measurement vector but guaranteed to have a real element type. For instance, if the measurement type is an Vector<int,3>, then the mean is Vector<double,3>. If the measurement type is a VariableLengthVector<float>, then the mean is VariableLengthVector<double>. In contrast to this behavior, the covariance is always a VariableSizeMatrix<double>.

If the covariance is singular or nearly singular, the membership function behaves somewhat like an impulse located at the mean. In this case, we specify the covariance to be a diagonal matrix with large values along the diagonal. This membership function, therefore, will return small but differentiable values everywhere and increase sharply near the mean.

Examples
Examples/Statistics/BayesianPluginClassifier.cxx, and Examples/Statistics/GaussianMembershipFunction.cxx.

Definition at line 56 of file itkGaussianMembershipFunction.h.

Member Typedef Documentation

◆ ConstPointer

template<typename TMeasurementVector >
using itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::ConstPointer = SmartPointer<const Self>

Definition at line 65 of file itkGaussianMembershipFunction.h.

◆ CovarianceMatrixType

template<typename TMeasurementVector >
using itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::CovarianceMatrixType = VariableSizeMatrix<double>

Type of the covariance matrix

Definition at line 87 of file itkGaussianMembershipFunction.h.

◆ MeanVectorType

template<typename TMeasurementVector >
using itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::MeanVectorType = MeasurementVectorRealType

SmartPointer class for superclass

Definition at line 84 of file itkGaussianMembershipFunction.h.

◆ MeasurementVectorRealType

template<typename TMeasurementVector >
using itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::MeasurementVectorRealType = typename itk::NumericTraits<MeasurementVectorType>::RealType

Type of the mean vector. RealType on a vector-type is the same vector-type but with a real element type.

Definition at line 83 of file itkGaussianMembershipFunction.h.

◆ MeasurementVectorSizeType

template<typename TMeasurementVector >
using itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::MeasurementVectorSizeType = typename Superclass::MeasurementVectorSizeType

Length of each measurement vector

Definition at line 79 of file itkGaussianMembershipFunction.h.

◆ MeasurementVectorType

template<typename TMeasurementVector >
using itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::MeasurementVectorType = TMeasurementVector

Typedef alias for the measurement vectors

Definition at line 76 of file itkGaussianMembershipFunction.h.

◆ MembershipFunctionPointer

template<typename TMeasurementVector >
using itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::MembershipFunctionPointer = typename Superclass::Pointer

SmartPointer class for superclass

Definition at line 73 of file itkGaussianMembershipFunction.h.

◆ Pointer

template<typename TMeasurementVector >
using itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::Pointer = SmartPointer<Self>

Definition at line 64 of file itkGaussianMembershipFunction.h.

◆ Self

template<typename TMeasurementVector >
using itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::Self = GaussianMembershipFunction

Standard class type aliases

Definition at line 62 of file itkGaussianMembershipFunction.h.

◆ Superclass

template<typename TMeasurementVector >
using itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::Superclass = MembershipFunctionBase<TMeasurementVector>

Definition at line 63 of file itkGaussianMembershipFunction.h.

Constructor & Destructor Documentation

◆ GaussianMembershipFunction()

template<typename TMeasurementVector >
itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::GaussianMembershipFunction ( )
protected

SmartPointer class for superclass

◆ ~GaussianMembershipFunction()

template<typename TMeasurementVector >
itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::~GaussianMembershipFunction ( )
overrideprotecteddefault

SmartPointer class for superclass

Member Function Documentation

◆ CreateAnother()

template<typename TMeasurementVector >
virtual::itk::LightObject::Pointer itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::CreateAnother ( ) const
virtual

SmartPointer class for superclass

Reimplemented from itk::Object.

◆ Evaluate()

template<typename TMeasurementVector >
double itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::Evaluate ( const MeasurementVectorType measurement) const
overridevirtual

Evaluate the probability density of a measurement vector.

Implements itk::Statistics::MembershipFunctionBase< TMeasurementVector >.

◆ GetCovariance()

template<typename TMeasurementVector >
virtual const CovarianceMatrixType& itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::GetCovariance ( ) const
virtual

SmartPointer class for superclass

◆ GetInverseCovariance()

template<typename TMeasurementVector >
virtual const CovarianceMatrixType& itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::GetInverseCovariance ( ) const
virtual

SmartPointer class for superclass

◆ GetMean()

template<typename TMeasurementVector >
virtual const MeanVectorType& itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::GetMean ( ) const
virtual

Get the mean of the Gaussian distribution. Mean is a vector type similar to the measurement type but with a real element type.

◆ GetNameOfClass()

template<typename TMeasurementVector >
virtual const char* itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::GetNameOfClass ( ) const
virtual

◆ InternalClone()

template<typename TMeasurementVector >
LightObject::Pointer itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::InternalClone ( ) const
overridevirtual

Method to clone a membership function, i.e. create a new instance of the same type of membership function and configure its ivars to match.

Reimplemented from itk::LightObject.

◆ New()

template<typename TMeasurementVector >
static Pointer itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::New ( )
static

SmartPointer class for superclass

◆ PrintSelf()

template<typename TMeasurementVector >
void itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::PrintSelf ( std::ostream &  os,
Indent  indent 
) const
overrideprotectedvirtual

SmartPointer class for superclass

Reimplemented from itk::Object.

◆ SetCovariance()

template<typename TMeasurementVector >
void itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::SetCovariance ( const CovarianceMatrixType cov)

Set the covariance matrix. Covariance matrix is a VariableSizeMatrix of doubles. The inverse of the covariance matrix and the normalization term for the multivariate Gaussian are calculated whenever the covaraince matrix is changed.

◆ SetMean()

template<typename TMeasurementVector >
void itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::SetMean ( const MeanVectorType mean)

Set the mean of the Gaussian distribution. Mean is a vector type similar to the measurement type but with a real element type.

Member Data Documentation

◆ m_Covariance

template<typename TMeasurementVector >
CovarianceMatrixType itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::m_Covariance
private

SmartPointer class for superclass

Definition at line 131 of file itkGaussianMembershipFunction.h.

◆ m_CovarianceNonsingular

template<typename TMeasurementVector >
bool itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::m_CovarianceNonsingular
private

Boolean to cache whether the covariance is singular or nearly singular

Definition at line 142 of file itkGaussianMembershipFunction.h.

◆ m_InverseCovariance

template<typename TMeasurementVector >
CovarianceMatrixType itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::m_InverseCovariance
private

SmartPointer class for superclass

Definition at line 135 of file itkGaussianMembershipFunction.h.

◆ m_Mean

template<typename TMeasurementVector >
MeanVectorType itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::m_Mean
private

SmartPointer class for superclass

Definition at line 130 of file itkGaussianMembershipFunction.h.

◆ m_PreFactor

template<typename TMeasurementVector >
double itk::Statistics::GaussianMembershipFunction< TMeasurementVector >::m_PreFactor
private

SmartPointer class for superclass

Definition at line 139 of file itkGaussianMembershipFunction.h.


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