#include <itkCumulativeGaussianOptimizer.h>

Inheritance diagram for itk::CumulativeGaussianOptimizer:

Collaboration diagram for itk::CumulativeGaussianOptimizer:

Public Types
using	ConstPointer = SmartPointer< const Self >

using	CostFunctionType = CumulativeGaussianCostFunction

using	MeasureType = CostFunctionType::MeasureType

using	Pointer = SmartPointer< Self >

using	Self = CumulativeGaussianOptimizer

using	Superclass = MultipleValuedNonLinearOptimizer

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

using	CostFunctionPointer = CostFunctionType::Pointer

using	CostFunctionType = MultipleValuedCostFunction

using	DerivativeType = Array2D< double >

using	MeasureType = Array< double >

using	ParametersType = Superclass::ParametersType

using	Pointer = SmartPointer< Self >

using	Self = MultipleValuedNonLinearOptimizer

using	Superclass = NonLinearOptimizer

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

using	ParametersType = Superclass::ParametersType

using	Pointer = SmartPointer< Self >

using	ScalesType = Superclass::ScalesType

using	Self = NonLinearOptimizer

using	Superclass = Optimizer

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

using	ParametersType = OptimizerParameters< double >

using	Pointer = SmartPointer< Self >

using	ScalesType = Array< double >

using	Self = Optimizer

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

Public Member Functions
virtual ::itk::LightObject::Pointer	CreateAnother () const

virtual const char *	GetNameOfClass () const

Public Member Functions inherited from itk::MultipleValuedNonLinearOptimizer
virtual ::itk::LightObject::Pointer	CreateAnother () const

virtual void	SetCostFunction (CostFunctionType *costFunction)

Public Member Functions inherited from itk::NonLinearOptimizer
virtual ::itk::LightObject::Pointer	CreateAnother () const

Public Member Functions inherited from itk::Optimizer
virtual ::itk::LightObject::Pointer	CreateAnother () const

virtual const ParametersType &	GetInitialPosition () const

virtual void	SetInitialPosition (const ParametersType &param)

void	SetScales (const ScalesType &scales)

virtual const ScalesType &	GetScales () const

virtual const ScalesType &	GetInverseScales () const

virtual const ParametersType &	GetCurrentPosition () const

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
static Pointer	New ()

Static Public Member Functions inherited from itk::MultipleValuedNonLinearOptimizer
static Pointer	New ()

Static Public Member Functions inherited from itk::NonLinearOptimizer
static Pointer	New ()

Static Public Member Functions inherited from itk::Optimizer
static Pointer	New ()

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 ()

double	m_DifferenceTolerance

double	m_ComputedMean

double	m_ComputedStandardDeviation

double	m_ComputedAmplitude

double	m_ComputedTransitionHeight

double	m_UpperAsymptote

double	m_LowerAsymptote

double	m_OffsetForMean

bool	m_Verbose

double	m_FitError

MeasureType *	m_FinalSampledArray

MeasureType *	m_CumulativeGaussianArray

std::ostringstream	m_StopConditionDescription

virtual void	SetDifferenceTolerance (double _arg)

virtual double	GetDifferenceTolerance ()

virtual void	SetVerbose (bool _arg)

virtual bool	GetVerbose ()

virtual double	GetComputedMean ()

virtual double	GetComputedStandardDeviation ()

virtual double	GetUpperAsymptote ()

virtual double	GetLowerAsymptote ()

virtual MeasureType *	GetFinalSampledArray ()

virtual double	GetFitError ()

void	SetDataArray (MeasureType *cumGaussianArray)

void	StartOptimization () override

void	PrintArray (MeasureType *array)

const std::string	GetStopConditionDescription () const override

	CumulativeGaussianOptimizer ()

	~CumulativeGaussianOptimizer () override

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

MeasureType *	ExtendGaussian (MeasureType originalArray, MeasureType extendedArray, int startingPointForInsertion)

MeasureType *	RecalculateExtendedArrayFromGaussianParameters (MeasureType originalArray, MeasureType extendedArray, int startingPointForInsertion) const

double	FindAverageSumOfSquaredDifferences (MeasureType array1, MeasureType array2)

void	FindParametersOfGaussian (MeasureType *sampledGaussianArray)

void	MeasureGaussianParameters (MeasureType *array)

void	PrintComputedParameterHeader ()

void	PrintComputedParameters () const

double	VerticalBestShift (MeasureType originalArray, MeasureType newArray)

Additional Inherited Members
Protected Member Functions inherited from itk::MultipleValuedNonLinearOptimizer
	MultipleValuedNonLinearOptimizer ()

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

	~MultipleValuedNonLinearOptimizer () override=default

Protected Member Functions inherited from itk::NonLinearOptimizer
	NonLinearOptimizer ()=default

	~NonLinearOptimizer () override

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

	~Optimizer () override=default

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

virtual void	SetCurrentPosition (const ParametersType &param)

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::MultipleValuedNonLinearOptimizer
CostFunctionPointer	m_CostFunction

Protected Attributes inherited from itk::Optimizer
bool	m_ScalesInitialized { false }

ParametersType	m_CurrentPosition

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

Detailed Description

This is an optimizer specific to estimating the parameters of Cumulative Gaussian sampled data.

This optimizer will only work if the data array is sampled from a Cumulative Gaussian curve. It's more of a curve fitter than an optimizer, with the advantage of being fast and specific. It works by taking the derivative of the Cumulative Gaussian sample then repeatedly extending the tails of the Gaussian and recalculating the Gaussian parameters until the change in iterations is within tolerance or very small. The Gaussian is then integrated to reproduce the Cumulative Gaussian and the asymptotes are estimated by using least squares fit to estimate the constant from integration.

Definition at line 48 of file itkCumulativeGaussianOptimizer.h.

Member Typedef Documentation

◆ ConstPointer

using itk::CumulativeGaussianOptimizer::ConstPointer = SmartPointer<const Self>

Definition at line 55 of file itkCumulativeGaussianOptimizer.h.

◆ CostFunctionType

using itk::CumulativeGaussianOptimizer::CostFunctionType = CumulativeGaussianCostFunction

Cost function type alias. NOTE: This optimizer is specific to fitting a Cumulative Gaussian.

Definition at line 59 of file itkCumulativeGaussianOptimizer.h.

◆ MeasureType

using itk::CumulativeGaussianOptimizer::MeasureType = CostFunctionType::MeasureType

Data array type alias.

Definition at line 62 of file itkCumulativeGaussianOptimizer.h.

◆ Pointer

using itk::CumulativeGaussianOptimizer::Pointer = SmartPointer<Self>

Definition at line 54 of file itkCumulativeGaussianOptimizer.h.

◆ Self

using itk::CumulativeGaussianOptimizer::Self = CumulativeGaussianOptimizer

Standard type alias.

Definition at line 52 of file itkCumulativeGaussianOptimizer.h.

◆ Superclass

using itk::CumulativeGaussianOptimizer::Superclass = MultipleValuedNonLinearOptimizer

Definition at line 53 of file itkCumulativeGaussianOptimizer.h.

Constructor & Destructor Documentation

◆ CumulativeGaussianOptimizer()

itk::CumulativeGaussianOptimizer::CumulativeGaussianOptimizer ( )

protected

When to stop the iteration for the Gaussian extension loop.

◆ ~CumulativeGaussianOptimizer()

itk::CumulativeGaussianOptimizer::~CumulativeGaussianOptimizer ( )

overrideprotected

When to stop the iteration for the Gaussian extension loop.

Member Function Documentation

◆ CreateAnother()

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

virtual

Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class.

Reimplemented from itk::Object.

◆ ExtendGaussian()

MeasureType* itk::CumulativeGaussianOptimizer::ExtendGaussian	(	MeasureType *	originalArray,
		MeasureType *	extendedArray,
		int	startingPointForInsertion
	)

private

Extend the tails of the Gaussian.

◆ FindAverageSumOfSquaredDifferences()

double itk::CumulativeGaussianOptimizer::FindAverageSumOfSquaredDifferences	(	MeasureType *	array1,
		MeasureType *	array2
	)

private

Calculates the squared difference error between each Gaussian iteration loop.

◆ FindParametersOfGaussian()

void itk::CumulativeGaussianOptimizer::FindParametersOfGaussian ( MeasureType * sampledGaussianArray )

private

Given an array sampled from a Gaussin, compute the final parameters.

◆ GetComputedMean()

virtual double itk::CumulativeGaussianOptimizer::GetComputedMean ( )

virtual

When to stop the iteration for the Gaussian extension loop.

◆ GetComputedStandardDeviation()

virtual double itk::CumulativeGaussianOptimizer::GetComputedStandardDeviation ( )

virtual

When to stop the iteration for the Gaussian extension loop.

◆ GetDifferenceTolerance()

virtual double itk::CumulativeGaussianOptimizer::GetDifferenceTolerance ( )

virtual

When to stop the iteration for the Gaussian extension loop.

◆ GetFinalSampledArray()

virtual MeasureType* itk::CumulativeGaussianOptimizer::GetFinalSampledArray ( )

virtual

When to stop the iteration for the Gaussian extension loop.

◆ GetFitError()

virtual double itk::CumulativeGaussianOptimizer::GetFitError ( )

virtual

When to stop the iteration for the Gaussian extension loop.

◆ GetLowerAsymptote()

virtual double itk::CumulativeGaussianOptimizer::GetLowerAsymptote ( )

virtual

When to stop the iteration for the Gaussian extension loop.

◆ GetNameOfClass()

virtual const char* itk::CumulativeGaussianOptimizer::GetNameOfClass ( ) const

virtual

Run-time type information (and related methods).

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

◆ GetStopConditionDescription()

const std::string itk::CumulativeGaussianOptimizer::GetStopConditionDescription ( ) const

overridevirtual

Report the reason for stopping.

Reimplemented from itk::Optimizer.

◆ GetUpperAsymptote()

virtual double itk::CumulativeGaussianOptimizer::GetUpperAsymptote ( )

virtual

When to stop the iteration for the Gaussian extension loop.

◆ GetVerbose()

virtual bool itk::CumulativeGaussianOptimizer::GetVerbose ( )

virtual

When to stop the iteration for the Gaussian extension loop.

◆ MeasureGaussianParameters()

void itk::CumulativeGaussianOptimizer::MeasureGaussianParameters ( MeasureType * array )

private

Measure the parameters of a Gaussian sampled array.

◆ New()

static Pointer itk::CumulativeGaussianOptimizer::New ( )

static

Method for creation through the object factory.

◆ PrintArray()

void itk::CumulativeGaussianOptimizer::PrintArray ( MeasureType * array )

Print an array.

◆ PrintComputedParameterHeader()

void itk::CumulativeGaussianOptimizer::PrintComputedParameterHeader ( )

private

Print the header for output table.

◆ PrintComputedParameters()

void itk::CumulativeGaussianOptimizer::PrintComputedParameters ( ) const

private

Print the computed parameters.

◆ PrintSelf()

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

overrideprotectedvirtual

When to stop the iteration for the Gaussian extension loop.

Reimplemented from itk::Object.

◆ RecalculateExtendedArrayFromGaussianParameters()

MeasureType* itk::CumulativeGaussianOptimizer::RecalculateExtendedArrayFromGaussianParameters	(	MeasureType *	originalArray,
		MeasureType *	extendedArray,
		int	startingPointForInsertion
	)		const

private

Recalulate the parameters of the extended Gaussian array.

◆ SetDataArray()

void itk::CumulativeGaussianOptimizer::SetDataArray ( MeasureType * cumGaussianArray )

When to stop the iteration for the Gaussian extension loop.

◆ SetDifferenceTolerance()

virtual void itk::CumulativeGaussianOptimizer::SetDifferenceTolerance ( double _arg )

virtual

Set and get macros.

◆ SetVerbose()

virtual void itk::CumulativeGaussianOptimizer::SetVerbose ( bool _arg )

virtual

When to stop the iteration for the Gaussian extension loop.

◆ StartOptimization()

void itk::CumulativeGaussianOptimizer::StartOptimization ( )

overridevirtual

Start the optimizer.

Reimplemented from itk::Optimizer.

◆ VerticalBestShift()

double itk::CumulativeGaussianOptimizer::VerticalBestShift	(	MeasureType *	originalArray,
		MeasureType *	newArray
	)

private

Find the constant of the integrated sample.

Member Data Documentation

◆ m_ComputedAmplitude

double itk::CumulativeGaussianOptimizer::m_ComputedAmplitude

private

The final amplitude of the Gaussian.

Definition at line 115 of file itkCumulativeGaussianOptimizer.h.

◆ m_ComputedMean

double itk::CumulativeGaussianOptimizer::m_ComputedMean

private

The final mean of the Cumulative Gaussian.

Definition at line 109 of file itkCumulativeGaussianOptimizer.h.

◆ m_ComputedStandardDeviation

double itk::CumulativeGaussianOptimizer::m_ComputedStandardDeviation

private

The final standard deviation of the Cumulative Gaussian.

Definition at line 112 of file itkCumulativeGaussianOptimizer.h.

◆ m_ComputedTransitionHeight

double itk::CumulativeGaussianOptimizer::m_ComputedTransitionHeight

private

The transition height (distance between upper and lower asymptotes) of the Cumulative Gaussian.

Definition at line 119 of file itkCumulativeGaussianOptimizer.h.

◆ m_CumulativeGaussianArray

MeasureType* itk::CumulativeGaussianOptimizer::m_CumulativeGaussianArray

private

Original data array.

Definition at line 141 of file itkCumulativeGaussianOptimizer.h.

◆ m_DifferenceTolerance

double itk::CumulativeGaussianOptimizer::m_DifferenceTolerance

private

When to stop the iteration for the Gaussian extension loop.

Definition at line 106 of file itkCumulativeGaussianOptimizer.h.

◆ m_FinalSampledArray

MeasureType* itk::CumulativeGaussianOptimizer::m_FinalSampledArray

private

Array of values computed from the final parameters of the Cumulative Gaussian.

Definition at line 138 of file itkCumulativeGaussianOptimizer.h.

◆ m_FitError

double itk::CumulativeGaussianOptimizer::m_FitError

private

Least squares fit error as a measure of goodness.

Definition at line 134 of file itkCumulativeGaussianOptimizer.h.

◆ m_LowerAsymptote

double itk::CumulativeGaussianOptimizer::m_LowerAsymptote

private

The final lower asymptote of the Cumulative Gaussian.

Definition at line 125 of file itkCumulativeGaussianOptimizer.h.

◆ m_OffsetForMean

double itk::CumulativeGaussianOptimizer::m_OffsetForMean

private

Offset for the mean calculation.

Definition at line 128 of file itkCumulativeGaussianOptimizer.h.

◆ m_StopConditionDescription

std::ostringstream itk::CumulativeGaussianOptimizer::m_StopConditionDescription

private

Describe the stop condition

Definition at line 179 of file itkCumulativeGaussianOptimizer.h.

◆ m_UpperAsymptote

double itk::CumulativeGaussianOptimizer::m_UpperAsymptote

private

The final upper asymptote of the Cumulative Gaussian.

Definition at line 122 of file itkCumulativeGaussianOptimizer.h.

◆ m_Verbose

bool itk::CumulativeGaussianOptimizer::m_Verbose

private

Flag to print iteration results.

Definition at line 131 of file itkCumulativeGaussianOptimizer.h.

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

itkCumulativeGaussianOptimizer.h

Public Types

Public Member Functions

Static Public Member Functions

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ ConstPointer

◆ CostFunctionType

◆ MeasureType

◆ Pointer

◆ Self

◆ Superclass

Constructor & Destructor Documentation

◆ CumulativeGaussianOptimizer()

◆ ~CumulativeGaussianOptimizer()

Member Function Documentation

◆ CreateAnother()

◆ ExtendGaussian()

◆ FindAverageSumOfSquaredDifferences()

◆ FindParametersOfGaussian()

◆ GetComputedMean()

◆ GetComputedStandardDeviation()

◆ GetDifferenceTolerance()

◆ GetFinalSampledArray()

◆ GetFitError()

◆ GetLowerAsymptote()

◆ GetNameOfClass()

◆ GetStopConditionDescription()

◆ GetUpperAsymptote()

◆ GetVerbose()

◆ MeasureGaussianParameters()

◆ New()

◆ PrintArray()

◆ PrintComputedParameterHeader()

◆ PrintComputedParameters()

◆ PrintSelf()

◆ RecalculateExtendedArrayFromGaussianParameters()

◆ SetDataArray()

◆ SetDifferenceTolerance()

◆ SetVerbose()

◆ StartOptimization()

◆ VerticalBestShift()

Member Data Documentation

◆ m_ComputedAmplitude

◆ m_ComputedMean

◆ m_ComputedStandardDeviation

◆ m_ComputedTransitionHeight

◆ m_CumulativeGaussianArray

◆ m_DifferenceTolerance

◆ m_FinalSampledArray

◆ m_FitError

◆ m_LowerAsymptote

◆ m_OffsetForMean

◆ m_StopConditionDescription

◆ m_UpperAsymptote

◆ m_Verbose