#include <itkCumulativeGaussianOptimizer.h>

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.

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

const char *	GetNameOfClass () const override

std::string	GetStopConditionDescription () const override

void	PrintArray (MeasureType *array)

void	SetDataArray (MeasureType *cumGaussianArray)

void	StartOptimization () override


virtual void	SetDifferenceTolerance (double _arg)

virtual double	GetDifferenceTolerance ()

virtual void	SetVerbose (bool _arg)

virtual bool	GetVerbose ()

virtual void	VerboseOn ()

virtual void	VerboseOff ()

virtual double	GetComputedMean ()

virtual double	GetComputedStandardDeviation ()

virtual double	GetUpperAsymptote ()

virtual double	GetLowerAsymptote ()

virtual MeasureType *	GetFinalSampledArray ()

virtual double	GetFitError ()

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

const char *	GetNameOfClass () const override

virtual void	SetCostFunction (CostFunctionType *costFunction)

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

const char *	GetNameOfClass () const override

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

virtual const ParametersType &	GetCurrentPosition () const

virtual const ParametersType &	GetInitialPosition () const

const char *	GetNameOfClass () const override

virtual void	SetInitialPosition (const ParametersType &param)

void	SetScales (const ScalesType &scales)

virtual const ScalesType &	GetScales () const

virtual const ScalesType &	GetInverseScales () const

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

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 ()

Protected Member Functions
	CumulativeGaussianOptimizer ()

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

	~CumulativeGaussianOptimizer () override

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 ()

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

virtual void	SetCurrentPosition (const ParametersType &param)

	~Optimizer () override=default

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

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

virtual void	SetTimeStamp (const TimeStamp &timeStamp)

	~Object () override

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 ()

Private Member Functions
MeasureType *	ExtendGaussian (MeasureType originalArray, MeasureType extendedArray, int startingPointForInsertion)

double	FindAverageSumOfSquaredDifferences (MeasureType array1, MeasureType array2)

void	FindParametersOfGaussian (MeasureType *sampledGaussianArray)

void	MeasureGaussianParameters (MeasureType *array)

void	PrintComputedParameterHeader ()

void	PrintComputedParameters () const

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

double	VerticalBestShift (MeasureType originalArray, MeasureType newArray)

Private Attributes
double	m_ComputedAmplitude {}

double	m_ComputedMean {}

double	m_ComputedStandardDeviation {}

double	m_ComputedTransitionHeight {}

MeasureType *	m_CumulativeGaussianArray {}

double	m_DifferenceTolerance {}

MeasureType *	m_FinalSampledArray {}

double	m_FitError {}

double	m_LowerAsymptote {}

double	m_OffsetForMean {}

std::ostringstream	m_StopConditionDescription {}

double	m_UpperAsymptote {}

bool	m_Verbose {}

Additional Inherited Members
Protected Attributes inherited from itk::MultipleValuedNonLinearOptimizer
CostFunctionPointer	m_CostFunction {}

Protected Attributes inherited from itk::Optimizer
ParametersType	m_CurrentPosition {}

bool	m_ScalesInitialized { false }

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

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

Referenced by GetNameOfClass().

◆ ~CumulativeGaussianOptimizer()

itk::CumulativeGaussianOptimizer::~CumulativeGaussianOptimizer ( )

overrideprotected

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::LightObject.

◆ 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 Gaussian, compute the final parameters.

◆ GetComputedMean()

virtual double itk::CumulativeGaussianOptimizer::GetComputedMean ( )

virtual

Set and get macros.

◆ GetComputedStandardDeviation()

virtual double itk::CumulativeGaussianOptimizer::GetComputedStandardDeviation ( )

virtual

Set and get macros.

◆ GetDifferenceTolerance()

virtual double itk::CumulativeGaussianOptimizer::GetDifferenceTolerance ( )

virtual

Set and get macros.

◆ GetFinalSampledArray()

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

virtual

Set and get macros.

◆ GetFitError()

virtual double itk::CumulativeGaussianOptimizer::GetFitError ( )

virtual

Set and get macros.

◆ GetLowerAsymptote()

virtual double itk::CumulativeGaussianOptimizer::GetLowerAsymptote ( )

virtual

Set and get macros.

◆ GetNameOfClass()

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

overridevirtual

See also: LightObject::GetNameOfClass()

Reimplemented from itk::LightObject.

References CumulativeGaussianOptimizer().

◆ GetStopConditionDescription()

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

overridevirtual

Report the reason for stopping.

Reimplemented from itk::Optimizer.

◆ GetUpperAsymptote()

virtual double itk::CumulativeGaussianOptimizer::GetUpperAsymptote ( )

virtual

Set and get macros.

◆ GetVerbose()

virtual bool itk::CumulativeGaussianOptimizer::GetVerbose ( )

virtual

Set and get macros.

◆ 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

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::LightObject.

◆ RecalculateExtendedArrayFromGaussianParameters()

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

private

Recalculate the parameters of the extended Gaussian array.

◆ SetDataArray()

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

◆ SetDifferenceTolerance()

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

virtual

Set and get macros.

◆ SetVerbose()

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

virtual

Set and get macros.

◆ StartOptimization()

void itk::CumulativeGaussianOptimizer::StartOptimization ( )

overridevirtual

Start the optimizer.

Reimplemented from itk::Optimizer.

◆ VerboseOff()

virtual void itk::CumulativeGaussianOptimizer::VerboseOff ( )

virtual

Set and get macros.

◆ VerboseOn()

virtual void itk::CumulativeGaussianOptimizer::VerboseOn ( )

virtual

Set and get macros.

◆ 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 116 of file itkCumulativeGaussianOptimizer.h.

◆ m_ComputedMean

double itk::CumulativeGaussianOptimizer::m_ComputedMean {}

private

The final mean of the Cumulative Gaussian.

Definition at line 110 of file itkCumulativeGaussianOptimizer.h.

◆ m_ComputedStandardDeviation

double itk::CumulativeGaussianOptimizer::m_ComputedStandardDeviation {}

private

The final standard deviation of the Cumulative Gaussian.

Definition at line 113 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 120 of file itkCumulativeGaussianOptimizer.h.

◆ m_CumulativeGaussianArray

MeasureType* itk::CumulativeGaussianOptimizer::m_CumulativeGaussianArray {}

private

Original data array.

Definition at line 142 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 107 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 139 of file itkCumulativeGaussianOptimizer.h.

◆ m_FitError

double itk::CumulativeGaussianOptimizer::m_FitError {}

private

Least squares fit error as a measure of goodness.

Definition at line 135 of file itkCumulativeGaussianOptimizer.h.

◆ m_LowerAsymptote

double itk::CumulativeGaussianOptimizer::m_LowerAsymptote {}

private

The final lower asymptote of the Cumulative Gaussian.

Definition at line 126 of file itkCumulativeGaussianOptimizer.h.

◆ m_OffsetForMean

double itk::CumulativeGaussianOptimizer::m_OffsetForMean {}

private

Offset for the mean calculation.

Definition at line 129 of file itkCumulativeGaussianOptimizer.h.

◆ m_StopConditionDescription

std::ostringstream itk::CumulativeGaussianOptimizer::m_StopConditionDescription {}

private

Describe the stop condition

Definition at line 180 of file itkCumulativeGaussianOptimizer.h.

◆ m_UpperAsymptote

double itk::CumulativeGaussianOptimizer::m_UpperAsymptote {}

private

The final upper asymptote of the Cumulative Gaussian.

Definition at line 123 of file itkCumulativeGaussianOptimizer.h.

◆ m_Verbose

bool itk::CumulativeGaussianOptimizer::m_Verbose {}

private

Flag to print iteration results.

Definition at line 132 of file itkCumulativeGaussianOptimizer.h.

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

itkCumulativeGaussianOptimizer.h

Detailed Description

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

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()

◆ VerboseOff()

◆ VerboseOn()

◆ 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