#include <itkQuasiNewtonOptimizerv4.h>

Inheritance diagram for itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >:

Collaboration diagram for itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >:

Public Types
using	ConstPointer = SmartPointer< const Self >

using	DerivativeType = typename Superclass::DerivativeType

using	HessianArrayType = std::vector< HessianType >

using	HessianType = itk::Array2D< TInternalComputationValueType >

using	IndexRangeType = typename Superclass::IndexRangeType

using	InternalComputationValueType = TInternalComputationValueType

using	MeasureType = typename Superclass::MeasureType

using	ParametersType = typename Superclass::ParametersType

using	Pointer = SmartPointer< Self >

using	Self = QuasiNewtonOptimizerv4Template

using	Superclass = GradientDescentOptimizerv4Template< TInternalComputationValueType >

Public Types inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >
using	ConstPointer = SmartPointer< const Self >

using	DerivativeType = typename Superclass::DerivativeType

using	IndexRangeType = typename Superclass::IndexRangeType

using	InternalComputationValueType = TInternalComputationValueType

using	MeasureType = typename Superclass::MeasureType

using	ParametersType = typename Superclass::ParametersType

using	Pointer = SmartPointer< Self >

using	ScalesType = typename Superclass::ScalesType

using	Self = GradientDescentOptimizerv4Template

using	Superclass = GradientDescentOptimizerBasev4Template< TInternalComputationValueType >

Public Types inherited from itk::GradientDescentOptimizerBasev4Template< TInternalComputationValueType >
using	ConstPointer = SmartPointer< const Self >

using	ConvergenceMonitoringType = itk::Function::WindowConvergenceMonitoringFunction< TInternalComputationValueType >

using	DerivativeType = typename Superclass::DerivativeType

using	InternalComputationValueType = TInternalComputationValueType

using	MeasureType = typename Superclass::MeasureType

using	MetricType = typename Superclass::MetricType

using	MetricTypePointer = typename MetricType::Pointer

using	ParametersType = typename Superclass::ParametersType

using	Pointer = SmartPointer< Self >

using	ScalesType = typename Superclass::ScalesType

using	Self = GradientDescentOptimizerBasev4Template

using	StopConditionDescriptionType = typename Superclass::StopConditionDescriptionType

using	StopConditionReturnStringType = typename Superclass::StopConditionReturnStringType

using	Superclass = ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType >

using	IndexRangeType = ThreadedIndexedContainerPartitioner::IndexRangeType

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

using	DerivativeType = typename MetricType::DerivativeType

using	MeasureType = typename MetricType::MeasureType

using	MetricType = ObjectToObjectMetricBaseTemplate< TInternalComputationValueType >

using	MetricTypePointer = typename MetricType::Pointer

using	NumberOfParametersType = typename MetricType::NumberOfParametersType

using	ParametersType = OptimizerParameters< TInternalComputationValueType >

using	Pointer = SmartPointer< Self >

using	ScalesEstimatorType = OptimizerParameterScalesEstimatorTemplate< TInternalComputationValueType >

using	ScalesType = OptimizerParameters< TInternalComputationValueType >

using	Self = ObjectToObjectOptimizerBaseTemplate

using	StopConditionDescriptionType = std::ostringstream

using	StopConditionReturnStringType = std::string

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 void	EstimateNewtonStepOverSubRange (const IndexRangeType &subrange)

virtual const char *	GetNameOfClass () const

virtual const DerivativeType &	GetNewtonStep () const

virtual void	SetMaximumIterationsWithoutProgress (SizeValueType _arg)

virtual void	SetMaximumNewtonStepSizeInPhysicalUnits (TInternalComputationValueType _arg)

void	StartOptimization (bool doOnlyInitialization=false) override

Public Member Functions inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >
virtual void	SetLearningRate (TInternalComputationValueType _arg)

virtual const TInternalComputationValueType &	GetLearningRate () const

virtual void	SetMaximumStepSizeInPhysicalUnits (TInternalComputationValueType _arg)

virtual const TInternalComputationValueType &	GetMaximumStepSizeInPhysicalUnits () const

virtual void	SetDoEstimateLearningRateAtEachIteration (bool _arg)

virtual const bool &	GetDoEstimateLearningRateAtEachIteration () const

virtual void	DoEstimateLearningRateAtEachIterationOn ()

virtual void	DoEstimateLearningRateAtEachIterationOff ()

virtual void	SetDoEstimateLearningRateOnce (bool _arg)

virtual const bool &	GetDoEstimateLearningRateOnce () const

virtual void	DoEstimateLearningRateOnceOn ()

virtual void	DoEstimateLearningRateOnceOff ()

virtual void	SetMinimumConvergenceValue (TInternalComputationValueType _arg)

virtual void	SetConvergenceWindowSize (SizeValueType _arg)

virtual const TInternalComputationValueType &	GetConvergenceValue () const

virtual void	SetReturnBestParametersAndValue (bool _arg)

virtual const bool &	GetReturnBestParametersAndValue () const

virtual void	ReturnBestParametersAndValueOn ()

virtual void	ReturnBestParametersAndValueOff ()

void	StopOptimization () override

void	ResumeOptimization () override

virtual void	EstimateLearningRate ()

Public Member Functions inherited from itk::GradientDescentOptimizerBasev4Template< TInternalComputationValueType >
virtual const DerivativeType &	GetGradient () const

virtual const StopConditionObjectToObjectOptimizerEnum &	GetStopCondition () const

void	SetNumberOfIterations (const SizeValueType numberOfIterations) override

SizeValueType	GetNumberOfIterations () const override

SizeValueType	GetCurrentIteration () const override

const StopConditionReturnStringType	GetStopConditionDescription () const override

virtual void	ModifyGradientByScales ()

virtual void	ModifyGradientByLearningRate ()

Public Member Functions inherited from itk::ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType >
virtual void	SetMetric (MetricType *_arg)

virtual MetricType *	GetModifiableMetric ()

virtual const MetricType *	GetMetric () const

virtual const MeasureType &	GetCurrentMetricValue () const

virtual const MeasureType &	GetValue () const

virtual void	SetScales (const ScalesType &scales)

virtual const ScalesType &	GetScales () const

virtual const bool &	GetScalesAreIdentity () const

virtual void	SetWeights (ScalesType _arg)

virtual const ScalesType &	GetWeights () const

virtual const bool &	GetWeightsAreIdentity () const

bool	GetScalesInitialized () const

virtual void	SetScalesEstimator (ScalesEstimatorType *_arg)

virtual void	SetDoEstimateScales (bool _arg)

virtual const bool &	GetDoEstimateScales () const

virtual void	DoEstimateScalesOn ()

virtual void	DoEstimateScalesOff ()

virtual void	SetNumberOfWorkUnits (ThreadIdType number)

virtual const ThreadIdType &	GetNumberOfWorkUnits () 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::GradientDescentOptimizerv4Template< TInternalComputationValueType >
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
void	AdvanceOneStep () override

void	CombineGradientNewtonStep ()

virtual bool	ComputeHessianAndStepWithBFGS (IndexValueType loc)

virtual void	EstimateNewtonStep ()

void	ModifyCombinedNewtonStep ()

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

	QuasiNewtonOptimizerv4Template ()

virtual void	ResetNewtonStep (IndexValueType loc)

	~QuasiNewtonOptimizerv4Template () override=default

Protected Member Functions inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >
void	ModifyGradientByScalesOverSubRange (const IndexRangeType &subrange) override

void	ModifyGradientByLearningRateOverSubRange (const IndexRangeType &subrange) override

	GradientDescentOptimizerv4Template ()

	~GradientDescentOptimizerv4Template () override=default

Protected Member Functions inherited from itk::GradientDescentOptimizerBasev4Template< TInternalComputationValueType >
	GradientDescentOptimizerBasev4Template ()

	~GradientDescentOptimizerBasev4Template () override=default

Protected Member Functions inherited from itk::ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType >
	ObjectToObjectOptimizerBaseTemplate ()

	~ObjectToObjectOptimizerBaseTemplate () override

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
SizeValueType	m_BestIteration { 0 }

ParametersType	m_BestPosition

MeasureType	m_BestValue

ParametersType	m_CurrentPosition

HessianArrayType	m_HessianArray

SizeValueType	m_MaximumIterationsWithoutProgress { 30 }

TInternalComputationValueType	m_MaximumNewtonStepSizeInPhysicalUnits

DerivativeType	m_NewtonStep

std::vector< bool >	m_NewtonStepValidFlags

std::string	m_NewtonStepWarning

ParametersType	m_OptimalStep

ParametersType	m_PreviousPosition

MeasureType	m_PreviousValue

Protected Attributes inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >
TInternalComputationValueType	m_LearningRate

TInternalComputationValueType	m_MinimumConvergenceValue

TInternalComputationValueType	m_ConvergenceValue

MeasureType	m_CurrentBestValue

ParametersType	m_BestParameters

bool	m_ReturnBestParametersAndValue { false }

DerivativeType	m_PreviousGradient

Protected Attributes inherited from itk::GradientDescentOptimizerBasev4Template< TInternalComputationValueType >
bool	m_DoEstimateLearningRateAtEachIteration

bool	m_DoEstimateLearningRateOnce

TInternalComputationValueType	m_MaximumStepSizeInPhysicalUnits

bool	m_UseConvergenceMonitoring

SizeValueType	m_ConvergenceWindowSize

ConvergenceMonitoringType::Pointer	m_ConvergenceMonitoring

DomainThreader< ThreadedIndexedContainerPartitioner, Self >::Pointer	m_ModifyGradientByScalesThreader

DomainThreader< ThreadedIndexedContainerPartitioner, Self >::Pointer	m_ModifyGradientByLearningRateThreader

bool	m_Stop { false }

StopConditionObjectToObjectOptimizerEnum	m_StopCondition

StopConditionDescriptionType	m_StopConditionDescription

DerivativeType	m_Gradient

Protected Attributes inherited from itk::ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType >
MetricTypePointer	m_Metric

ThreadIdType	m_NumberOfWorkUnits

SizeValueType	m_CurrentIteration

SizeValueType	m_NumberOfIterations

MeasureType	m_CurrentMetricValue

ScalesType	m_Scales

ScalesType	m_Weights

bool	m_ScalesAreIdentity

ScalesEstimatorType::Pointer	m_ScalesEstimator

bool	m_WeightsAreIdentity

bool	m_DoEstimateScales

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

Private Attributes
DomainThreader< ThreadedIndexedContainerPartitioner, Self >::Pointer	m_EstimateNewtonStepThreader

Detailed Description

template<typename TInternalComputationValueType>
class itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >

Implement a Quasi-Newton optimizer with BFGS Hessian estimation.

Second order approximation of the cost function is usually more efficient since it estimates the descent or ascent direction more precisely. However, computation of Hessian is usually expensive or unavailable. Alternatively Quasi-Newton methods can estimate a Hessian from the gradients in previous steps. Here a specific Quasi-Newton method, BFGS, is used to compute the Quasi-Newton steps.

The Quasi-Newton method doesn't produce a valid step sometimes, ex. when the metric function is not a convex locally. In this scenario, the gradient step is used after being scaled properly.

A helper member object, m_ScalesEstimator may be set to estimate parameter scales and step scales. A step scale measures the magnitude of a step and is used for learning rate computation.

When m_ScalesEstimator is set, SetMaximumNewtonStepSizeInPhysicalUnits() may be called to set the maximum step size. If it is not called, m_MaximumNewtonStepSizeInPhysicalUnits defaults to lambda * OptimizerParameterScalesEstimatorTemplate::EstimateMaximumStepSize(), where lambda is in [1,5].

When m_ScalesEstimator is not set, the parameter scales and learning rates defaults to ones, or can be set by users manually.

Definition at line 60 of file itkQuasiNewtonOptimizerv4.h.

Member Typedef Documentation

◆ ConstPointer

template<typename TInternalComputationValueType >

using itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::ConstPointer = SmartPointer<const Self>

Definition at line 70 of file itkQuasiNewtonOptimizerv4.h.

◆ DerivativeType

template<typename TInternalComputationValueType >

using itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::DerivativeType = typename Superclass::DerivativeType

Definition at line 83 of file itkQuasiNewtonOptimizerv4.h.

◆ HessianArrayType

template<typename TInternalComputationValueType >

using itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::HessianArrayType = std::vector<HessianType>

Type for an array of Hessian matrix for local support

Definition at line 90 of file itkQuasiNewtonOptimizerv4.h.

◆ HessianType

template<typename TInternalComputationValueType >

using itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::HessianType = itk::Array2D<TInternalComputationValueType>

Type for Hessian matrix in the Quasi-Newton method

Definition at line 87 of file itkQuasiNewtonOptimizerv4.h.

◆ IndexRangeType

template<typename TInternalComputationValueType >

using itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::IndexRangeType = typename Superclass::IndexRangeType

Definition at line 84 of file itkQuasiNewtonOptimizerv4.h.

◆ InternalComputationValueType

template<typename TInternalComputationValueType >

using itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::InternalComputationValueType = TInternalComputationValueType

It should be possible to derive the internal computation type from the class object.

Definition at line 79 of file itkQuasiNewtonOptimizerv4.h.

◆ MeasureType

template<typename TInternalComputationValueType >

using itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::MeasureType = typename Superclass::MeasureType

Definition at line 82 of file itkQuasiNewtonOptimizerv4.h.

◆ ParametersType

template<typename TInternalComputationValueType >

using itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::ParametersType = typename Superclass::ParametersType

Definition at line 81 of file itkQuasiNewtonOptimizerv4.h.

◆ Pointer

template<typename TInternalComputationValueType >

using itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::Pointer = SmartPointer<Self>

Definition at line 69 of file itkQuasiNewtonOptimizerv4.h.

◆ Self

template<typename TInternalComputationValueType >

using itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::Self = QuasiNewtonOptimizerv4Template

Standard class type aliases.

Definition at line 67 of file itkQuasiNewtonOptimizerv4.h.

◆ Superclass

template<typename TInternalComputationValueType >

using itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::Superclass = GradientDescentOptimizerv4Template<TInternalComputationValueType>

Definition at line 68 of file itkQuasiNewtonOptimizerv4.h.

Constructor & Destructor Documentation

◆ QuasiNewtonOptimizerv4Template()

template<typename TInternalComputationValueType >

itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::QuasiNewtonOptimizerv4Template ( )

protected

◆ ~QuasiNewtonOptimizerv4Template()

template<typename TInternalComputationValueType >

itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::~QuasiNewtonOptimizerv4Template ( )

overrideprotecteddefault

Member Function Documentation

◆ AdvanceOneStep()

template<typename TInternalComputationValueType >

void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::AdvanceOneStep ( )

overrideprotectedvirtual

Advance one step using the Quasi-Newton step. When the Newton step is invalid, the gradient step will be used.

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

◆ CombineGradientNewtonStep()

template<typename TInternalComputationValueType >

void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::CombineGradientNewtonStep ( )

protected

Combine a gradient step with a Newton step. The Newton step will be used when it is valid. Otherwise the gradient step will be used.

◆ ComputeHessianAndStepWithBFGS()

template<typename TInternalComputationValueType >

virtual bool itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::ComputeHessianAndStepWithBFGS ( IndexValueType loc )

protectedvirtual

Estimate the next Hessian and step with BFGS method. The details of the method are described at http://en.wikipedia.org/wiki/BFGS_method .

◆ CreateAnother()

template<typename TInternalComputationValueType >

virtual::itk::LightObject::Pointer itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::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::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

◆ EstimateNewtonStep()

template<typename TInternalComputationValueType >

virtual void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::EstimateNewtonStep ( )

protectedvirtual

Estimate a Newton step

◆ EstimateNewtonStepOverSubRange()

template<typename TInternalComputationValueType >

virtual void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::EstimateNewtonStepOverSubRange ( const IndexRangeType & subrange )

virtual

Estimate the quasi-newton step over a given index range. This function is used in QuasiNewtonOptimizerv4EstimateNewtonStepThreaderTemplate class.

◆ GetNameOfClass()

template<typename TInternalComputationValueType >

virtual const char* itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::GetNameOfClass ( ) const

virtual

Run-time type information (and related methods).

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

◆ GetNewtonStep()

template<typename TInternalComputationValueType >

virtual const DerivativeType& itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::GetNewtonStep ( ) const

virtual

Get the most recent Newton step.

◆ ModifyCombinedNewtonStep()

template<typename TInternalComputationValueType >

void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::ModifyCombinedNewtonStep ( )

protected

Estimate and apply the learning rate(s) for a combined Newton step. A combined Newton step uses the Newton step by default and the gradient step when the Newton step is not valid.

The learning rate is less than 1.0 and is restricted by m_MaximumNewtonStepSizeInPhysicalUnits.

◆ New()

template<typename TInternalComputationValueType >

static Pointer itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::New ( )

static

Method for creation through the object factory.

◆ PrintSelf()

template<typename TInternalComputationValueType >

void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::PrintSelf	(	std::ostream &	os,
		Indent	indent
	)		const

overrideprotectedvirtual

Store the best value and related parameters.

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

◆ ResetNewtonStep()

template<typename TInternalComputationValueType >

virtual void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::ResetNewtonStep ( IndexValueType loc )

protectedvirtual

Reset the Hessian to identity matrix and the Newton step to zeros.

◆ SetMaximumIterationsWithoutProgress()

template<typename TInternalComputationValueType >

virtual void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::SetMaximumIterationsWithoutProgress ( SizeValueType _arg )

virtual

Set the maximum tolerable number of iteration without any progress

◆ SetMaximumNewtonStepSizeInPhysicalUnits()

template<typename TInternalComputationValueType >

virtual void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::SetMaximumNewtonStepSizeInPhysicalUnits ( TInternalComputationValueType _arg )

virtual

Set the maximum step size.

When SetScalesEstimator is called by user, the optimizer will compute learning rates as m_MaximumNewtonStepSizeInPhysicalUnits / m_ScalesEstimator->EstimateStepScale(newtonStep).

If SetMaximumNewtonStepSizeInPhysicalUnits is not called by user, m_MaximumNewtonStepSizeInPhysicalUnits defaults to lambda * m_ScalesEstimator->EstimateMaximumStepSize(),

where EstimateMaximumStepSize returns one voxel spacing and lambda may be in [1,5] according to our experience.

◆ StartOptimization()

template<typename TInternalComputationValueType >

void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::StartOptimization ( bool doOnlyInitialization = false )

overridevirtual

Start and run the optimization

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

Member Data Documentation

◆ m_BestIteration

template<typename TInternalComputationValueType >

SizeValueType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_BestIteration { 0 }

protected

Definition at line 140 of file itkQuasiNewtonOptimizerv4.h.

◆ m_BestPosition

template<typename TInternalComputationValueType >

ParametersType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_BestPosition

protected

Definition at line 139 of file itkQuasiNewtonOptimizerv4.h.

◆ m_BestValue

template<typename TInternalComputationValueType >

MeasureType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_BestValue

protected

The best value so far and relevant information

Definition at line 138 of file itkQuasiNewtonOptimizerv4.h.

◆ m_CurrentPosition

template<typename TInternalComputationValueType >

ParametersType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_CurrentPosition

protected

The information about the current step

Definition at line 130 of file itkQuasiNewtonOptimizerv4.h.

◆ m_EstimateNewtonStepThreader

template<typename TInternalComputationValueType >

DomainThreader<ThreadedIndexedContainerPartitioner, Self>::Pointer itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_EstimateNewtonStepThreader

private

Threader for Newton step estimation.

Definition at line 205 of file itkQuasiNewtonOptimizerv4.h.

◆ m_HessianArray

template<typename TInternalComputationValueType >

HessianArrayType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_HessianArray

protected

The Hessian with local support

Definition at line 152 of file itkQuasiNewtonOptimizerv4.h.

◆ m_MaximumIterationsWithoutProgress

template<typename TInternalComputationValueType >

SizeValueType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_MaximumIterationsWithoutProgress { 30 }

protected

The maximum tolerable number of iteration without any progress

Definition at line 127 of file itkQuasiNewtonOptimizerv4.h.

◆ m_MaximumNewtonStepSizeInPhysicalUnits

template<typename TInternalComputationValueType >

TInternalComputationValueType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_MaximumNewtonStepSizeInPhysicalUnits

protected

The maximum Quasi-Newton step size to restrict learning rates.

Definition at line 149 of file itkQuasiNewtonOptimizerv4.h.

◆ m_NewtonStep

template<typename TInternalComputationValueType >

DerivativeType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_NewtonStep

protected

The Quasi-Newton step

Definition at line 143 of file itkQuasiNewtonOptimizerv4.h.

◆ m_NewtonStepValidFlags

template<typename TInternalComputationValueType >

std::vector<bool> itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_NewtonStepValidFlags

protected

Valid flag for the Quasi-Newton steps

Definition at line 155 of file itkQuasiNewtonOptimizerv4.h.

◆ m_NewtonStepWarning

template<typename TInternalComputationValueType >

std::string itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_NewtonStepWarning

protected

Warning message during Quasi-Newton step estimation

Definition at line 146 of file itkQuasiNewtonOptimizerv4.h.

◆ m_OptimalStep

template<typename TInternalComputationValueType >

ParametersType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_OptimalStep

protected

Definition at line 131 of file itkQuasiNewtonOptimizerv4.h.

◆ m_PreviousPosition

template<typename TInternalComputationValueType >

ParametersType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_PreviousPosition

protected

Definition at line 135 of file itkQuasiNewtonOptimizerv4.h.

◆ m_PreviousValue

template<typename TInternalComputationValueType >

MeasureType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_PreviousValue

protected

The information about the previous step

Definition at line 134 of file itkQuasiNewtonOptimizerv4.h.

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

itkQuasiNewtonOptimizerv4.h

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Protected Attributes

Private Attributes

Detailed Description

template<typename TInternalComputationValueType> class itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >

Member Typedef Documentation

◆ ConstPointer

◆ DerivativeType

◆ HessianArrayType

◆ HessianType

◆ IndexRangeType

◆ InternalComputationValueType

◆ MeasureType

◆ ParametersType

◆ Pointer

◆ Self

◆ Superclass

Constructor & Destructor Documentation

◆ QuasiNewtonOptimizerv4Template()

◆ ~QuasiNewtonOptimizerv4Template()

Member Function Documentation

◆ AdvanceOneStep()

◆ CombineGradientNewtonStep()

◆ ComputeHessianAndStepWithBFGS()

◆ CreateAnother()

◆ EstimateNewtonStep()

◆ EstimateNewtonStepOverSubRange()

◆ GetNameOfClass()

◆ GetNewtonStep()

◆ ModifyCombinedNewtonStep()

◆ New()

◆ PrintSelf()

◆ ResetNewtonStep()

◆ SetMaximumIterationsWithoutProgress()

◆ SetMaximumNewtonStepSizeInPhysicalUnits()

◆ StartOptimization()

Member Data Documentation

◆ m_BestIteration

◆ m_BestPosition

◆ m_BestValue

◆ m_CurrentPosition

◆ m_EstimateNewtonStepThreader

◆ m_HessianArray

◆ m_MaximumIterationsWithoutProgress

◆ m_MaximumNewtonStepSizeInPhysicalUnits

◆ m_NewtonStep

◆ m_NewtonStepValidFlags

◆ m_NewtonStepWarning

◆ m_OptimalStep

◆ m_PreviousPosition

◆ m_PreviousValue

template<typename TInternalComputationValueType>
class itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >