#include <itkRegularStepGradientDescentOptimizerv4.h>

Detailed Description

template<typename TInternalComputationValueType = double>
class itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >

Regular Step Gradient descent optimizer.

This optimizer is a variant of gradient descent that attempts to prevent it from taking steps that are too large. At each iteration, this optimizer will take a step along the direction of the metric derivative. Each time the direction of the derivative abruptly changes, the optimizer assumes that a local extrema has been passed and reacts by reducing the step length by a relaxation factor that is set to 0.5 by default. The default value for the initial step length is 1, and this value can only be changed manually via SetLearningRate() since this optimizer does not use the ScaleEstimator to automatically estimate the learning rate. Also note that unlike the previous version of RegularStepGradientDescentOptimizer, ITKv4 does not have a "maximize/minimize" option to modify the effect of the metric derivative. The assigned metric is assumed to return a parameter derivative result that "improves" the optimization.

Examples: Examples/RegistrationITKv4/ImageRegistration1.cxx, Examples/RegistrationITKv4/ImageRegistration12.cxx, Examples/RegistrationITKv4/ImageRegistration13.cxx, Examples/RegistrationITKv4/ImageRegistration3.cxx, Examples/RegistrationITKv4/ImageRegistration4.cxx, Examples/RegistrationITKv4/ImageRegistration5.cxx, Examples/RegistrationITKv4/ImageRegistration6.cxx, Examples/RegistrationITKv4/ImageRegistration7.cxx, Examples/RegistrationITKv4/ImageRegistration8.cxx, Examples/RegistrationITKv4/ImageRegistration9.cxx, Examples/RegistrationITKv4/MultiResImageRegistration1.cxx, Examples/RegistrationITKv4/MultiStageImageRegistration1.cxx, Examples/RegistrationITKv4/MultiStageImageRegistration2.cxx, and SphinxExamples/src/Registration/Common/Perform2DTranslationRegistrationWithMeanSquares/Code.cxx.

Definition at line 47 of file itkRegularStepGradientDescentOptimizerv4.h.

Inheritance diagram for itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >:

Collaboration diagram for itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >:

Public Types
using	CompensatedSummationType = CompensatedSummation< InternalComputationValueType >

using	ConstPointer = SmartPointer< const Self >

using	InternalComputationValueType = TInternalComputationValueType

using	Pointer = SmartPointer< Self >

using	Self = RegularStepGradientDescentOptimizerv4

using	Superclass = GradientDescentOptimizerv4Template< TInternalComputationValueType >

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

using	InternalComputationValueType = TInternalComputationValueType

using	Pointer = SmartPointer< Self >

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	IndexRangeType = ThreadedIndexedContainerPartitioner::IndexRangeType

using	InternalComputationValueType = TInternalComputationValueType

using	MetricTypePointer = typename MetricType::Pointer

using	Pointer = SmartPointer< Self >

using	Self = GradientDescentOptimizerBasev4Template

using	Superclass = ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType >

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
void	EstimateLearningRate () override

double	GetCurrentStepLength () const

const char *	GetNameOfClass () const override

void	StartOptimization (bool doOnlyInitialization=false) override


virtual void	SetMinimumStepLength (TInternalComputationValueType _arg)

virtual const TInternalComputationValueType &	GetMinimumStepLength () const


virtual void	SetRelaxationFactor (TInternalComputationValueType _arg)

virtual const TInternalComputationValueType &	GetRelaxationFactor () const


virtual void	SetGradientMagnitudeTolerance (TInternalComputationValueType _arg)

virtual const TInternalComputationValueType &	GetGradientMagnitudeTolerance () const


virtual void	SetCurrentLearningRateRelaxation (MeasureType _arg)

virtual const MeasureType &	GetCurrentLearningRateRelaxation () const

Public Member Functions inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >
virtual const TInternalComputationValueType &	GetConvergenceValue () const

void	ResumeOptimization () override

virtual void	SetConvergenceWindowSize (SizeValueType _arg)

virtual void	SetMinimumConvergenceValue (TInternalComputationValueType _arg)

void	StopOptimization () override

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	SetDoEstimateLearningRateOnce (bool _arg)

virtual const bool &	GetDoEstimateLearningRateOnce () const

virtual void	DoEstimateLearningRateOnceOn ()

virtual void	SetReturnBestParametersAndValue (bool _arg)

virtual const bool &	GetReturnBestParametersAndValue () const

virtual void	ReturnBestParametersAndValueOn ()

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

virtual const StopConditionObjectToObjectOptimizerEnum &	GetStopCondition () const

StopConditionReturnStringType	GetStopConditionDescription () const override

virtual void	ModifyGradientByScales ()

virtual void	ModifyGradientByLearningRate ()

Public Member Functions inherited from itk::ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType >
virtual bool	CanUseScales () const

virtual SizeValueType	GetCurrentIteration () const

virtual const MeasureType &	GetCurrentMetricValue () const

virtual const ParametersType &	GetCurrentPosition () const

virtual SizeValueType	GetNumberOfIterations () const

virtual const ThreadIdType &	GetNumberOfWorkUnits () const

virtual const ScalesType &	GetScales () const

virtual const bool &	GetScalesAreIdentity () const

bool	GetScalesInitialized () const

virtual const MeasureType &	GetValue () const

virtual const ScalesType &	GetWeights () const

virtual const bool &	GetWeightsAreIdentity () const

virtual void	SetNumberOfIterations (SizeValueType _arg)

virtual void	SetNumberOfWorkUnits (ThreadIdType number)

virtual void	SetScalesEstimator (ScalesEstimatorType *_arg)

virtual void	SetWeights (ScalesType _arg)

virtual void	SetMetric (MetricType *_arg)

virtual MetricType *	GetModifiableMetric ()

virtual void	SetScales (const ScalesType &scales)

virtual void	SetDoEstimateScales (bool _arg)

virtual const bool &	GetDoEstimateScales () const

virtual void	DoEstimateScalesOn ()

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

LightObject::Pointer	CreateAnother () const override

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

	RegularStepGradientDescentOptimizerv4 ()

	~RegularStepGradientDescentOptimizerv4 () override=default


void	ModifyGradientByScalesOverSubRange (const IndexRangeType &subrange) override

void	ModifyGradientByLearningRateOverSubRange (const IndexRangeType &subrange) override

Protected Member Functions inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >
	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 ()

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 Attributes
MeasureType	m_CurrentLearningRateRelaxation {}

TInternalComputationValueType	m_GradientMagnitudeTolerance {}

TInternalComputationValueType	m_MinimumStepLength {}

TInternalComputationValueType	m_RelaxationFactor {}

Additional Inherited Members
Protected Attributes inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >
ParametersType	m_BestParameters {}

TInternalComputationValueType	m_ConvergenceValue {}

MeasureType	m_CurrentBestValue {}

TInternalComputationValueType	m_LearningRate {}

TInternalComputationValueType	m_MinimumConvergenceValue {}

DerivativeType	m_PreviousGradient {}

bool	m_ReturnBestParametersAndValue { false }

Protected Attributes inherited from itk::GradientDescentOptimizerBasev4Template< TInternalComputationValueType >
ConvergenceMonitoringType::Pointer	m_ConvergenceMonitoring {}

SizeValueType	m_ConvergenceWindowSize {}

bool	m_DoEstimateLearningRateAtEachIteration {}

bool	m_DoEstimateLearningRateOnce {}

DerivativeType	m_Gradient {}

TInternalComputationValueType	m_MaximumStepSizeInPhysicalUnits {}

DomainThreader< ThreadedIndexedContainerPartitioner, Self >::Pointer	m_ModifyGradientByLearningRateThreader {}

DomainThreader< ThreadedIndexedContainerPartitioner, Self >::Pointer	m_ModifyGradientByScalesThreader {}

bool	m_Stop { false }

StopConditionObjectToObjectOptimizerEnum	m_StopCondition {}

StopConditionDescriptionType	m_StopConditionDescription {}

bool	m_UseConvergenceMonitoring {}

Protected Attributes inherited from itk::ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType >
SizeValueType	m_CurrentIteration {}

MeasureType	m_CurrentMetricValue {}

bool	m_DoEstimateScales {}

MetricTypePointer	m_Metric {}

SizeValueType	m_NumberOfIterations {}

ThreadIdType	m_NumberOfWorkUnits {}

ScalesType	m_Scales {}

bool	m_ScalesAreIdentity {}

ScalesEstimatorType::Pointer	m_ScalesEstimator {}

ScalesType	m_Weights {}

bool	m_WeightsAreIdentity {}

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

Member Typedef Documentation

◆ CompensatedSummationType

template<typename TInternalComputationValueType = double>

using itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::CompensatedSummationType = CompensatedSummation<InternalComputationValueType>

Compensated summation type.

Definition at line 79 of file itkRegularStepGradientDescentOptimizerv4.h.

◆ ConstPointer

template<typename TInternalComputationValueType = double>

using itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::ConstPointer = SmartPointer<const Self>

Definition at line 57 of file itkRegularStepGradientDescentOptimizerv4.h.

◆ InternalComputationValueType

template<typename TInternalComputationValueType = double>

using itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::InternalComputationValueType = TInternalComputationValueType

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

Definition at line 67 of file itkRegularStepGradientDescentOptimizerv4.h.

◆ Pointer

template<typename TInternalComputationValueType = double>

using itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::Pointer = SmartPointer<Self>

Definition at line 56 of file itkRegularStepGradientDescentOptimizerv4.h.

◆ Self

template<typename TInternalComputationValueType = double>

using itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::Self = RegularStepGradientDescentOptimizerv4

Standard class type aliases.

Definition at line 54 of file itkRegularStepGradientDescentOptimizerv4.h.

◆ Superclass

template<typename TInternalComputationValueType = double>

using itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::Superclass = GradientDescentOptimizerv4Template<TInternalComputationValueType>

Definition at line 55 of file itkRegularStepGradientDescentOptimizerv4.h.

Constructor & Destructor Documentation

◆ RegularStepGradientDescentOptimizerv4()

template<typename TInternalComputationValueType = double>

itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::RegularStepGradientDescentOptimizerv4 ( )

protected

Default constructor.

◆ ~RegularStepGradientDescentOptimizerv4()

template<typename TInternalComputationValueType = double>

itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::~RegularStepGradientDescentOptimizerv4 ( )

overrideprotecteddefault

Destructor.

Member Function Documentation

◆ AdvanceOneStep()

template<typename TInternalComputationValueType = double>

void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::AdvanceOneStep ( )

overrideprotectedvirtual

Advance one Step following the gradient direction. Includes transform update.

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

◆ EstimateLearningRate()

template<typename TInternalComputationValueType = double>

void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::EstimateLearningRate ( )

overridevirtual

Estimate the learning rate based on the current gradient.

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

◆ GetCurrentLearningRateRelaxation()

template<typename TInternalComputationValueType = double>

virtual const MeasureType& itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::GetCurrentLearningRateRelaxation ( ) const

virtual

Set/Get current scale for learning rate.

◆ GetCurrentStepLength()

template<typename TInternalComputationValueType = double>

double itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::GetCurrentStepLength ( ) const

Get current gradient step value.

◆ GetGradientMagnitudeTolerance()

template<typename TInternalComputationValueType = double>

virtual const TInternalComputationValueType& itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::GetGradientMagnitudeTolerance ( ) const

virtual

Set/Get gradient magnitude tolerance value for convergence checking.

◆ GetMinimumStepLength()

template<typename TInternalComputationValueType = double>

virtual const TInternalComputationValueType& itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::GetMinimumStepLength ( ) const

virtual

Minimum step length (learning rate) value for convergence checking. When the local minima is passed by taking a large step, the step length is adjusted (decreased) by the relaxation factor, so that smaller steps are taken towards the minimum point (convergence). When the step length value reaches a small value, it would be treated as converged.

The default value is set to 1e-4 to pass all tests.

◆ GetNameOfClass()

template<typename TInternalComputationValueType = double>

const char* itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::GetNameOfClass ( ) const

overridevirtual

See also: LightObject::GetNameOfClass()

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

◆ GetRelaxationFactor()

template<typename TInternalComputationValueType = double>

virtual const TInternalComputationValueType& itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::GetRelaxationFactor ( ) const

virtual

Set/Get relaxation factor value.

◆ ModifyGradientByLearningRateOverSubRange()

template<typename TInternalComputationValueType = double>

void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::ModifyGradientByLearningRateOverSubRange ( const IndexRangeType & subrange )

overrideprotectedvirtual

Modify the input gradient over a given index range.

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

◆ ModifyGradientByScalesOverSubRange()

template<typename TInternalComputationValueType = double>

void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::ModifyGradientByScalesOverSubRange ( const IndexRangeType & subrange )

overrideprotectedvirtual

Modify the input gradient over a given index range.

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

◆ New()

template<typename TInternalComputationValueType = double>

static Pointer itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::New ( )

static

New macro for creation of through a Smart Pointer.

◆ PrintSelf()

template<typename TInternalComputationValueType = double>

void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::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::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

◆ SetCurrentLearningRateRelaxation()

template<typename TInternalComputationValueType = double>

virtual void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::SetCurrentLearningRateRelaxation ( MeasureType _arg )

virtual

Set/Get current scale for learning rate.

◆ SetGradientMagnitudeTolerance()

template<typename TInternalComputationValueType = double>

virtual void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::SetGradientMagnitudeTolerance ( TInternalComputationValueType _arg )

virtual

Set/Get gradient magnitude tolerance value for convergence checking.

◆ SetMinimumStepLength()

template<typename TInternalComputationValueType = double>

virtual void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::SetMinimumStepLength ( TInternalComputationValueType _arg )

virtual

Minimum step length (learning rate) value for convergence checking. When the local minima is passed by taking a large step, the step length is adjusted (decreased) by the relaxation factor, so that smaller steps are taken towards the minimum point (convergence). When the step length value reaches a small value, it would be treated as converged.

The default value is set to 1e-4 to pass all tests.

◆ SetRelaxationFactor()

template<typename TInternalComputationValueType = double>

virtual void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::SetRelaxationFactor ( TInternalComputationValueType _arg )

virtual

Set/Get relaxation factor value.

◆ StartOptimization()

template<typename TInternalComputationValueType = double>

void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::StartOptimization ( bool doOnlyInitialization = false )

overridevirtual

Start and run the optimization.

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

Member Data Documentation

◆ m_CurrentLearningRateRelaxation

template<typename TInternalComputationValueType = double>

MeasureType itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::m_CurrentLearningRateRelaxation {}

private

Definition at line 152 of file itkRegularStepGradientDescentOptimizerv4.h.

◆ m_GradientMagnitudeTolerance

template<typename TInternalComputationValueType = double>

TInternalComputationValueType itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::m_GradientMagnitudeTolerance {}

private

Definition at line 150 of file itkRegularStepGradientDescentOptimizerv4.h.

◆ m_MinimumStepLength

template<typename TInternalComputationValueType = double>

TInternalComputationValueType itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::m_MinimumStepLength {}

private

Definition at line 148 of file itkRegularStepGradientDescentOptimizerv4.h.

◆ m_RelaxationFactor

template<typename TInternalComputationValueType = double>

TInternalComputationValueType itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::m_RelaxationFactor {}

private

Definition at line 146 of file itkRegularStepGradientDescentOptimizerv4.h.

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

itkRegularStepGradientDescentOptimizerv4.h

Detailed Description

template<typename TInternalComputationValueType = double> class itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Private Attributes

Additional Inherited Members

Member Typedef Documentation

◆ CompensatedSummationType

◆ ConstPointer

◆ InternalComputationValueType

◆ Pointer

◆ Self

◆ Superclass

Constructor & Destructor Documentation

◆ RegularStepGradientDescentOptimizerv4()

◆ ~RegularStepGradientDescentOptimizerv4()

Member Function Documentation

◆ AdvanceOneStep()

◆ EstimateLearningRate()

◆ GetCurrentLearningRateRelaxation()

◆ GetCurrentStepLength()

◆ GetGradientMagnitudeTolerance()

◆ GetMinimumStepLength()

◆ GetNameOfClass()

◆ GetRelaxationFactor()

◆ ModifyGradientByLearningRateOverSubRange()

◆ ModifyGradientByScalesOverSubRange()

◆ New()

◆ PrintSelf()

◆ SetCurrentLearningRateRelaxation()

◆ SetGradientMagnitudeTolerance()

◆ SetMinimumStepLength()

◆ SetRelaxationFactor()

◆ StartOptimization()

Member Data Documentation

◆ m_CurrentLearningRateRelaxation

◆ m_GradientMagnitudeTolerance

◆ m_MinimumStepLength

◆ m_RelaxationFactor

template<typename TInternalComputationValueType = double>
class itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >