#include <itkGradientDescentLineSearchOptimizerv4.h>

Detailed Description

template<typename TInternalComputationValueType>
class itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >

Gradient descent optimizer with a golden section line search.

GradientDescentLineSearchOptimizer implements a simple gradient descent optimizer that is followed by a line search to find the best value for the learning rate. At each iteration the current position is updated according to

\[ p_{n+1} = p_n + \mbox{learningRateByGoldenSectionLineSearch} \, \frac{\partial f(p_n) }{\partial p_n} \]

Options are identical to the superclass's except for:

options Epsilon, LowerLimit and UpperLimit that will guide a golden section line search to find the optimal gradient update within the range :

[ learningRate * LowerLimit , learningRate * UpperLimit ]

where Epsilon sets the resolution of the search. Smaller values lead to additional computation time but better localization of the minimum.

By default, this optimizer will return the best value and associated parameters that were calculated during the optimization. See SetReturnBestParametersAndValue().

Definition at line 60 of file itkGradientDescentLineSearchOptimizerv4.h.

Inheritance diagram for itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >:

Collaboration diagram for itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >:

Public Types
using	ConstPointer = SmartPointer<const Self>

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

using	InternalComputationValueType = TInternalComputationValueType

using	Pointer = SmartPointer<Self>

using	Self = GradientDescentLineSearchOptimizerv4Template

using	Superclass = GradientDescentOptimizerv4Template<TInternalComputationValueType>

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

using	DerivativeType

using	IndexRangeType

using	InternalComputationValueType = TInternalComputationValueType

using	MeasureType

using	ParametersType

using	Pointer = SmartPointer<Self>

using	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

using	IndexRangeType = ThreadedIndexedContainerPartitioner::IndexRangeType

using	InternalComputationValueType = TInternalComputationValueType

using	MeasureType

using	MetricType

using	MetricTypePointer = typename MetricType::Pointer

using	ParametersType

using	Pointer = SmartPointer<Self>

using	ScalesType

using	Self = GradientDescentOptimizerBasev4Template

using	StopConditionDescriptionType

using	StopConditionReturnStringType

using	Superclass = ObjectToObjectOptimizerBaseTemplate<TInternalComputationValueType>

Public Types inherited from itk::ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType >
using	ConstPointer

using	ConstPointer

using	DerivativeType

using	DerivativeType

using	MeasureType

using	MeasureType

using	MetricType

using	MetricType

using	MetricTypePointer

using	MetricTypePointer

using	NumberOfParametersType

using	NumberOfParametersType

using	ParametersType

using	ParametersType

using	Pointer

using	Pointer

using	ScalesEstimatorType

using	ScalesEstimatorType

using	ScalesType

using	ScalesType

using	Self

using	Self

using	StopConditionDescriptionType

using	StopConditionDescriptionType

using	StopConditionReturnStringType

using	StopConditionReturnStringType

using	Superclass

using	Superclass

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


virtual void	SetEpsilon (TInternalComputationValueType _arg)

virtual TInternalComputationValueType	GetEpsilon ()


virtual void	SetLowerLimit (TInternalComputationValueType _arg)

virtual TInternalComputationValueType	GetLowerLimit ()

virtual void	SetUpperLimit (TInternalComputationValueType _arg)

virtual TInternalComputationValueType	GetUpperLimit ()

virtual void	SetMaximumLineSearchIterations (unsigned int _arg)

virtual unsigned int	GetMaximumLineSearchIterations ()

Public Member Functions inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >
virtual::itk::LightObject::Pointer	CreateAnother () const

virtual void	EstimateLearningRate ()

	itkVirtualGetConstReferenceMacro (ConvergenceValue, TInternalComputationValueType)

	itkVirtualSetMacro (ConvergenceWindowSize, SizeValueType)

	itkVirtualSetMacro (MinimumConvergenceValue, TInternalComputationValueType)

void	ResumeOptimization () override

void	StartOptimization (bool doOnlyInitialization=false) override

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	DoEstimateLearningRateAtEachIterationOff ()

virtual void	SetDoEstimateLearningRateOnce (bool _arg)

virtual const bool &	GetDoEstimateLearningRateOnce () const

virtual void	DoEstimateLearningRateOnceOn ()

virtual void	DoEstimateLearningRateOnceOff ()

virtual void	SetReturnBestParametersAndValue (bool _arg)

virtual const bool &	GetReturnBestParametersAndValue () const

virtual void	ReturnBestParametersAndValueOn ()

virtual void	ReturnBestParametersAndValueOff ()

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

StopConditionReturnStringType	GetStopConditionDescription () const override

	itkVirtualGetConstReferenceMacro (StopCondition, StopConditionObjectToObjectOptimizerEnum)

virtual void	ModifyGradientByScales ()

virtual void	ModifyGradientByLearningRate ()

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

virtual bool	CanUseScales () const

virtual SizeValueType	GetCurrentIteration () const

virtual SizeValueType	GetCurrentIteration () const

virtual const MeasureType &	GetCurrentMetricValue () const

virtual const MeasureType &	GetCurrentMetricValue () const

virtual const ParametersType &	GetCurrentPosition () const

virtual const ParametersType &	GetCurrentPosition () const

virtual const ThreadIdType &	GetNumberOfWorkUnits () const

virtual const ThreadIdType &	GetNumberOfWorkUnits () const

virtual const ScalesType &	GetScales () const

virtual const ScalesType &	GetScales () const

virtual const bool &	GetScalesAreIdentity () const

virtual const bool &	GetScalesAreIdentity () const

bool	GetScalesInitialized () const

bool	GetScalesInitialized () const

virtual const MeasureType &	GetValue () const

virtual const MeasureType &	GetValue () const

virtual const ScalesType &	GetWeights () const

virtual const ScalesType &	GetWeights () const

virtual const bool &	GetWeightsAreIdentity () const

virtual const bool &	GetWeightsAreIdentity () const

	itkVirtualGetConstMacro (NumberOfIterations, SizeValueType)

	itkVirtualGetConstMacro (NumberOfIterations, SizeValueType)

	itkVirtualSetMacro (NumberOfIterations, SizeValueType)

	itkVirtualSetMacro (NumberOfIterations, SizeValueType)

virtual void	SetNumberOfWorkUnits (ThreadIdType number)

virtual void	SetNumberOfWorkUnits (ThreadIdType number)

virtual void	SetScales (const ScalesType &scales)

virtual void	SetScales (const ScalesType &scales)

virtual void	SetScalesEstimator (ScalesEstimatorType *_arg)

virtual void	SetScalesEstimator (ScalesEstimatorType *_arg)

virtual void	SetWeights (ScalesType _arg)

virtual void	SetWeights (ScalesType _arg)

	itkVirtualSetObjectMacro (Metric, MetricType)

virtual MetricType *	GetModifiableMetric ()

virtual const MetricType *	GetMetric () const

	itkVirtualSetObjectMacro (Metric, MetricType)

virtual MetricType *	GetModifiableMetric ()

virtual const MetricType *	GetMetric () const

virtual void	SetDoEstimateScales (bool _arg)

virtual const bool &	GetDoEstimateScales () const

virtual void	DoEstimateScalesOn ()

virtual void	DoEstimateScalesOff ()

virtual void	SetDoEstimateScales (bool _arg)

virtual const bool &	GetDoEstimateScales () const

virtual void	DoEstimateScalesOn ()

virtual void	DoEstimateScalesOff ()

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

TInternalComputationValueType	GoldenSectionSearch (TInternalComputationValueType a, TInternalComputationValueType b, TInternalComputationValueType c, TInternalComputationValueType metricb=NumericTraits< TInternalComputationValueType >::max())

	GradientDescentLineSearchOptimizerv4Template ()

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

	~GradientDescentLineSearchOptimizerv4Template () override=default

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

void	ModifyGradientByLearningRateOverSubRange (const IndexRangeType &subrange) override

void	ModifyGradientByScalesOverSubRange (const IndexRangeType &subrange) override

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

	~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 ()

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

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

	~ObjectToObjectOptimizerBaseTemplate () override

	~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 ()

Protected Attributes
TInternalComputationValueType	m_Epsilon {}

unsigned int	m_LineSearchIterations {}

TInternalComputationValueType	m_LowerLimit {}

unsigned int	m_MaximumLineSearchIterations {}

TInternalComputationValueType	m_Phi {}

TInternalComputationValueType	m_Resphi {}

TInternalComputationValueType	m_UpperLimit {}

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

SizeValueType	m_CurrentIteration

MeasureType	m_CurrentMetricValue

MeasureType	m_CurrentMetricValue

bool	m_DoEstimateScales

bool	m_DoEstimateScales

MetricTypePointer	m_Metric

MetricTypePointer	m_Metric

SizeValueType	m_NumberOfIterations

SizeValueType	m_NumberOfIterations

ThreadIdType	m_NumberOfWorkUnits

ThreadIdType	m_NumberOfWorkUnits

ScalesType	m_Scales

ScalesType	m_Scales

bool	m_ScalesAreIdentity

bool	m_ScalesAreIdentity

ScalesEstimatorType::Pointer	m_ScalesEstimator

ScalesEstimatorType::Pointer	m_ScalesEstimator

ScalesType	m_Weights

ScalesType	m_Weights

bool	m_WeightsAreIdentity

bool	m_WeightsAreIdentity

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

Member Typedef Documentation

◆ ConstPointer

template<typename TInternalComputationValueType>

using itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::ConstPointer = SmartPointer<const Self>

Definition at line 70 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ ConvergenceMonitoringType

template<typename TInternalComputationValueType>

using itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::ConvergenceMonitoringType = itk::Function::WindowConvergenceMonitoringFunction<TInternalComputationValueType>

Type for the convergence checker

Definition at line 89 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ InternalComputationValueType

template<typename TInternalComputationValueType>

using itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::InternalComputationValueType = TInternalComputationValueType

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

Definition at line 79 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ Pointer

template<typename TInternalComputationValueType>

using itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::Pointer = SmartPointer<Self>

Definition at line 69 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ Self

template<typename TInternalComputationValueType>

using itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::Self = GradientDescentLineSearchOptimizerv4Template

Standard class type aliases.

Definition at line 67 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ Superclass

template<typename TInternalComputationValueType>

using itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::Superclass = GradientDescentOptimizerv4Template<TInternalComputationValueType>

Definition at line 68 of file itkGradientDescentLineSearchOptimizerv4.h.

Constructor & Destructor Documentation

◆ GradientDescentLineSearchOptimizerv4Template()

template<typename TInternalComputationValueType>

itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::GradientDescentLineSearchOptimizerv4Template ( )

protected

Default constructor

◆ ~GradientDescentLineSearchOptimizerv4Template()

template<typename TInternalComputationValueType>

itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::~GradientDescentLineSearchOptimizerv4Template ( )

overrideprotecteddefault

Destructor

Member Function Documentation

◆ AdvanceOneStep()

template<typename TInternalComputationValueType>

void itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::AdvanceOneStep ( )

overrideprotectedvirtual

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

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

◆ CreateAnother()

template<typename TInternalComputationValueType>

virtual::itk::LightObject::Pointer itk::GradientDescentLineSearchOptimizerv4Template< 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::LightObject.

◆ GetEpsilon()

template<typename TInternalComputationValueType>

virtual TInternalComputationValueType itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::GetEpsilon ( )

virtual

The epsilon determines the accuracy of the line search i.e. the energy alteration that is considered convergent.

◆ GetLowerLimit()

template<typename TInternalComputationValueType>

virtual TInternalComputationValueType itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::GetLowerLimit ( )

virtual

The upper and lower limit below determine the range of values over which the learning rate can be adjusted by the golden section line search. The update can then occur in the range from the smallest change given by : NewParams = OldParams + LowerLimit * gradient to the largest change given by : NewParams = OldParams + UpperLimit * gradient Reasonable values might be 0 and 2.

◆ GetMaximumLineSearchIterations()

template<typename TInternalComputationValueType>

virtual unsigned int itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::GetMaximumLineSearchIterations ( )

virtual

The upper and lower limit below determine the range of values over which the learning rate can be adjusted by the golden section line search. The update can then occur in the range from the smallest change given by : NewParams = OldParams + LowerLimit * gradient to the largest change given by : NewParams = OldParams + UpperLimit * gradient Reasonable values might be 0 and 2.

◆ GetNameOfClass()

template<typename TInternalComputationValueType>

virtual const char * itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::GetNameOfClass ( ) const

virtual

See also: LightObject::GetNameOfClass()

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

Reimplemented in itk::ConjugateGradientLineSearchOptimizerv4Template< TInternalComputationValueType >, itk::ConjugateGradientLineSearchOptimizerv4Template< double >, and itk::ConjugateGradientLineSearchOptimizerv4Template< double >.

◆ GetUpperLimit()

template<typename TInternalComputationValueType>

virtual TInternalComputationValueType itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::GetUpperLimit ( )

virtual

The upper and lower limit below determine the range of values over which the learning rate can be adjusted by the golden section line search. The update can then occur in the range from the smallest change given by : NewParams = OldParams + LowerLimit * gradient to the largest change given by : NewParams = OldParams + UpperLimit * gradient Reasonable values might be 0 and 2.

◆ GoldenSectionSearch()

template<typename TInternalComputationValueType>

TInternalComputationValueType itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::GoldenSectionSearch	(	TInternalComputationValueType	a,
		TInternalComputationValueType	b,
		TInternalComputationValueType	c,
		TInternalComputationValueType	metricb = NumericTraits< TInternalComputationValueType >::max() )

protected

Search the golden section.

a and c are the current bounds; the minimum is between them. b is a center point. f(x) is some mathematical function elsewhere defined. a corresponds to x1; b corresponds to x2; c corresponds to x3. x corresponds to x4.

◆ New()

template<typename TInternalComputationValueType>

static Pointer itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::New ( )

static

New macro for creation of through a Smart Pointer

◆ PrintSelf()

template<typename TInternalComputationValueType>

void itk::GradientDescentLineSearchOptimizerv4Template< 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::LightObject.

◆ SetEpsilon()

template<typename TInternalComputationValueType>

virtual void itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::SetEpsilon ( TInternalComputationValueType _arg )

virtual

The epsilon determines the accuracy of the line search i.e. the energy alteration that is considered convergent.

◆ SetLowerLimit()

template<typename TInternalComputationValueType>

virtual void itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::SetLowerLimit ( TInternalComputationValueType _arg )

virtual

The upper and lower limit below determine the range of values over which the learning rate can be adjusted by the golden section line search. The update can then occur in the range from the smallest change given by : NewParams = OldParams + LowerLimit * gradient to the largest change given by : NewParams = OldParams + UpperLimit * gradient Reasonable values might be 0 and 2.

◆ SetMaximumLineSearchIterations()

template<typename TInternalComputationValueType>

virtual void itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::SetMaximumLineSearchIterations ( unsigned int _arg )

virtual

The upper and lower limit below determine the range of values over which the learning rate can be adjusted by the golden section line search. The update can then occur in the range from the smallest change given by : NewParams = OldParams + LowerLimit * gradient to the largest change given by : NewParams = OldParams + UpperLimit * gradient Reasonable values might be 0 and 2.

◆ SetUpperLimit()

template<typename TInternalComputationValueType>

virtual void itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::SetUpperLimit ( TInternalComputationValueType _arg )

virtual

The upper and lower limit below determine the range of values over which the learning rate can be adjusted by the golden section line search. The update can then occur in the range from the smallest change given by : NewParams = OldParams + LowerLimit * gradient to the largest change given by : NewParams = OldParams + UpperLimit * gradient Reasonable values might be 0 and 2.

Member Data Documentation

◆ m_Epsilon

template<typename TInternalComputationValueType>

TInternalComputationValueType itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::m_Epsilon {}

protected

Definition at line 148 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ m_LineSearchIterations

template<typename TInternalComputationValueType>

unsigned int itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::m_LineSearchIterations {}

protected

Counts the recursion depth for the golden section search

Definition at line 154 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ m_LowerLimit

template<typename TInternalComputationValueType>

TInternalComputationValueType itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::m_LowerLimit {}

protected

Definition at line 144 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ m_MaximumLineSearchIterations

template<typename TInternalComputationValueType>

unsigned int itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::m_MaximumLineSearchIterations {}

protected

Controls the maximum recursion depth for the golden section search

Definition at line 151 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ m_Phi

template<typename TInternalComputationValueType>

TInternalComputationValueType itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::m_Phi {}

protected

Definition at line 146 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ m_Resphi

template<typename TInternalComputationValueType>

TInternalComputationValueType itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::m_Resphi {}

protected

Definition at line 147 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ m_UpperLimit

template<typename TInternalComputationValueType>

TInternalComputationValueType itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::m_UpperLimit {}

protected

Definition at line 145 of file itkGradientDescentLineSearchOptimizerv4.h.

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

itkGradientDescentLineSearchOptimizerv4.h

Detailed Description

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Protected Attributes

Member Typedef Documentation

◆ ConstPointer

◆ ConvergenceMonitoringType

◆ InternalComputationValueType

◆ Pointer

◆ Self

◆ Superclass

Constructor & Destructor Documentation

◆ GradientDescentLineSearchOptimizerv4Template()

◆ ~GradientDescentLineSearchOptimizerv4Template()

Member Function Documentation

◆ AdvanceOneStep()

◆ CreateAnother()

◆ GetEpsilon()

◆ GetLowerLimit()

◆ GetMaximumLineSearchIterations()

◆ GetNameOfClass()

◆ GetUpperLimit()

◆ GoldenSectionSearch()

◆ New()

◆ PrintSelf()

◆ SetEpsilon()

◆ SetLowerLimit()

◆ SetMaximumLineSearchIterations()

◆ SetUpperLimit()

Member Data Documentation

◆ m_Epsilon

◆ m_LineSearchIterations

◆ m_LowerLimit

◆ m_MaximumLineSearchIterations

◆ m_Phi

◆ m_Resphi

◆ m_UpperLimit