itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType > Class Template Reference

#include <itkQuasiNewtonOptimizerv4.h>

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 61 of file itkQuasiNewtonOptimizerv4.h.

Inheritance diagram for itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >:

Collaboration diagram for itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >:

Public Types
using	ConstPointer = SmartPointer< const Self >
using	HessianArrayType = std::vector< HessianType >
using	HessianType = itk::Array2D< TInternalComputationValueType >
using	InternalComputationValueType = TInternalComputationValueType
using	Pointer = SmartPointer< Self >
using	Self = QuasiNewtonOptimizerv4Template
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
virtual void	EstimateNewtonStepOverSubRange (const IndexRangeType &subrange)
const char *	GetNameOfClass () const override
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	EstimateLearningRate ()
virtual const TInternalComputationValueType &	GetConvergenceValue () const
const char *	GetNameOfClass () const override
void	ResumeOptimization () override
virtual void	SetConvergenceWindowSize (SizeValueType _arg)
virtual void	SetMinimumConvergenceValue (TInternalComputationValueType _arg)
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	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
const char *	GetNameOfClass () const override
virtual const StopConditionObjectToObjectOptimizerEnum &	GetStopCondition () const
StopConditionReturnStringType	GetStopConditionDescription () const override
virtual void	ModifyGradientByLearningRateOverSubRange (const IndexRangeType &subrange)=0
virtual void	ModifyGradientByScalesOverSubRange (const IndexRangeType &subrange)=0
virtual void	ResumeOptimization ()=0
void	StartOptimization (bool doOnlyInitialization=false) override
virtual void	StopOptimization ()
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
const char *	GetNameOfClass () const override
virtual SizeValueType	GetNumberOfIterations () const
virtual const ThreadIdType &	GetNumberOfWorkUnits () const
virtual const ScalesType &	GetScales () const
virtual const bool &	GetScalesAreIdentity () const
bool	GetScalesInitialized () const
virtual StopConditionReturnStringType	GetStopConditionDescription () const=0
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	StartOptimization (bool doOnlyInitialization=false)
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
const char *	GetNameOfClass () const override
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 Pointer	CreateAnother () const
virtual void	Delete ()
virtual const char *	GetNameOfClass () const
virtual int	GetReferenceCount () const
void	Print (std::ostream &os, Indent indent=0) const
virtual void	Register () const
virtual void	SetReferenceCount (int)
virtual void	UnRegister () const noexcept

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 >
virtual void	AdvanceOneStep ()
	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 >
void	PrintSelf (std::ostream &os, Indent indent) const override
	GradientDescentOptimizerBasev4Template ()
	~GradientDescentOptimizerBasev4Template () override=default
Protected Member Functions inherited from itk::ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType >
void	PrintSelf (std::ostream &os, Indent indent) const override
	ObjectToObjectOptimizerBaseTemplate ()
	~ObjectToObjectOptimizerBaseTemplate () override
Protected Member Functions inherited from itk::Object
	Object ()
bool	PrintObservers (std::ostream &os, Indent indent) const
void	PrintSelf (std::ostream &os, Indent indent) const override
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	PrintSelf (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 {}
BooleanStdVectorType	m_NewtonStepValidFlags {}
std::string	m_NewtonStepWarning {}
ParametersType	m_OptimalStep {}
ParametersType	m_PreviousPosition {}
MeasureType	m_PreviousValue {}
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 {}

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

Member Typedef Documentation

ConstPointer

template<typename TInternalComputationValueType >

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

Definition at line 71 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 91 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 88 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 80 of file itkQuasiNewtonOptimizerv4.h.

Pointer

template<typename TInternalComputationValueType >

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

Definition at line 70 of file itkQuasiNewtonOptimizerv4.h.

Self

template<typename TInternalComputationValueType >

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

Standard class type aliases.

Definition at line 68 of file itkQuasiNewtonOptimizerv4.h.

Superclass

template<typename TInternalComputationValueType >

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

Definition at line 69 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 https://en.wikipedia.org/wiki/BFGS_method .

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 >

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

overridevirtual

See also

LightObject::GetNameOfClass()

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

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 >.

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 141 of file itkQuasiNewtonOptimizerv4.h.

m_BestPosition

template<typename TInternalComputationValueType >

ParametersType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_BestPosition {}

protected

Definition at line 140 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 139 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 131 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 207 of file itkQuasiNewtonOptimizerv4.h.

m_HessianArray

template<typename TInternalComputationValueType >

HessianArrayType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_HessianArray {}

protected

The Hessian with local support

Definition at line 153 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 128 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 150 of file itkQuasiNewtonOptimizerv4.h.

m_NewtonStep

template<typename TInternalComputationValueType >

DerivativeType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_NewtonStep {}

protected

The Quasi-Newton step

Definition at line 144 of file itkQuasiNewtonOptimizerv4.h.

m_NewtonStepValidFlags

template<typename TInternalComputationValueType >

BooleanStdVectorType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_NewtonStepValidFlags {}

protected

Valid flag for the Quasi-Newton steps.

Definition at line 157 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 147 of file itkQuasiNewtonOptimizerv4.h.

m_OptimalStep

template<typename TInternalComputationValueType >

ParametersType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_OptimalStep {}

protected

Definition at line 132 of file itkQuasiNewtonOptimizerv4.h.

m_PreviousPosition

template<typename TInternalComputationValueType >

ParametersType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_PreviousPosition {}

protected

Definition at line 136 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 135 of file itkQuasiNewtonOptimizerv4.h.

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

• itkQuasiNewtonOptimizerv4.h