itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType > Class Template Reference

#include <itkQuasiNewtonOptimizerv4.h>

Inheritance diagram for itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >:

Collaboration diagram for itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >:

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 59 of file itkQuasiNewtonOptimizerv4.h.

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	StopConditionType = typename Superclass::StopConditionType
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	StopConditionType = typename Superclass::StopConditionType
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	IndexRangeType = ThreadedIndexedContainerPartitioner::IndexRangeType
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
enum	StopConditionType {   MAXIMUM_NUMBER_OF_ITERATIONS,   COSTFUNCTION_ERROR,   UPDATE_PARAMETERS_ERROR,   STEP_TOO_SMALL,   CONVERGENCE_CHECKER_PASSED,   GRADIENT_MAGNITUDE_TOLEARANCE,   OTHER_ERROR }
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 ::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	EstimateLearningRate ()
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	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 >
SizeValueType	GetCurrentIteration () const override
virtual const DerivativeType &	GetGradient () const
SizeValueType	GetNumberOfIterations () const override
virtual const StopConditionType &	GetStopCondition () const
const StopConditionReturnStringType	GetStopConditionDescription () const override
void	SetNumberOfIterations (const SizeValueType numberOfIterations) override
virtual void	ModifyGradientByScales ()
virtual void	ModifyGradientByLearningRate ()
Public Member Functions inherited from itk::ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType >
virtual const MeasureType &	GetCurrentMetricValue () const
virtual const ParametersType &	GetCurrentPosition () 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	SetNumberOfWorkUnits (ThreadIdType number)
virtual void	SetScalesEstimator (ScalesEstimatorType *_arg)
virtual void	SetWeights (ScalesType _arg)
virtual void	SetMetric (MetricType *_arg)
virtual MetricType *	GetModifiableMetric ()
virtual const MetricType *	GetMetric () const
virtual void	SetScales (const ScalesType &scales)
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 *)
unsigned long	AddObserver (const EventObject &event, Command *) 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 noexceptoverride
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
virtual void	Delete ()
virtual int	GetReferenceCount () const
	itkCloneMacro (Self)
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 flag)
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 location)
virtual void	EstimateNewtonStep ()
void	ModifyCombinedNewtonStep ()
void	PrintSelf (std::ostream &os, Indent indent) const override
	QuasiNewtonOptimizerv4Template ()
virtual void	ResetNewtonStep (IndexValueType location)
	~QuasiNewtonOptimizerv4Template () override=default
Protected Member Functions inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >
	GradientDescentOptimizerv4Template ()
void	ModifyGradientByLearningRateOverSubRange (const IndexRangeType &subrange) override
void	ModifyGradientByScalesOverSubRange (const IndexRangeType &subrange) 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 () override
Protected Member Functions inherited from itk::Object
	Object ()
bool	PrintObservers (std::ostream &os, Indent indent) const
virtual void	SetTimeStamp (const TimeStamp &time)
	~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
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 >
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}
StopConditionType	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

template<typename TInternalComputationValueType >

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

Definition at line 69 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

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

Definition at line 82 of file itkQuasiNewtonOptimizerv4.h.

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.

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.

template<typename TInternalComputationValueType >

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

Definition at line 83 of file itkQuasiNewtonOptimizerv4.h.

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 78 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

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

Definition at line 81 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

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

Definition at line 80 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

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

Definition at line 68 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

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

Standard class type aliases.

Definition at line 66 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

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

Definition at line 84 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

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

Definition at line 67 of file itkQuasiNewtonOptimizerv4.h.

Constructor & Destructor Documentation

template<typename TInternalComputationValueType >

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

protected

template<typename TInternalComputationValueType >

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

overrideprotecteddefault

Member Function Documentation

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 >.

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.

template<typename TInternalComputationValueType >

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

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 .

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 >.

template<typename TInternalComputationValueType >

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

protectedvirtual

Estimate a Newton step

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.

template<typename TInternalComputationValueType >

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

virtual

Run-time type information (and related methods).

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

template<typename TInternalComputationValueType >

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

virtual

Get the most recent Newton step.

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.

template<typename TInternalComputationValueType >

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

static

Method for creation through the object factory.

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 >.

template<typename TInternalComputationValueType >

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

protectedvirtual

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

template<typename TInternalComputationValueType >

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

virtual

Set the maximum tolerable number of iteration without any progress

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.

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

template<typename TInternalComputationValueType >

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

protected

Definition at line 139 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

ParametersType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_BestPosition

protected

Definition at line 138 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

MeasureType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_BestValue

protected

The best value so far and relevant information

Definition at line 137 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

ParametersType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_CurrentPosition

protected

The information about the current step

Definition at line 129 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

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

private

Threader for Newton step estimation.

Definition at line 197 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

HessianArrayType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_HessianArray

protected

The Hessian with local support

Definition at line 151 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

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

protected

The maximum tolerable number of iteration without any progress

Definition at line 126 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

TInternalComputationValueType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_MaximumNewtonStepSizeInPhysicalUnits

protected

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

Definition at line 148 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

DerivativeType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_NewtonStep

protected

The Quasi-Newton step

Definition at line 142 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

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

protected

Valid flag for the Quasi-Newton steps

Definition at line 154 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

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

protected

Warning message during Quasi-Newton step estimation

Definition at line 145 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

ParametersType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_OptimalStep

protected

Definition at line 130 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

ParametersType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_PreviousPosition

protected

Definition at line 134 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >

MeasureType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_PreviousValue

protected

The information about the previous step

Definition at line 133 of file itkQuasiNewtonOptimizerv4.h.

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

• itkQuasiNewtonOptimizerv4.h