ITK  5.4.0
Insight Toolkit
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itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType > Class Template Reference

#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 MeasureTypeGetCurrentLearningRateRelaxation () 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 DerivativeTypeGetGradient () const
 
virtual const StopConditionObjectToObjectOptimizerEnumGetStopCondition () const
 
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 MeasureTypeGetCurrentMetricValue () const
 
virtual const ParametersTypeGetCurrentPosition () const
 
virtual SizeValueType GetNumberOfIterations () const
 
virtual const ThreadIdTypeGetNumberOfWorkUnits () const
 
virtual const ScalesTypeGetScales () const
 
virtual const bool & GetScalesAreIdentity () const
 
bool GetScalesInitialized () const
 
virtual const MeasureTypeGetValue () const
 
virtual const ScalesTypeGetWeights () 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 MetricTypeGetModifiableMetric ()
 
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 *)
 
unsigned long AddObserver (const EventObject &event, Command *) 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
 
CommandGetCommand (unsigned long tag)
 
bool GetDebug () const
 
MetaDataDictionaryGetMetaDataDictionary ()
 
const MetaDataDictionaryGetMetaDataDictionary () const
 
virtual ModifiedTimeType GetMTime () const
 
virtual const TimeStampGetTimeStamp () const
 
bool HasObserver (const EventObject &event) const
 
void InvokeEvent (const EventObject &)
 
void InvokeEvent (const EventObject &) const
 
virtual void Modified () const
 
void Register () const override
 
void RemoveAllObservers ()
 
void RemoveObserver (unsigned long tag)
 
void SetDebug (bool debugFlag) const
 
void SetReferenceCount (int) override
 
void UnRegister () const noexcept override
 
void SetMetaDataDictionary (const MetaDataDictionary &rhs)
 
void SetMetaDataDictionary (MetaDataDictionary &&rrhs)
 
virtual void SetObjectName (std::string _arg)
 
virtual const std::string & GetObjectName () const
 
- Public Member Functions inherited from itk::LightObject
Pointer Clone () const
 
virtual void Delete ()
 
virtual int GetReferenceCount () const
 
void Print (std::ostream &os, Indent indent=0) const
 

Static Public Member Functions

static Pointer New ()
 
- Static Public Member Functions inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >
static Pointer New ()
 
- Static Public Member Functions inherited from itk::Object
static bool GetGlobalWarningDisplay ()
 
static void GlobalWarningDisplayOff ()
 
static void GlobalWarningDisplayOn ()
 
static Pointer New ()
 
static void SetGlobalWarningDisplay (bool val)
 
- Static Public Member Functions inherited from itk::LightObject
static void BreakOnError ()
 
static Pointer New ()
 

Protected Member Functions

void AdvanceOneStep () override
 
void 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

◆ 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: