ITK  5.4.0
Insight Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Protected Attributes | List of all members
itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType > Class Template Reference

#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 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

const char * GetNameOfClass () const override
 
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 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 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
 
const char * GetNameOfClass () const override
 
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
 
 GradientDescentLineSearchOptimizerv4Template ()
 
void PrintSelf (std::ostream &os, Indent indent) const override
 
 ~GradientDescentLineSearchOptimizerv4Template () override=default
 
TInternalComputationValueType GoldenSectionSearch (TInternalComputationValueType a, TInternalComputationValueType b, TInternalComputationValueType c, TInternalComputationValueType metricb=NumericTraits< TInternalComputationValueType >::max())
 
- 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 >
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
 
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 {}
 
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

◆ ConstPointer

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

Definition at line 71 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 90 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 80 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ Pointer

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

Definition at line 70 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ Self

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

Standard class type aliases.

Definition at line 68 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ Superclass

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

Definition at line 69 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 >.

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

Run-time type information (and related methods).

Reimplemented from itk::Object.

◆ 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.

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

◆ 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 150 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 156 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ m_LowerLimit

template<typename TInternalComputationValueType >
TInternalComputationValueType itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::m_LowerLimit {}
protected

Definition at line 146 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 153 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ m_Phi

template<typename TInternalComputationValueType >
TInternalComputationValueType itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::m_Phi {}
protected

Definition at line 148 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ m_Resphi

template<typename TInternalComputationValueType >
TInternalComputationValueType itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::m_Resphi {}
protected

Definition at line 149 of file itkGradientDescentLineSearchOptimizerv4.h.

◆ m_UpperLimit

template<typename TInternalComputationValueType >
TInternalComputationValueType itk::GradientDescentLineSearchOptimizerv4Template< TInternalComputationValueType >::m_UpperLimit {}
protected

Definition at line 147 of file itkGradientDescentLineSearchOptimizerv4.h.


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