ITK  5.2.0
Insight Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Protected Attributes | Private Attributes | List of all members
itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType > Class Template Reference

#include <itkQuasiNewtonOptimizerv4.h>

+ Inheritance diagram for itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >:
+ Collaboration diagram for itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >:

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 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 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 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
 
using Superclass = ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType >
 
using IndexRangeType = ThreadedIndexedContainerPartitioner::IndexRangeType
 
- 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 DerivativeTypeGetNewtonStep () 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 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 SetMinimumConvergenceValue (TInternalComputationValueType _arg)
 
virtual void SetConvergenceWindowSize (SizeValueType _arg)
 
virtual const TInternalComputationValueType & GetConvergenceValue () const
 
virtual void SetReturnBestParametersAndValue (bool _arg)
 
virtual const bool & GetReturnBestParametersAndValue () const
 
virtual void ReturnBestParametersAndValueOn ()
 
virtual void ReturnBestParametersAndValueOff ()
 
void StopOptimization () override
 
void ResumeOptimization () override
 
virtual void EstimateLearningRate ()
 
- Public Member Functions inherited from itk::GradientDescentOptimizerBasev4Template< TInternalComputationValueType >
virtual const DerivativeTypeGetGradient () const
 
virtual const StopConditionObjectToObjectOptimizerEnumGetStopCondition () const
 
void SetNumberOfIterations (const SizeValueType numberOfIterations) override
 
SizeValueType GetNumberOfIterations () const override
 
SizeValueType GetCurrentIteration () const override
 
const StopConditionReturnStringType GetStopConditionDescription () const override
 
virtual void ModifyGradientByScales ()
 
virtual void ModifyGradientByLearningRate ()
 
- Public Member Functions inherited from itk::ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType >
virtual void SetMetric (MetricType *_arg)
 
virtual MetricTypeGetModifiableMetric ()
 
virtual const MetricTypeGetMetric () const
 
virtual const MeasureTypeGetCurrentMetricValue () const
 
virtual const MeasureTypeGetValue () const
 
virtual void SetScales (const ScalesType &scales)
 
virtual const ScalesTypeGetScales () const
 
virtual const bool & GetScalesAreIdentity () const
 
virtual void SetWeights (ScalesType _arg)
 
virtual const ScalesTypeGetWeights () const
 
virtual const bool & GetWeightsAreIdentity () const
 
bool GetScalesInitialized () const
 
virtual void SetScalesEstimator (ScalesEstimatorType *_arg)
 
virtual void SetDoEstimateScales (bool _arg)
 
virtual const bool & GetDoEstimateScales () const
 
virtual void DoEstimateScalesOn ()
 
virtual void DoEstimateScalesOff ()
 
virtual void SetNumberOfWorkUnits (ThreadIdType number)
 
virtual const ThreadIdTypeGetNumberOfWorkUnits () const
 
virtual const ParametersTypeGetCurrentPosition () const
 
- 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
 
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
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 >
void ModifyGradientByScalesOverSubRange (const IndexRangeType &subrange) override
 
void ModifyGradientByLearningRateOverSubRange (const IndexRangeType &subrange) override
 
 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 ()
 
 ~Object () override
 
bool PrintObservers (std::ostream &os, Indent indent) const
 
virtual void SetTimeStamp (const TimeStamp &time)
 
- 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 >
TInternalComputationValueType m_LearningRate
 
TInternalComputationValueType m_MinimumConvergenceValue
 
TInternalComputationValueType m_ConvergenceValue
 
MeasureType m_CurrentBestValue
 
ParametersType m_BestParameters
 
bool m_ReturnBestParametersAndValue { false }
 
DerivativeType m_PreviousGradient
 
- Protected Attributes inherited from itk::GradientDescentOptimizerBasev4Template< TInternalComputationValueType >
bool m_DoEstimateLearningRateAtEachIteration
 
bool m_DoEstimateLearningRateOnce
 
TInternalComputationValueType m_MaximumStepSizeInPhysicalUnits
 
bool m_UseConvergenceMonitoring
 
SizeValueType m_ConvergenceWindowSize
 
ConvergenceMonitoringType::Pointer m_ConvergenceMonitoring
 
DomainThreader< ThreadedIndexedContainerPartitioner, Self >::Pointer m_ModifyGradientByScalesThreader
 
DomainThreader< ThreadedIndexedContainerPartitioner, Self >::Pointer m_ModifyGradientByLearningRateThreader
 
bool m_Stop { false }
 
StopConditionObjectToObjectOptimizerEnum m_StopCondition
 
StopConditionDescriptionType m_StopConditionDescription
 
DerivativeType m_Gradient
 
- Protected Attributes inherited from itk::ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType >
MetricTypePointer m_Metric
 
ThreadIdType m_NumberOfWorkUnits
 
SizeValueType m_CurrentIteration
 
SizeValueType m_NumberOfIterations
 
MeasureType m_CurrentMetricValue
 
ScalesType m_Scales
 
ScalesType m_Weights
 
bool m_ScalesAreIdentity
 
ScalesEstimatorType::Pointer m_ScalesEstimator
 
bool m_WeightsAreIdentity
 
bool m_DoEstimateScales
 
- Protected Attributes inherited from itk::LightObject
std::atomic< int > m_ReferenceCount
 

Private Attributes

DomainThreader< ThreadedIndexedContainerPartitioner, Self >::Pointer m_EstimateNewtonStepThreader
 

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 60 of file itkQuasiNewtonOptimizerv4.h.

Member Typedef Documentation

◆ ConstPointer

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

Definition at line 70 of file itkQuasiNewtonOptimizerv4.h.

◆ DerivativeType

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

Definition at line 83 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 90 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 87 of file itkQuasiNewtonOptimizerv4.h.

◆ IndexRangeType

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

Definition at line 84 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 79 of file itkQuasiNewtonOptimizerv4.h.

◆ MeasureType

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

Definition at line 82 of file itkQuasiNewtonOptimizerv4.h.

◆ ParametersType

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

Definition at line 81 of file itkQuasiNewtonOptimizerv4.h.

◆ Pointer

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

Definition at line 69 of file itkQuasiNewtonOptimizerv4.h.

◆ Self

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

Standard class type aliases.

Definition at line 67 of file itkQuasiNewtonOptimizerv4.h.

◆ Superclass

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

Definition at line 68 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  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 .

◆ CreateAnother()

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 >.

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

Run-time type information (and related methods).

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

Store the best value and related parameters.

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

◆ ResetNewtonStep()

template<typename TInternalComputationValueType >
virtual void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::ResetNewtonStep ( IndexValueType  location)
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 140 of file itkQuasiNewtonOptimizerv4.h.

◆ m_BestPosition

template<typename TInternalComputationValueType >
ParametersType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_BestPosition
protected

Definition at line 139 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 138 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 130 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 205 of file itkQuasiNewtonOptimizerv4.h.

◆ m_HessianArray

template<typename TInternalComputationValueType >
HessianArrayType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_HessianArray
protected

The Hessian with local support

Definition at line 152 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 127 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 149 of file itkQuasiNewtonOptimizerv4.h.

◆ m_NewtonStep

template<typename TInternalComputationValueType >
DerivativeType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_NewtonStep
protected

The Quasi-Newton step

Definition at line 143 of file itkQuasiNewtonOptimizerv4.h.

◆ m_NewtonStepValidFlags

template<typename TInternalComputationValueType >
std::vector<bool> itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_NewtonStepValidFlags
protected

Valid flag for the Quasi-Newton steps

Definition at line 155 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 146 of file itkQuasiNewtonOptimizerv4.h.

◆ m_OptimalStep

template<typename TInternalComputationValueType >
ParametersType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_OptimalStep
protected

Definition at line 131 of file itkQuasiNewtonOptimizerv4.h.

◆ m_PreviousPosition

template<typename TInternalComputationValueType >
ParametersType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_PreviousPosition
protected

Definition at line 135 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 134 of file itkQuasiNewtonOptimizerv4.h.


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