ITK  4.8.0
Insight Segmentation and Registration Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Protected Attributes | Private Member Functions | List of all members
itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType > Class Template Reference

#include <itkRegularStepGradientDescentOptimizerv4.h>

+ Inheritance diagram for itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >:
+ Collaboration diagram for itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >:

Detailed Description

template<typename TInternalComputationValueType>
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 ReuglarStepGradientDescentOptimizer, 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, and Examples/RegistrationITKv4/MultiStageImageRegistration2.cxx.

Definition at line 46 of file itkRegularStepGradientDescentOptimizerv4.h.

Public Types

typedef CompensatedSummation
< InternalComputationValueType
CompensatedSummationType
 
typedef SmartPointer< const SelfConstPointer
 
typedef Superclass::DerivativeType DerivativeType
 
typedef Superclass::IndexRangeType IndexRangeType
 
typedef
TInternalComputationValueType 
InternalComputationValueType
 
typedef Superclass::MeasureType MeasureType
 
typedef Superclass::ParametersType ParametersType
 
typedef SmartPointer< SelfPointer
 
typedef Superclass::ScalesType ScalesType
 
typedef
RegularStepGradientDescentOptimizerv4 
Self
 
typedef
Superclass::StopConditionType 
StopConditionType
 
typedef
GradientDescentOptimizerv4Template
< TInternalComputationValueType > 
Superclass
 
- Public Types inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >
typedef SmartPointer< const SelfConstPointer
 
typedef Superclass::DerivativeType DerivativeType
 
typedef Superclass::IndexRangeType IndexRangeType
 
typedef
TInternalComputationValueType 
InternalComputationValueType
 
typedef Superclass::MeasureType MeasureType
 
typedef Superclass::ParametersType ParametersType
 
typedef SmartPointer< SelfPointer
 
typedef Superclass::ScalesType ScalesType
 
typedef
GradientDescentOptimizerv4Template 
Self
 
typedef
Superclass::StopConditionType 
StopConditionType
 
typedef
GradientDescentOptimizerBasev4Template
< TInternalComputationValueType > 
Superclass
 
- Public Types inherited from itk::GradientDescentOptimizerBasev4Template< TInternalComputationValueType >
typedef SmartPointer< const SelfConstPointer
 
typedef
itk::Function::WindowConvergenceMonitoringFunction
< TInternalComputationValueType > 
ConvergenceMonitoringType
 
typedef Superclass::DerivativeType DerivativeType
 
typedef
ThreadedIndexedContainerPartitioner::IndexRangeType 
IndexRangeType
 
typedef
TInternalComputationValueType 
InternalComputationValueType
 
typedef Superclass::MeasureType MeasureType
 
typedef Superclass::MetricType MetricType
 
typedef MetricType::Pointer MetricTypePointer
 
typedef Superclass::ParametersType ParametersType
 
typedef SmartPointer< SelfPointer
 
typedef Superclass::ScalesType ScalesType
 
typedef
GradientDescentOptimizerBasev4Template 
Self
 
typedef
Superclass::StopConditionDescriptionType 
StopConditionDescriptionType
 
typedef
Superclass::StopConditionReturnStringType 
StopConditionReturnStringType
 
enum  StopConditionType {
  MAXIMUM_NUMBER_OF_ITERATIONS,
  COSTFUNCTION_ERROR,
  UPDATE_PARAMETERS_ERROR,
  STEP_TOO_SMALL,
  CONVERGENCE_CHECKER_PASSED,
  GRADIENT_MAGNITUDE_TOLEARANCE,
  OTHER_ERROR
}
 
typedef
ObjectToObjectOptimizerBaseTemplate
< TInternalComputationValueType > 
Superclass
 
- Public Types inherited from itk::ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType >
typedef SmartPointer< const SelfConstPointer
 
typedef MetricType::DerivativeType DerivativeType
 
typedef MetricType::MeasureType MeasureType
 
typedef
ObjectToObjectMetricBaseTemplate
< TInternalComputationValueType > 
MetricType
 
typedef MetricType::Pointer MetricTypePointer
 
typedef
MetricType::NumberOfParametersType 
NumberOfParametersType
 
typedef OptimizerParameters
< TInternalComputationValueType > 
ParametersType
 
typedef SmartPointer< SelfPointer
 
typedef
OptimizerParameterScalesEstimatorTemplate
< TInternalComputationValueType > 
ScalesEstimatorType
 
typedef OptimizerParameters
< TInternalComputationValueType > 
ScalesType
 
typedef
ObjectToObjectOptimizerBaseTemplate 
Self
 
typedef std::ostringstream StopConditionDescriptionType
 
typedef std::string StopConditionReturnStringType
 
typedef Object Superclass
 
- Public Types inherited from itk::Object
typedef SmartPointer< const SelfConstPointer
 
typedef SmartPointer< SelfPointer
 
typedef Object Self
 
typedef LightObject Superclass
 
- Public Types inherited from itk::LightObject
typedef SmartPointer< const SelfConstPointer
 
typedef SmartPointer< SelfPointer
 
typedef LightObject Self
 

Public Member Functions

virtual ::itk::LightObject::Pointer CreateAnother () const
 
virtual void EstimateLearningRate () override
 
double GetCurrentStepLength () const
 
virtual const char * GetNameOfClass () const
 
virtual 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
 
- Public Member Functions inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >
virtual const
TInternalComputationValueType & 
GetConvergenceValue () const
 
virtual const
TInternalComputationValueType & 
GetLearningRate () const
 
virtual const
TInternalComputationValueType & 
GetMaximumStepSizeInPhysicalUnits () const
 
virtual void ResumeOptimization () override
 
virtual void SetConvergenceWindowSize (SizeValueType _arg)
 
virtual void SetLearningRate (TInternalComputationValueType _arg)
 
virtual void SetMaximumStepSizeInPhysicalUnits (TInternalComputationValueType _arg)
 
virtual void SetMinimumConvergenceValue (TInternalComputationValueType _arg)
 
virtual void StopOptimization (void) override
 
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 >
virtual SizeValueType GetCurrentIteration () const override
 
virtual const DerivativeTypeGetGradient () const
 
virtual SizeValueType GetNumberOfIterations () const override
 
virtual const StopConditionTypeGetStopCondition () const
 
virtual const
StopConditionReturnStringType 
GetStopConditionDescription () const override
 
virtual void SetNumberOfIterations (const SizeValueType numberOfIterations) override
 
virtual void ModifyGradientByScales ()
 
virtual void ModifyGradientByLearningRate ()
 
- Public Member Functions inherited from itk::ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType >
virtual const MeasureTypeGetCurrentMetricValue () const
 
virtual const ParametersTypeGetCurrentPosition () const
 
virtual const ThreadIdTypeGetNumberOfThreads () 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 SetNumberOfThreads (ThreadIdType number)
 
virtual void SetScalesEstimator (ScalesEstimatorType *_arg)
 
virtual void SetWeights (ScalesType _arg)
 
virtual void SetMetric (MetricType *_arg)
 
virtual MetricTypeGetModifiableMetric ()
 
virtual const MetricTypeGetMetric () 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
 
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
 
virtual void Register () const override
 
void RemoveAllObservers ()
 
void RemoveObserver (unsigned long tag)
 
void SetDebug (bool debugFlag) const
 
void SetMetaDataDictionary (const MetaDataDictionary &rhs)
 
virtual void SetReferenceCount (int) override
 
virtual void UnRegister () const noexceptoverride
 
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

virtual void AdvanceOneStep (void) override
 
virtual void PrintSelf (std::ostream &os, Indent indent) const override
 
 RegularStepGradientDescentOptimizerv4 ()
 
virtual ~RegularStepGradientDescentOptimizerv4 ()
 
virtual void ModifyGradientByScalesOverSubRange (const IndexRangeType &subrange) override
 
virtual void ModifyGradientByLearningRateOverSubRange (const IndexRangeType &subrange) override
 
- Protected Member Functions inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >
 GradientDescentOptimizerv4Template ()
 
virtual ~GradientDescentOptimizerv4Template ()
 
- Protected Member Functions inherited from itk::GradientDescentOptimizerBasev4Template< TInternalComputationValueType >
 GradientDescentOptimizerBasev4Template ()
 
virtual ~GradientDescentOptimizerBasev4Template ()
 
- Protected Member Functions inherited from itk::ObjectToObjectOptimizerBaseTemplate< TInternalComputationValueType >
 ObjectToObjectOptimizerBaseTemplate ()
 
virtual ~ObjectToObjectOptimizerBaseTemplate ()
 
- Protected Member Functions inherited from itk::Object
 Object ()
 
bool PrintObservers (std::ostream &os, Indent indent) const
 
virtual void SetTimeStamp (const TimeStamp &time)
 
virtual ~Object ()
 
- 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

MeasureType m_CurrentLearningRateRelaxation
 
TInternalComputationValueType m_GradientMagnitudeTolerance
 
TInternalComputationValueType m_MinimumStepLength
 
TInternalComputationValueType m_RelaxationFactor
 
- 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
 
- 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
 
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_NumberOfThreads
 
ScalesType m_Scales
 
bool m_ScalesAreIdentity
 
ScalesEstimatorType::Pointer m_ScalesEstimator
 
ScalesType m_Weights
 
bool m_WeightsAreIdentity
 
- Protected Attributes inherited from itk::LightObject
AtomicInt< int > m_ReferenceCount
 

Private Member Functions

void operator= (const Self &)
 
 RegularStepGradientDescentOptimizerv4 (const Self &)
 

Member Typedef Documentation

template<typename TInternalComputationValueType >
typedef CompensatedSummation< InternalComputationValueType > itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::CompensatedSummationType

Compensated summation type

Definition at line 77 of file itkRegularStepGradientDescentOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef SmartPointer< const Self > itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::ConstPointer

Definition at line 54 of file itkRegularStepGradientDescentOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef Superclass::DerivativeType itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::DerivativeType

Derivative type

Definition at line 67 of file itkRegularStepGradientDescentOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef Superclass::IndexRangeType itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::IndexRangeType

Definition at line 71 of file itkRegularStepGradientDescentOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef TInternalComputationValueType itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::InternalComputationValueType

It should be possible to derive the internal computation type from the class object.

Definition at line 60 of file itkRegularStepGradientDescentOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef Superclass::MeasureType itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::MeasureType

Metric type over which this class is templated

Definition at line 70 of file itkRegularStepGradientDescentOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef Superclass::ParametersType itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::ParametersType

Definition at line 73 of file itkRegularStepGradientDescentOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef SmartPointer< Self > itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::Pointer

Definition at line 53 of file itkRegularStepGradientDescentOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef Superclass::ScalesType itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::ScalesType

Definition at line 72 of file itkRegularStepGradientDescentOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef RegularStepGradientDescentOptimizerv4 itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::Self

Standard class typedefs.

Definition at line 51 of file itkRegularStepGradientDescentOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef Superclass::StopConditionType itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::StopConditionType

Definition at line 74 of file itkRegularStepGradientDescentOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef GradientDescentOptimizerv4Template<TInternalComputationValueType> itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::Superclass

Definition at line 52 of file itkRegularStepGradientDescentOptimizerv4.h.

Constructor & Destructor Documentation

template<typename TInternalComputationValueType >
itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::RegularStepGradientDescentOptimizerv4 ( )
protected

Default constructor

template<typename TInternalComputationValueType >
virtual itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::~RegularStepGradientDescentOptimizerv4 ( )
protectedvirtual

Destructor

template<typename TInternalComputationValueType >
itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::RegularStepGradientDescentOptimizerv4 ( const Self )
private

Member Function Documentation

template<typename TInternalComputationValueType >
virtual void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::AdvanceOneStep ( void  )
overrideprotectedvirtual

Advance one Step following the gradient direction. Includes transform update.

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

template<typename TInternalComputationValueType >
virtual::itk::LightObject::Pointer itk::RegularStepGradientDescentOptimizerv4< 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::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::EstimateLearningRate ( )
overridevirtual

Estimate the learning rate based on the current gradient.

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

template<typename TInternalComputationValueType >
double itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::GetCurrentStepLength ( ) const

Get current gradient step value

template<typename TInternalComputationValueType >
virtual const TInternalComputationValueType& itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::GetGradientMagnitudeTolerance ( ) const
virtual

Set/Get gradient magnitude tolerance value

template<typename TInternalComputationValueType >
virtual const TInternalComputationValueType& itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::GetMinimumStepLength ( ) const
virtual

Minimum step length (learning rate) value for convergence checking. The step length is decreased by relaxation factor if the step is too long, and the algorithm passes the local minimum. When the step length value reaches a small value, it would be treated as converged.

The default m_MinimumStepLength is set to 1e-4 to pass all tests.

template<typename TInternalComputationValueType >
virtual const char* itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::GetNameOfClass ( ) const
virtual

Run-time type information (and related methods).

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

template<typename TInternalComputationValueType >
virtual const TInternalComputationValueType& itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::GetRelaxationFactor ( ) const
virtual

Set/Get relaxation factor value

template<typename TInternalComputationValueType >
virtual void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::ModifyGradientByLearningRateOverSubRange ( const IndexRangeType subrange)
overrideprotectedvirtual

Modify the input gradient over a given index range.

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

template<typename TInternalComputationValueType >
virtual void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::ModifyGradientByScalesOverSubRange ( const IndexRangeType subrange)
overrideprotectedvirtual

Modify the input gradient over a given index range.

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

template<typename TInternalComputationValueType >
static Pointer itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::New ( )
static

New macro for creation of through a Smart Pointer

template<typename TInternalComputationValueType >
void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::operator= ( const Self )
private
template<typename TInternalComputationValueType >
virtual 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 >.

template<typename TInternalComputationValueType >
virtual void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::SetGradientMagnitudeTolerance ( TInternalComputationValueType  _arg)
virtual

Set/Get gradient magnitude tolerance value

template<typename TInternalComputationValueType >
virtual void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::SetMinimumStepLength ( TInternalComputationValueType  _arg)
virtual

Minimum step length (learning rate) value for convergence checking. The step length is decreased by relaxation factor if the step is too long, and the algorithm passes the local minimum. When the step length value reaches a small value, it would be treated as converged.

The default m_MinimumStepLength is set to 1e-4 to pass all tests.

template<typename TInternalComputationValueType >
virtual void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::SetRelaxationFactor ( TInternalComputationValueType  _arg)
virtual

Set/Get relaxation factor value

template<typename TInternalComputationValueType >
virtual void itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::StartOptimization ( bool  doOnlyInitialization = false)
overridevirtual

Start and run the optimization

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

Member Data Documentation

template<typename TInternalComputationValueType >
MeasureType itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::m_CurrentLearningRateRelaxation
protected

Current scale for learning rate

Definition at line 144 of file itkRegularStepGradientDescentOptimizerv4.h.

template<typename TInternalComputationValueType >
TInternalComputationValueType itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::m_GradientMagnitudeTolerance
protected

Minimum gradient magnitude value for convergence checking

Definition at line 141 of file itkRegularStepGradientDescentOptimizerv4.h.

template<typename TInternalComputationValueType >
TInternalComputationValueType itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::m_MinimumStepLength
protected

Minimum gradient step value for convergence checking

Definition at line 138 of file itkRegularStepGradientDescentOptimizerv4.h.

template<typename TInternalComputationValueType >
TInternalComputationValueType itk::RegularStepGradientDescentOptimizerv4< TInternalComputationValueType >::m_RelaxationFactor
protected

When the local minima is passed by taking a large step, the step size is adjusted by the relaxation factor, so we can take smaller steps toward the minimum point.

Definition at line 127 of file itkRegularStepGradientDescentOptimizerv4.h.


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