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itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType > Class Template Reference

#include <itkQuasiNewtonOptimizerv4.h>

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

Detailed Description

template<typename TInternalComputationValueType>
class itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >

Implement a Quasi-Newton optimizer with BFGS Hessian estimation.

Second order approximation of the cost function is usually more efficient since it estimates the descent or ascent direction more precisely. However, computation of Hessian is usually expensive or unavailable. Alternatively Quasi-Newton methods can estimate a Hessian from the gradients in previous steps. Here a specific Quasi-Newton method, BFGS, is used to compute the Quasi-Newton steps.

The Quasi-Newton method doesn't produce a valid step sometimes, ex. when the metric function is not a convex locally. In this scenario, the gradient step is used after being scaled properly.

A helper member object, m_ScalesEstimator may be set to estimate parameter scales and step scales. A step scale measures the magnitude of a step and is used for learning rate computation.

When m_ScalesEstimator is set, SetMaximumNewtonStepSizeInPhysicalUnits() may be called to set the maximum step size. If it is not called, m_MaximumNewtonStepSizeInPhysicalUnits defaults to lambda * OptimizerParameterScalesEstimatorTemplate::EstimateMaximumStepSize(), where lambda is in [1,5].

When m_ScalesEstimator is not set, the parameter scales and learning rates defaults to ones, or can be set by users manually.

Definition at line 59 of file itkQuasiNewtonOptimizerv4.h.

Public Types

typedef SmartPointer< const SelfConstPointer
 
typedef Superclass::DerivativeType DerivativeType
 
typedef std::vector< HessianTypeHessianArrayType
 
typedef itk::Array2D
< TInternalComputationValueType > 
HessianType
 
typedef Superclass::IndexRangeType IndexRangeType
 
typedef
TInternalComputationValueType 
InternalComputationValueType
 
typedef Superclass::MeasureType MeasureType
 
typedef Superclass::ParametersType ParametersType
 
typedef SmartPointer< SelfPointer
 
typedef
QuasiNewtonOptimizerv4Template 
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 EstimateNewtonStepOverSubRange (const IndexRangeType &subrange)
 
virtual const char * GetNameOfClass () const
 
virtual const DerivativeTypeGetNewtonStep () const
 
virtual void SetMaximumIterationsWithoutProgress (SizeValueType _arg)
 
virtual void SetMaximumNewtonStepSizeInPhysicalUnits (TInternalComputationValueType _arg)
 
virtual void StartOptimization (bool doOnlyInitialization=false) override
 
- Public Member Functions inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >
virtual void EstimateLearningRate ()
 
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
 
void CombineGradientNewtonStep ()
 
virtual bool ComputeHessianAndStepWithBFGS (IndexValueType location)
 
virtual void EstimateNewtonStep ()
 
void ModifyCombinedNewtonStep ()
 
virtual void PrintSelf (std::ostream &os, Indent indent) const override
 
 QuasiNewtonOptimizerv4Template ()
 
virtual void ResetNewtonStep (IndexValueType location)
 
virtual ~QuasiNewtonOptimizerv4Template ()
 
- Protected Member Functions inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >
 GradientDescentOptimizerv4Template ()
 
virtual ~GradientDescentOptimizerv4Template ()
 
virtual void ModifyGradientByScalesOverSubRange (const IndexRangeType &subrange) override
 
virtual void ModifyGradientByLearningRateOverSubRange (const IndexRangeType &subrange) override
 
- 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

SizeValueType m_BestIteration
 
ParametersType m_BestPosition
 
MeasureType m_BestValue
 
ParametersType m_CurrentPosition
 
HessianArrayType m_HessianArray
 
SizeValueType m_MaximumIterationsWithoutProgress
 
TInternalComputationValueType m_MaximumNewtonStepSizeInPhysicalUnits
 
DerivativeType m_NewtonStep
 
std::vector< bool > m_NewtonStepValidFlags
 
std::string m_NewtonStepWarning
 
ParametersType m_OptimalStep
 
ParametersType m_PreviousPosition
 
MeasureType m_PreviousValue
 
- Protected Attributes inherited from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >
ParametersType m_BestParameters
 
TInternalComputationValueType m_ConvergenceValue
 
MeasureType m_CurrentBestValue
 
TInternalComputationValueType m_LearningRate
 
TInternalComputationValueType m_MinimumConvergenceValue
 
DerivativeType m_PreviousGradient
 
bool m_ReturnBestParametersAndValue
 
- 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 &) ITK_DELETE_FUNCTION
 
 QuasiNewtonOptimizerv4Template (const Self &) ITK_DELETE_FUNCTION
 

Private Attributes

DomainThreader
< ThreadedIndexedContainerPartitioner,
Self >::Pointer 
m_EstimateNewtonStepThreader
 

Member Typedef Documentation

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

Definition at line 67 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef Superclass::DerivativeType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::DerivativeType

Definition at line 80 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef std::vector<HessianType> itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::HessianArrayType

Type for an array of Hessian matrix for local support

Definition at line 88 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef itk::Array2D<TInternalComputationValueType> itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::HessianType

Type for Hessian matrix in the Quasi-Newton method

Definition at line 85 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef Superclass::IndexRangeType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::IndexRangeType

Definition at line 81 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef TInternalComputationValueType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::InternalComputationValueType

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

Definition at line 73 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef Superclass::MeasureType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::MeasureType

Definition at line 79 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef Superclass::ParametersType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::ParametersType

Definition at line 78 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef SmartPointer< Self > itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::Pointer

Definition at line 66 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef QuasiNewtonOptimizerv4Template itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::Self

Standard class typedefs.

Definition at line 64 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef Superclass::StopConditionType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::StopConditionType

Definition at line 82 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >
typedef GradientDescentOptimizerv4Template<TInternalComputationValueType> itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::Superclass

Definition at line 65 of file itkQuasiNewtonOptimizerv4.h.

Constructor & Destructor Documentation

template<typename TInternalComputationValueType >
itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::QuasiNewtonOptimizerv4Template ( )
protected
template<typename TInternalComputationValueType >
virtual itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::~QuasiNewtonOptimizerv4Template ( )
protectedvirtual
template<typename TInternalComputationValueType >
itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::QuasiNewtonOptimizerv4Template ( const Self )
private

Member Function Documentation

template<typename TInternalComputationValueType >
virtual void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::AdvanceOneStep ( void  )
overrideprotectedvirtual

Advance one step using the Quasi-Newton step. When the Newton step is invalid, the gradient step will be used.

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

template<typename TInternalComputationValueType >
void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::CombineGradientNewtonStep ( )
protected

Combine a gradient step with a Newton step. The Newton step will be used when it is valid. Otherwise the gradient step will be used.

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

Estimate the next Hessian and step with BFGS method. The details of the method are described at http://en.wikipedia.org/wiki/BFGS_method .

template<typename TInternalComputationValueType >
virtual::itk::LightObject::Pointer itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::CreateAnother ( ) const
virtual

Create an object from an instance, potentially deferring to a factory. This method allows you to create an instance of an object that is exactly the same type as the referring object. This is useful in cases where an object has been cast back to a base class.

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

template<typename TInternalComputationValueType >
virtual void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::EstimateNewtonStep ( )
protectedvirtual

Estimate a Newton step

template<typename TInternalComputationValueType >
virtual void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::EstimateNewtonStepOverSubRange ( const IndexRangeType subrange)
virtual

Estimate the quasi-newton step over a given index range. This function is used in QuasiNewtonOptimizerv4EstimateNewtonStepThreaderTemplate class.

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

Run-time type information (and related methods).

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

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

Get the most recent Newton step.

template<typename TInternalComputationValueType >
void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::ModifyCombinedNewtonStep ( )
protected

Estimate and apply the learning rate(s) for a combined Newton step. A combined Newton step uses the Newton step by default and the gradient step when the Newton step is not valid.

The learning rate is less than 1.0 and is restricted by m_MaximumNewtonStepSizeInPhysicalUnits.

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

Method for creation through the object factory.

template<typename TInternalComputationValueType >
void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::operator= ( const Self )
private
template<typename TInternalComputationValueType >
virtual void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::PrintSelf ( std::ostream &  os,
Indent  indent 
) const
overrideprotectedvirtual

Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

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

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

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

Set the maximum tolerable number of iteration without any progress

template<typename TInternalComputationValueType >
virtual void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::SetMaximumNewtonStepSizeInPhysicalUnits ( TInternalComputationValueType  _arg)
virtual

Set the maximum step size.

When SetScalesEstimator is called by user, the optimizer will compute learning rates as m_MaximumNewtonStepSizeInPhysicalUnits / m_ScalesEstimator->EstimateStepScale(newtonStep).

If SetMaximumNewtonStepSizeInPhysicalUnits is not called by user, m_MaximumNewtonStepSizeInPhysicalUnits defaults to lambda * m_ScalesEstimator->EstimateMaximumStepSize(),

where EstimateMaximumStepSize returns one voxel spacing and lambda may be in [1,5] according to our experience.

template<typename TInternalComputationValueType >
virtual void itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::StartOptimization ( bool  doOnlyInitialization = false)
overridevirtual

Start and run the optimization

Reimplemented from itk::GradientDescentOptimizerv4Template< TInternalComputationValueType >.

Member Data Documentation

template<typename TInternalComputationValueType >
SizeValueType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_BestIteration
protected

Definition at line 137 of file itkQuasiNewtonOptimizerv4.h.

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

Definition at line 136 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >
MeasureType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_BestValue
protected

The best value so far and relevant information

Definition at line 135 of file itkQuasiNewtonOptimizerv4.h.

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

The information about the current step

Definition at line 127 of file itkQuasiNewtonOptimizerv4.h.

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

Threader for Newton step estimation.

Definition at line 198 of file itkQuasiNewtonOptimizerv4.h.

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

The Hessian with local support

Definition at line 149 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >
SizeValueType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_MaximumIterationsWithoutProgress
protected

The maximum tolerable number of iteration without any progress

Definition at line 124 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >
TInternalComputationValueType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_MaximumNewtonStepSizeInPhysicalUnits
protected

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

Definition at line 146 of file itkQuasiNewtonOptimizerv4.h.

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

The Quasi-Newton step

Definition at line 140 of file itkQuasiNewtonOptimizerv4.h.

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

Valid flag for the Quasi-Newton steps

Definition at line 152 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >
std::string itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_NewtonStepWarning
protected

Warning message during Quasi-Newton step estimation

Definition at line 143 of file itkQuasiNewtonOptimizerv4.h.

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

Definition at line 128 of file itkQuasiNewtonOptimizerv4.h.

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

Definition at line 132 of file itkQuasiNewtonOptimizerv4.h.

template<typename TInternalComputationValueType >
MeasureType itk::QuasiNewtonOptimizerv4Template< TInternalComputationValueType >::m_PreviousValue
protected

The information about the previous step

Definition at line 131 of file itkQuasiNewtonOptimizerv4.h.


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