#include <itkGradientDescentLineSearchOptimizerv4.h>

Inheritance diagram for itk::GradientDescentLineSearchOptimizerv4:

Collaboration diagram for itk::GradientDescentLineSearchOptimizerv4:

Public Types
typedef SmartPointer< const Self >	ConstPointer
typedef itk::Function::WindowConvergenceMonitoringFunction < double >	ConvergenceMonitoringType
typedef Superclass::DerivativeType	DerivativeType
typedef Superclass::InternalComputationValueType	InternalComputationValueType
typedef Superclass::MeasureType	MeasureType
typedef SmartPointer< Self >	Pointer
typedef GradientDescentLineSearchOptimizerv4	Self
typedef GradientDescentOptimizerv4	Superclass
Public Types inherited from itk::GradientDescentOptimizerv4
Public Types inherited from itk::GradientDescentOptimizerBasev4
typedef Superclass::MetricType	MetricType
typedef MetricType::Pointer	MetricTypePointer
typedef std::ostringstream	StopConditionDescriptionType
typedef std::string	StopConditionReturnStringType
enum	StopConditionType { MAXIMUM_NUMBER_OF_ITERATIONS, COSTFUNCTION_ERROR, UPDATE_PARAMETERS_ERROR, STEP_TOO_SMALL, QUASI_NEWTON_STEP_ERROR, CONVERGENCE_CHECKER_PASSED, OTHER_ERROR }
Public Types inherited from itk::ObjectToObjectOptimizerBase
typedef MetricType::NumberOfParametersType	NumberOfParametersType
typedef OptimizerParameters < double >	ParametersType
typedef OptimizerParameters < double >	ScalesType
Public Types inherited from itk::Object
Public Types inherited from itk::LightObject

Public Member Functions
virtual ::itk::LightObject::Pointer	CreateAnother (void) const
virtual const char *	GetNameOfClass () const

virtual void	SetEpsilon (InternalComputationValueType _arg)
virtual InternalComputationValueType	GetEpsilon ()

virtual void	SetLowerLimit (InternalComputationValueType _arg)
virtual InternalComputationValueType	GetLowerLimit ()
virtual void	SetUpperLimit (InternalComputationValueType _arg)
virtual InternalComputationValueType	GetUpperLimit ()
virtual void	SetMaximumLineSearchIterations (unsigned int _arg)
virtual unsigned int	GetMaximumLineSearchIterations ()
Public Member Functions inherited from itk::GradientDescentOptimizerv4
virtual void	EstimateLearningRate ()
virtual const InternalComputationValueType &	GetConvergenceValue ()
virtual const InternalComputationValueType &	GetLearningRate ()
virtual const InternalComputationValueType &	GetMaximumStepSizeInPhysicalUnits ()
virtual void	ResumeOptimization ()
virtual void	SetConvergenceWindowSize (SizeValueType _arg)
virtual void	SetLearningRate (InternalComputationValueType _arg)
virtual void	SetMaximumStepSizeInPhysicalUnits (InternalComputationValueType _arg)
virtual void	SetMinimumConvergenceValue (InternalComputationValueType _arg)
virtual void	SetScalesEstimator (OptimizerParameterScalesEstimator *_arg)
virtual void	StartOptimization ()
virtual void	StopOptimization (void)
virtual void	SetDoEstimateScales (bool _arg)
virtual const bool &	GetDoEstimateScales ()
virtual void	DoEstimateScalesOn ()
virtual void	DoEstimateScalesOff ()
virtual void	SetDoEstimateLearningRateAtEachIteration (bool _arg)
virtual const bool &	GetDoEstimateLearningRateAtEachIteration ()
virtual void	DoEstimateLearningRateAtEachIterationOn ()
virtual void	DoEstimateLearningRateAtEachIterationOff ()
virtual void	SetDoEstimateLearningRateOnce (bool _arg)
virtual const bool &	GetDoEstimateLearningRateOnce ()
virtual void	DoEstimateLearningRateOnceOn ()
virtual void	DoEstimateLearningRateOnceOff ()
virtual void	SetReturnBestParametersAndValue (bool _arg)
virtual const bool &	GetReturnBestParametersAndValue ()
virtual void	ReturnBestParametersAndValueOn ()
virtual void	ReturnBestParametersAndValueOff ()
Public Member Functions inherited from itk::GradientDescentOptimizerBasev4
virtual SizeValueType	GetCurrentIteration () const
virtual const DerivativeType &	GetGradient ()
virtual const SizeValueType &	GetNumberOfIterations ()
virtual const StopConditionType &	GetStopCondition ()
virtual const StopConditionReturnStringType	GetStopConditionDescription () const
virtual void	SetNumberOfIterations (SizeValueType _arg)
virtual void	ModifyGradientByScales ()
virtual void	ModifyGradientByLearningRate ()
Public Member Functions inherited from itk::ObjectToObjectOptimizerBase
virtual const MeasureType &	GetCurrentMetricValue ()
const ParametersType &	GetCurrentPosition ()
virtual const ThreadIdType &	GetNumberOfThreads ()
virtual const ScalesType &	GetScales ()
virtual const bool &	GetScalesAreIdentity ()
const MeasureType &	GetValue ()
virtual void	SetNumberOfThreads (ThreadIdType number)
virtual void	SetScales (ScalesType _arg)
virtual MetricType *	GetMetric ()
virtual void	SetMetric (MetricType *_arg)
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
Command *	GetCommand (unsigned long tag)
bool	GetDebug () const
MetaDataDictionary &	GetMetaDataDictionary (void)
const MetaDataDictionary &	GetMetaDataDictionary (void) const
virtual unsigned long	GetMTime () const
virtual const TimeStamp &	GetTimeStamp () const
bool	HasObserver (const EventObject &event) const
void	InvokeEvent (const EventObject &)
void	InvokeEvent (const EventObject &) const
virtual void	Modified () const
virtual void	Register () const
void	RemoveAllObservers ()
void	RemoveObserver (unsigned long tag)
void	SetDebug (bool debugFlag) const
void	SetMetaDataDictionary (const MetaDataDictionary &rhs)
virtual void	SetReferenceCount (int)
virtual void	UnRegister () 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 ()

Protected Member Functions
virtual void	AdvanceOneStep (void)
InternalComputationValueType	GoldenSectionSearch (InternalComputationValueType a, InternalComputationValueType b, InternalComputationValueType c)
	GradientDescentLineSearchOptimizerv4 ()
virtual void	PrintSelf (std::ostream &os, Indent indent) const
virtual	~GradientDescentLineSearchOptimizerv4 ()
Protected Member Functions inherited from itk::GradientDescentOptimizerv4
	GradientDescentOptimizerv4 ()
virtual	~GradientDescentOptimizerv4 ()
virtual void	ModifyGradientByScalesOverSubRange (const IndexRangeType &subrange)
virtual void	ModifyGradientByLearningRateOverSubRange (const IndexRangeType &subrange)
Protected Member Functions inherited from itk::GradientDescentOptimizerBasev4
	GradientDescentOptimizerBasev4 ()
virtual	~GradientDescentOptimizerBasev4 ()
Protected Member Functions inherited from itk::ObjectToObjectOptimizerBase
	ObjectToObjectOptimizerBase ()
virtual	~ObjectToObjectOptimizerBase ()
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
InternalComputationValueType	m_Epsilon
unsigned int	m_LineSearchIterations
InternalComputationValueType	m_LowerLimit
unsigned int	m_MaximumLineSearchIterations
InternalComputationValueType	m_Phi
InternalComputationValueType	m_Resphi
InternalComputationValueType	m_UpperLimit
Protected Attributes inherited from itk::GradientDescentOptimizerv4
ParametersType	m_BestParameters
ConvergenceMonitoringType::Pointer	m_ConvergenceMonitoring
InternalComputationValueType	m_ConvergenceValue
SizeValueType	m_ConvergenceWindowSize
MeasureType	m_CurrentBestValue
InternalComputationValueType	m_LearningRate
InternalComputationValueType	m_MaximumStepSizeInPhysicalUnits
InternalComputationValueType	m_MinimumConvergenceValue
bool	m_ReturnBestParametersAndValue
OptimizerParameterScalesEstimator::Pointer	m_ScalesEstimator
Protected Attributes inherited from itk::GradientDescentOptimizerBasev4
SizeValueType	m_CurrentIteration
DerivativeType	m_Gradient
GradientDescentOptimizerBasev4ModifyGradientByLearningRateThreader::Pointer	m_ModifyGradientByLearningRateThreader
GradientDescentOptimizerBasev4ModifyGradientByScalesThreader::Pointer	m_ModifyGradientByScalesThreader
SizeValueType	m_NumberOfIterations
bool	m_Stop
StopConditionType	m_StopCondition
StopConditionDescriptionType	m_StopConditionDescription
Protected Attributes inherited from itk::ObjectToObjectOptimizerBase
MeasureType	m_CurrentMetricValue
MetricTypePointer	m_Metric
ThreadIdType	m_NumberOfThreads
ScalesType	m_Scales
bool	m_ScalesAreIdentity

Private Member Functions
	GradientDescentLineSearchOptimizerv4 (const Self &)
void	operator= (const Self &)

Detailed Description

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 58 of file itkGradientDescentLineSearchOptimizerv4.h.

Member Typedef Documentation

typedef SmartPointer< const Self > itk::GradientDescentLineSearchOptimizerv4::ConstPointer

Reimplemented from itk::GradientDescentOptimizerv4.

Reimplemented in itk::ConjugateGradientLineSearchOptimizerv4.

Definition at line 66 of file itkGradientDescentLineSearchOptimizerv4.h.

typedef itk::Function::WindowConvergenceMonitoringFunction<double> itk::GradientDescentLineSearchOptimizerv4::ConvergenceMonitoringType

Type for the convergence checker

Reimplemented from itk::GradientDescentOptimizerv4.

Reimplemented in itk::ConjugateGradientLineSearchOptimizerv4.

Definition at line 82 of file itkGradientDescentLineSearchOptimizerv4.h.

typedef Superclass::DerivativeType itk::GradientDescentLineSearchOptimizerv4::DerivativeType

Derivative type

Reimplemented from itk::GradientDescentOptimizerv4.

Reimplemented in itk::ConjugateGradientLineSearchOptimizerv4.

Definition at line 72 of file itkGradientDescentLineSearchOptimizerv4.h.

typedef Superclass::InternalComputationValueType itk::GradientDescentLineSearchOptimizerv4::InternalComputationValueType

Internal computation type, for maintaining a desired precision

Reimplemented from itk::GradientDescentOptimizerv4.

Reimplemented in itk::ConjugateGradientLineSearchOptimizerv4.

Definition at line 79 of file itkGradientDescentLineSearchOptimizerv4.h.

typedef Superclass::MeasureType itk::GradientDescentLineSearchOptimizerv4::MeasureType

Metric type over which this class is templated

Reimplemented from itk::GradientDescentOptimizerv4.

Reimplemented in itk::ConjugateGradientLineSearchOptimizerv4.

Definition at line 78 of file itkGradientDescentLineSearchOptimizerv4.h.

typedef SmartPointer< Self > itk::GradientDescentLineSearchOptimizerv4::Pointer

Reimplemented from itk::GradientDescentOptimizerv4.

Reimplemented in itk::ConjugateGradientLineSearchOptimizerv4.

Definition at line 65 of file itkGradientDescentLineSearchOptimizerv4.h.

typedef GradientDescentLineSearchOptimizerv4 itk::GradientDescentLineSearchOptimizerv4::Self

Standard class typedefs.

Reimplemented from itk::GradientDescentOptimizerv4.

Reimplemented in itk::ConjugateGradientLineSearchOptimizerv4.

Definition at line 63 of file itkGradientDescentLineSearchOptimizerv4.h.

typedef GradientDescentOptimizerv4 itk::GradientDescentLineSearchOptimizerv4::Superclass

Reimplemented from itk::GradientDescentOptimizerv4.

Reimplemented in itk::ConjugateGradientLineSearchOptimizerv4.

Definition at line 64 of file itkGradientDescentLineSearchOptimizerv4.h.

Constructor & Destructor Documentation

itk::GradientDescentLineSearchOptimizerv4::GradientDescentLineSearchOptimizerv4 ( )

protected

Default constructor

virtual itk::GradientDescentLineSearchOptimizerv4::~GradientDescentLineSearchOptimizerv4 ( )

protectedvirtual

Destructor

itk::GradientDescentLineSearchOptimizerv4::GradientDescentLineSearchOptimizerv4 ( const Self & )

private

Member Function Documentation

virtual void itk::GradientDescentLineSearchOptimizerv4::AdvanceOneStep ( void )

protectedvirtual

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

Reimplemented from itk::GradientDescentOptimizerv4.

Reimplemented in itk::ConjugateGradientLineSearchOptimizerv4.

virtual::itk::LightObject::Pointer itk::GradientDescentLineSearchOptimizerv4::CreateAnother ( void ) 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::GradientDescentOptimizerv4.

Reimplemented in itk::ConjugateGradientLineSearchOptimizerv4.

virtual InternalComputationValueType itk::GradientDescentLineSearchOptimizerv4::GetEpsilon ( )

virtual

The epsilon determines the accuracy of the line search i.e. the energy alteration that is considered convergent.

virtual InternalComputationValueType itk::GradientDescentLineSearchOptimizerv4::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.

virtual unsigned int itk::GradientDescentLineSearchOptimizerv4::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.

virtual const char* itk::GradientDescentLineSearchOptimizerv4::GetNameOfClass ( ) const

virtual

Run-time type information (and related methods).

Reimplemented from itk::GradientDescentOptimizerv4.

Reimplemented in itk::ConjugateGradientLineSearchOptimizerv4.

virtual InternalComputationValueType itk::GradientDescentLineSearchOptimizerv4::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.

InternalComputationValueType itk::GradientDescentLineSearchOptimizerv4::GoldenSectionSearch	(	InternalComputationValueType	a,
		InternalComputationValueType	b,
		InternalComputationValueType	c
	)

protected

static Pointer itk::GradientDescentLineSearchOptimizerv4::New ( )

static

New macro for creation of through a Smart Pointer

Reimplemented from itk::GradientDescentOptimizerv4.

Reimplemented in itk::ConjugateGradientLineSearchOptimizerv4.

void itk::GradientDescentLineSearchOptimizerv4::operator= ( const Self & )

private

Mutex lock to protect modification to the reference count

Reimplemented from itk::GradientDescentOptimizerv4.

Reimplemented in itk::ConjugateGradientLineSearchOptimizerv4.

virtual void itk::GradientDescentLineSearchOptimizerv4::PrintSelf	(	std::ostream &	os,
		Indent	indent
	)		const

protectedvirtual

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::GradientDescentOptimizerv4.

Reimplemented in itk::ConjugateGradientLineSearchOptimizerv4.

virtual void itk::GradientDescentLineSearchOptimizerv4::SetEpsilon ( InternalComputationValueType _arg )

virtual

The epsilon determines the accuracy of the line search i.e. the energy alteration that is considered convergent.

virtual void itk::GradientDescentLineSearchOptimizerv4::SetLowerLimit ( InternalComputationValueType _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.

virtual void itk::GradientDescentLineSearchOptimizerv4::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.

virtual void itk::GradientDescentLineSearchOptimizerv4::SetUpperLimit ( InternalComputationValueType _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.