#include <itkRegularStepGradientDescentBaseOptimizer.h>

Detailed Description

Implement a gradient descent optimizer.

Definition at line 58 of file itkRegularStepGradientDescentBaseOptimizer.h.

Inheritance diagram for itk::RegularStepGradientDescentBaseOptimizer:

Collaboration diagram for itk::RegularStepGradientDescentBaseOptimizer:

Public Types
using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = RegularStepGradientDescentBaseOptimizer

using	StopConditionEnum = RegularStepGradientDescentBaseOptimizerEnums::StopCondition

using	Superclass = SingleValuedNonLinearOptimizer

Public Types inherited from itk::SingleValuedNonLinearOptimizer
using	ConstPointer = SmartPointer< const Self >

using	CostFunctionPointer = CostFunctionType::Pointer

using	CostFunctionType = SingleValuedCostFunction

using	DerivativeType = CostFunctionType::DerivativeType

using	MeasureType = CostFunctionType::MeasureType

using	ParametersType = Superclass::ParametersType

using	Pointer = SmartPointer< Self >

using	Self = SingleValuedNonLinearOptimizer

using	Superclass = NonLinearOptimizer

Public Types inherited from itk::NonLinearOptimizer
using	ConstPointer = SmartPointer< const Self >

using	ParametersType = Superclass::ParametersType

using	Pointer = SmartPointer< Self >

using	ScalesType = Superclass::ScalesType

using	Self = NonLinearOptimizer

using	Superclass = Optimizer

Public Types inherited from itk::Optimizer
using	ConstPointer = SmartPointer< const Self >

using	ParametersType = OptimizerParameters< double >

using	Pointer = SmartPointer< Self >

using	ScalesType = Array< double >

using	Self = Optimizer

using	Superclass = Object

Public Types inherited from itk::Object
using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = Object

using	Superclass = LightObject

Public Types inherited from itk::LightObject
using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = LightObject

Public Member Functions
const char *	GetNameOfClass () const override

std::string	GetStopConditionDescription () const override

void	ResumeOptimization ()

void	StartOptimization () override

void	StopOptimization ()


virtual void	SetMaximize (bool _arg)

virtual const bool &	GetMaximize () const

virtual void	MaximizeOn ()

bool	GetMinimize () const

void	SetMinimize (bool v)

void	MinimizeOn ()

void	MinimizeOff ()


virtual void	SetMaximumStepLength (double _arg)

virtual void	SetMinimumStepLength (double _arg)

virtual void	SetRelaxationFactor (double _arg)

virtual void	SetNumberOfIterations (SizeValueType _arg)

virtual void	SetGradientMagnitudeTolerance (double _arg)

virtual const double &	GetCurrentStepLength () const

virtual const double &	GetMaximumStepLength () const

virtual const double &	GetMinimumStepLength () const

virtual const double &	GetRelaxationFactor () const

virtual const SizeValueType &	GetNumberOfIterations () const

virtual const double &	GetGradientMagnitudeTolerance () const

virtual unsigned int	GetCurrentIteration () const

virtual const StopConditionEnum &	GetStopCondition () const

virtual const MeasureType &	GetValue () const

virtual const DerivativeType &	GetGradient () const

Public Member Functions inherited from itk::SingleValuedNonLinearOptimizer
virtual CostFunctionType *	GetModifiableCostFunction ()

const char *	GetNameOfClass () const override

MeasureType	GetValue (const ParametersType &parameters) const

virtual void	SetCostFunction (CostFunctionType *costFunction)

const char *	GetNameOfClass () const override

Public Member Functions inherited from itk::Optimizer
virtual const ParametersType &	GetCurrentPosition () const

virtual const ParametersType &	GetInitialPosition () const

const char *	GetNameOfClass () const override

virtual std::string	GetStopConditionDescription () const

virtual void	SetInitialPosition (const ParametersType &param)

void	SetScales (const ScalesType &scales)

virtual void	StartOptimization ()

virtual const ScalesType &	GetScales () const

virtual const ScalesType &	GetInverseScales () const

Public Member Functions inherited from itk::Object
unsigned long	AddObserver (const EventObject &event, Command *cmd) const

unsigned long	AddObserver (const EventObject &event, std::function< void(const EventObject &)> function) const

LightObject::Pointer	CreateAnother () const override

virtual void	DebugOff () const

virtual void	DebugOn () const

Command *	GetCommand (unsigned long tag)

bool	GetDebug () const

MetaDataDictionary &	GetMetaDataDictionary ()

const MetaDataDictionary &	GetMetaDataDictionary () const

virtual ModifiedTimeType	GetMTime () const

const char *	GetNameOfClass () const override

virtual const TimeStamp &	GetTimeStamp () 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) const

void	SetDebug (bool debugFlag) const

void	SetReferenceCount (int) override

void	UnRegister () const noexcept override

void	SetMetaDataDictionary (const MetaDataDictionary &rhs)

void	SetMetaDataDictionary (MetaDataDictionary &&rrhs)

virtual void	SetObjectName (std::string _arg)

virtual const std::string &	GetObjectName () const

Public Member Functions inherited from itk::LightObject
Pointer	Clone () const

virtual Pointer	CreateAnother () const

virtual void	Delete ()

virtual const char *	GetNameOfClass () const

virtual int	GetReferenceCount () const

void	Print (std::ostream &os, Indent indent=0) const

virtual void	Register () const

virtual void	SetReferenceCount (int)

virtual void	UnRegister () const noexcept

Static Public Member Functions
static Pointer	New ()

Static Public Member Functions inherited from itk::SingleValuedNonLinearOptimizer
static Pointer	New ()

Static Public Member Functions inherited from itk::NonLinearOptimizer
static Pointer	New ()

Static Public Member Functions inherited from itk::Optimizer
static Pointer	New ()

Static Public Member Functions inherited from itk::Object
static bool	GetGlobalWarningDisplay ()

static void	GlobalWarningDisplayOff ()

static void	GlobalWarningDisplayOn ()

static Pointer	New ()

static void	SetGlobalWarningDisplay (bool val)

Static Public Member Functions inherited from itk::LightObject
static void	BreakOnError ()

static Pointer	New ()

Protected Member Functions
virtual void	AdvanceOneStep ()

void	PrintSelf (std::ostream &os, Indent indent) const override

	RegularStepGradientDescentBaseOptimizer ()

virtual void	StepAlongGradient (double, const DerivativeType &)

	~RegularStepGradientDescentBaseOptimizer () override=default

Protected Member Functions inherited from itk::SingleValuedNonLinearOptimizer
void	PrintSelf (std::ostream &os, Indent indent) const override

	SingleValuedNonLinearOptimizer ()

	~SingleValuedNonLinearOptimizer () override=default

Protected Member Functions inherited from itk::NonLinearOptimizer
	NonLinearOptimizer ()=default

	~NonLinearOptimizer () override

Protected Member Functions inherited from itk::Optimizer
	Optimizer ()

void	PrintSelf (std::ostream &os, Indent indent) const override

virtual void	SetCurrentPosition (const ParametersType &param)

	~Optimizer () override=default

Protected Member Functions inherited from itk::Object
	Object ()

bool	PrintObservers (std::ostream &os, Indent indent) const

void	PrintSelf (std::ostream &os, Indent indent) const override

virtual void	SetTimeStamp (const TimeStamp &timeStamp)

	~Object () override

Protected Member Functions inherited from itk::LightObject
virtual LightObject::Pointer	InternalClone () const

	LightObject ()

virtual void	PrintHeader (std::ostream &os, Indent indent) const

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

virtual void	PrintTrailer (std::ostream &os, Indent indent) const

virtual	~LightObject ()

Protected Attributes
SizeValueType	m_CurrentIteration {}

double	m_CurrentStepLength {}

DerivativeType	m_Gradient {}

double	m_GradientMagnitudeTolerance {}

bool	m_Maximize {}

double	m_MaximumStepLength {}

double	m_MinimumStepLength {}

SizeValueType	m_NumberOfIterations {}

DerivativeType	m_PreviousGradient {}

double	m_RelaxationFactor {}

bool	m_Stop { false }

StopConditionEnum	m_StopCondition {}

std::ostringstream	m_StopConditionDescription {}

MeasureType	m_Value {}

Protected Attributes inherited from itk::SingleValuedNonLinearOptimizer
CostFunctionPointer	m_CostFunction {}

Protected Attributes inherited from itk::Optimizer
ParametersType	m_CurrentPosition {}

bool	m_ScalesInitialized { false }

Protected Attributes inherited from itk::LightObject
std::atomic< int >	m_ReferenceCount {}

Member Typedef Documentation

◆ ConstPointer

using itk::RegularStepGradientDescentBaseOptimizer::ConstPointer = SmartPointer<const Self>

Definition at line 67 of file itkRegularStepGradientDescentBaseOptimizer.h.

◆ Pointer

using itk::RegularStepGradientDescentBaseOptimizer::Pointer = SmartPointer<Self>

Definition at line 66 of file itkRegularStepGradientDescentBaseOptimizer.h.

◆ Self

using itk::RegularStepGradientDescentBaseOptimizer::Self = RegularStepGradientDescentBaseOptimizer

Standard "Self" type alias.

Definition at line 64 of file itkRegularStepGradientDescentBaseOptimizer.h.

◆ StopConditionEnum

using itk::RegularStepGradientDescentBaseOptimizer::StopConditionEnum = RegularStepGradientDescentBaseOptimizerEnums::StopCondition

Definition at line 75 of file itkRegularStepGradientDescentBaseOptimizer.h.

◆ Superclass

using itk::RegularStepGradientDescentBaseOptimizer::Superclass = SingleValuedNonLinearOptimizer

Definition at line 65 of file itkRegularStepGradientDescentBaseOptimizer.h.

Constructor & Destructor Documentation

◆ RegularStepGradientDescentBaseOptimizer()

itk::RegularStepGradientDescentBaseOptimizer::RegularStepGradientDescentBaseOptimizer ( )

protected

◆ ~RegularStepGradientDescentBaseOptimizer()

itk::RegularStepGradientDescentBaseOptimizer::~RegularStepGradientDescentBaseOptimizer ( )

overrideprotecteddefault

Member Function Documentation

◆ AdvanceOneStep()

virtual void itk::RegularStepGradientDescentBaseOptimizer::AdvanceOneStep ( )

protectedvirtual

Advance one step following the gradient direction This method verifies if a change in direction is required and if a reduction in steplength is required.

◆ GetCurrentIteration()

virtual unsigned int itk::RegularStepGradientDescentBaseOptimizer::GetCurrentIteration ( ) const

virtual

Set/Get parameters to control the optimization process.

◆ GetCurrentStepLength()

virtual const double & itk::RegularStepGradientDescentBaseOptimizer::GetCurrentStepLength ( ) const

virtual

Set/Get parameters to control the optimization process.

◆ GetGradient()

virtual const DerivativeType & itk::RegularStepGradientDescentBaseOptimizer::GetGradient ( ) const

virtual

Set/Get parameters to control the optimization process.

◆ GetGradientMagnitudeTolerance()

virtual const double & itk::RegularStepGradientDescentBaseOptimizer::GetGradientMagnitudeTolerance ( ) const

virtual

Set/Get parameters to control the optimization process.

◆ GetMaximize()

virtual const bool & itk::RegularStepGradientDescentBaseOptimizer::GetMaximize ( ) const

virtual

Specify whether to minimize or maximize the cost function.

◆ GetMaximumStepLength()

virtual const double & itk::RegularStepGradientDescentBaseOptimizer::GetMaximumStepLength ( ) const

virtual

Set/Get parameters to control the optimization process.

◆ GetMinimize()

bool itk::RegularStepGradientDescentBaseOptimizer::GetMinimize ( ) const

inline

Specify whether to minimize or maximize the cost function.

Definition at line 91 of file itkRegularStepGradientDescentBaseOptimizer.h.

◆ GetMinimumStepLength()

virtual const double & itk::RegularStepGradientDescentBaseOptimizer::GetMinimumStepLength ( ) const

virtual

Set/Get parameters to control the optimization process.

◆ GetNameOfClass()

const char * itk::RegularStepGradientDescentBaseOptimizer::GetNameOfClass ( ) const

overridevirtual

See also: LightObject::GetNameOfClass()

Reimplemented from itk::NonLinearOptimizer.

Reimplemented in itk::RegularStepGradientDescentOptimizer, and itk::VersorTransformOptimizer.

◆ GetNumberOfIterations()

virtual const SizeValueType & itk::RegularStepGradientDescentBaseOptimizer::GetNumberOfIterations ( ) const

virtual

Set/Get parameters to control the optimization process.

◆ GetRelaxationFactor()

virtual const double & itk::RegularStepGradientDescentBaseOptimizer::GetRelaxationFactor ( ) const

virtual

Set/Get parameters to control the optimization process.

◆ GetStopCondition()

virtual const StopConditionEnum & itk::RegularStepGradientDescentBaseOptimizer::GetStopCondition ( ) const

virtual

Set/Get parameters to control the optimization process.

◆ GetStopConditionDescription()

std::string itk::RegularStepGradientDescentBaseOptimizer::GetStopConditionDescription ( ) const

overridevirtual

Get the reason for termination

Reimplemented from itk::Optimizer.

◆ GetValue()

virtual const MeasureType & itk::RegularStepGradientDescentBaseOptimizer::GetValue ( ) const

virtual

Set/Get parameters to control the optimization process.

◆ MaximizeOn()

virtual void itk::RegularStepGradientDescentBaseOptimizer::MaximizeOn ( )

virtual

Specify whether to minimize or maximize the cost function.

◆ MinimizeOff()

void itk::RegularStepGradientDescentBaseOptimizer::MinimizeOff ( )

inline

Specify whether to minimize or maximize the cost function.

Definition at line 106 of file itkRegularStepGradientDescentBaseOptimizer.h.

◆ MinimizeOn()

void itk::RegularStepGradientDescentBaseOptimizer::MinimizeOn ( )

inline

Specify whether to minimize or maximize the cost function.

Definition at line 101 of file itkRegularStepGradientDescentBaseOptimizer.h.

◆ New()

static Pointer itk::RegularStepGradientDescentBaseOptimizer::New ( )

static

Method for creation through the object factory.

◆ PrintSelf()

void itk::RegularStepGradientDescentBaseOptimizer::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::Optimizer.

◆ ResumeOptimization()

void itk::RegularStepGradientDescentBaseOptimizer::ResumeOptimization ( )

Resume previously stopped optimization with current parameters.

See also: StopOptimization

◆ SetGradientMagnitudeTolerance()

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetGradientMagnitudeTolerance ( double _arg )

virtual

Set/Get parameters to control the optimization process.

◆ SetMaximize()

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetMaximize ( bool _arg )

virtual

Specify whether to minimize or maximize the cost function.

◆ SetMaximumStepLength()

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetMaximumStepLength ( double _arg )

virtual

Set/Get parameters to control the optimization process.

◆ SetMinimize()

void itk::RegularStepGradientDescentBaseOptimizer::SetMinimize ( bool v )

inline

Specify whether to minimize or maximize the cost function.

Definition at line 96 of file itkRegularStepGradientDescentBaseOptimizer.h.

◆ SetMinimumStepLength()

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetMinimumStepLength ( double _arg )

virtual

Set/Get parameters to control the optimization process.

◆ SetNumberOfIterations()

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetNumberOfIterations ( SizeValueType _arg )

virtual

Set/Get parameters to control the optimization process.

◆ SetRelaxationFactor()

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetRelaxationFactor ( double _arg )

virtual

Set/Get parameters to control the optimization process.

◆ StartOptimization()

void itk::RegularStepGradientDescentBaseOptimizer::StartOptimization ( )

overridevirtual

Start optimization.

Reimplemented from itk::Optimizer.

◆ StepAlongGradient()

virtual void itk::RegularStepGradientDescentBaseOptimizer::StepAlongGradient	(	double	,
		const DerivativeType &
	)

inlineprotectedvirtual

Advance one step along the corrected gradient taking into account the steplength represented by factor. This method is invoked by AdvanceOneStep. It is expected to be overridden by optimization methods in non-vector spaces