#include <itkGradientDescentOptimizer.h>

Inheritance diagram for itk::GradientDescentOptimizer:

Collaboration diagram for itk::GradientDescentOptimizer:

Public Types
using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = GradientDescentOptimizer

using	StopConditionGradientDescentOptimizerEnum = GradientDescentOptimizerEnums::StopConditionGradientDescentOptimizer

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
virtual ::itk::LightObject::Pointer	CreateAnother () const

virtual const char *	GetNameOfClass () const

Public Member Functions inherited from itk::SingleValuedNonLinearOptimizer
virtual ::itk::LightObject::Pointer	CreateAnother () const

virtual const CostFunctionType *	GetCostFunction () const

virtual CostFunctionType *	GetModifiableCostFunction ()

MeasureType	GetValue (const ParametersType &parameters) const

virtual void	SetCostFunction (CostFunctionType *costFunction)

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

virtual void	SetInitialPosition (const ParametersType &param)

void	SetScales (const ScalesType &scales)

virtual const ScalesType &	GetScales () const

virtual const ScalesType &	GetInverseScales () const

virtual const ParametersType &	GetCurrentPosition () 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

Command *	GetCommand (unsigned long tag)

bool	GetDebug () const

MetaDataDictionary &	GetMetaDataDictionary ()

const MetaDataDictionary &	GetMetaDataDictionary () const

virtual ModifiedTimeType	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

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
Pointer	Clone () const

virtual void	Delete ()

virtual int	GetReferenceCount () const

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

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 ()

DerivativeType	m_Gradient

bool	m_Maximize { false }

double	m_LearningRate { 1.0 }

bool	m_Stop { false }

double	m_Value { 0.0 }

StopConditionGradientDescentOptimizerEnum	m_StopCondition

SizeValueType	m_NumberOfIterations { 100 }

SizeValueType	m_CurrentIteration { 0 }

std::ostringstream	m_StopConditionDescription

virtual const bool &	GetMaximize () const

virtual void	SetMaximize (bool _arg)

virtual void	MaximizeOn ()

virtual void	MaximizeOff ()

bool	GetMinimize () const

void	SetMinimize (bool v)

void	MinimizeOn ()

void	MinimizeOff ()

virtual void	AdvanceOneStep ()

void	StartOptimization () override

void	ResumeOptimization ()

void	StopOptimization ()

virtual void	SetLearningRate (double _arg)

virtual const double &	GetLearningRate () const

virtual void	SetNumberOfIterations (SizeValueType _arg)

virtual const SizeValueType &	GetNumberOfIterations () const

virtual SizeValueType	GetCurrentIteration () const

virtual const double &	GetValue () const

virtual const StopConditionGradientDescentOptimizerEnum &	GetStopCondition () const

const std::string	GetStopConditionDescription () const override

virtual const DerivativeType &	GetGradient () const

	GradientDescentOptimizer ()

	~GradientDescentOptimizer () override=default

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

Additional Inherited Members
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 ()

	~Optimizer () override=default

virtual void	SetCurrentPosition (const ParametersType &param)

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

	~Object () override

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

virtual void	SetTimeStamp (const TimeStamp &timeStamp)

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 inherited from itk::SingleValuedNonLinearOptimizer
CostFunctionPointer	m_CostFunction

Protected Attributes inherited from itk::Optimizer
bool	m_ScalesInitialized { false }

ParametersType	m_CurrentPosition

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

Detailed Description

Implement a gradient descent optimizer.

GradientDescentOptimizer implements a simple gradient descent optimizer. At each iteration the current position is updated according to

$p_{n+1} = p_n + \mbox{learningRate} \, \frac{\partial f(p_n) }{\partial p_n}$

The learning rate is a fixed scalar defined via SetLearningRate(). The optimizer steps through a user defined number of iterations; no convergence checking is done.

Additionally, user can scale each component, $\partial f / \partial p$ , by setting a scaling vector using method SetScale().

See also: RegularStepGradientDescentOptimizer

Examples: Examples/RegistrationITKv4/ImageRegistration2.cxx, SphinxExamples/src/Core/Transform/MutualInformationAffine/Code.cxx, SphinxExamples/src/Registration/Common/MutualInformation/Code.cxx, and SphinxExamples/src/Registration/Common/PerformMultiModalityRegistrationWithMutualInformation/Code.cxx.

Definition at line 72 of file itkGradientDescentOptimizer.h.

Member Typedef Documentation

◆ ConstPointer

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

Definition at line 81 of file itkGradientDescentOptimizer.h.

◆ Pointer

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

Definition at line 80 of file itkGradientDescentOptimizer.h.

◆ Self

using itk::GradientDescentOptimizer::Self = GradientDescentOptimizer

Standard class type aliases.

Definition at line 78 of file itkGradientDescentOptimizer.h.

◆ StopConditionGradientDescentOptimizerEnum

using itk::GradientDescentOptimizer::StopConditionGradientDescentOptimizerEnum = GradientDescentOptimizerEnums::StopConditionGradientDescentOptimizer

Definition at line 90 of file itkGradientDescentOptimizer.h.

◆ Superclass

using itk::GradientDescentOptimizer::Superclass = SingleValuedNonLinearOptimizer

Definition at line 79 of file itkGradientDescentOptimizer.h.

Constructor & Destructor Documentation

◆ GradientDescentOptimizer()

itk::GradientDescentOptimizer::GradientDescentOptimizer ( )

protected

Methods to configure the cost function.

◆ ~GradientDescentOptimizer()

itk::GradientDescentOptimizer::~GradientDescentOptimizer ( )

overrideprotecteddefault

Methods to configure the cost function.

Member Function Documentation

◆ AdvanceOneStep()

virtual void itk::GradientDescentOptimizer::AdvanceOneStep ( )

virtual

Advance one step following the gradient direction.

Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer.

◆ CreateAnother()

virtual::itk::LightObject::Pointer itk::GradientDescentOptimizer::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::Object.

Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer.

◆ GetCurrentIteration()

virtual SizeValueType itk::GradientDescentOptimizer::GetCurrentIteration ( ) const

virtual

Get the current iteration number.

◆ GetGradient()

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

virtual

Get Gradient condition.

◆ GetLearningRate()

virtual const double& itk::GradientDescentOptimizer::GetLearningRate ( ) const

virtual

Get the learning rate.

◆ GetMaximize()

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

virtual

Methods to configure the cost function.

◆ GetMinimize()

bool itk::GradientDescentOptimizer::GetMinimize ( ) const

inline

Methods to configure the cost function.

Definition at line 105 of file itkGradientDescentOptimizer.h.

◆ GetNameOfClass()

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

virtual

Run-time type information (and related methods).

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer.

◆ GetNumberOfIterations()

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

virtual

Get the number of iterations.

◆ GetStopCondition()

virtual const StopConditionGradientDescentOptimizerEnum& itk::GradientDescentOptimizer::GetStopCondition ( ) const

virtual

Get Stop condition.

◆ GetStopConditionDescription()

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

overridevirtual

Methods to configure the cost function.

Reimplemented from itk::Optimizer.

◆ GetValue()

virtual const double& itk::GradientDescentOptimizer::GetValue ( ) const

virtual

Get the current value.

◆ MaximizeOff()

virtual void itk::GradientDescentOptimizer::MaximizeOff ( )

virtual

Methods to configure the cost function.

◆ MaximizeOn()

virtual void itk::GradientDescentOptimizer::MaximizeOn ( )

virtual

Methods to configure the cost function.

◆ MinimizeOff()

void itk::GradientDescentOptimizer::MinimizeOff ( )

inline

Methods to configure the cost function.

Definition at line 120 of file itkGradientDescentOptimizer.h.

◆ MinimizeOn()

void itk::GradientDescentOptimizer::MinimizeOn ( )

inline

Methods to configure the cost function.

Definition at line 115 of file itkGradientDescentOptimizer.h.

◆ New()

static Pointer itk::GradientDescentOptimizer::New ( )

static

Method for creation through the object factory.

◆ PrintSelf()

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

overrideprotectedvirtual

Methods to configure the cost function.

Reimplemented from itk::Object.

◆ ResumeOptimization()

void itk::GradientDescentOptimizer::ResumeOptimization ( )

Resume previously stopped optimization with current parameters

See also: StopOptimization.

◆ SetLearningRate()

virtual void itk::GradientDescentOptimizer::SetLearningRate ( double _arg )

virtual

Set the learning rate.

◆ SetMaximize()

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

virtual

Methods to configure the cost function.

◆ SetMinimize()

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

inline

Methods to configure the cost function.

Definition at line 110 of file itkGradientDescentOptimizer.h.

◆ SetNumberOfIterations()

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

virtual

Set the number of iterations.

◆ StartOptimization()

void itk::GradientDescentOptimizer::StartOptimization ( )

overridevirtual

Start optimization.

Reimplemented from itk::Optimizer.

◆ StopOptimization()

void itk::GradientDescentOptimizer::StopOptimization ( )

Stop optimization.

See also: ResumeOptimization

Member Data Documentation

◆ m_CurrentIteration

SizeValueType itk::GradientDescentOptimizer::m_CurrentIteration { 0 }

private

Methods to configure the cost function.

Definition at line 191 of file itkGradientDescentOptimizer.h.

◆ m_Gradient

DerivativeType itk::GradientDescentOptimizer::m_Gradient

protected

Methods to configure the cost function.

Definition at line 178 of file itkGradientDescentOptimizer.h.

◆ m_LearningRate

double itk::GradientDescentOptimizer::m_LearningRate { 1.0 }

protected

Methods to configure the cost function.

Definition at line 182 of file itkGradientDescentOptimizer.h.

◆ m_Maximize

bool itk::GradientDescentOptimizer::m_Maximize { false }

protected

Methods to configure the cost function.

Definition at line 180 of file itkGradientDescentOptimizer.h.

◆ m_NumberOfIterations

SizeValueType itk::GradientDescentOptimizer::m_NumberOfIterations { 100 }

private

Methods to configure the cost function.

Definition at line 190 of file itkGradientDescentOptimizer.h.

◆ m_Stop

bool itk::GradientDescentOptimizer::m_Stop { false }

private

Methods to configure the cost function.

Definition at line 185 of file itkGradientDescentOptimizer.h.

◆ m_StopCondition

StopConditionGradientDescentOptimizerEnum itk::GradientDescentOptimizer::m_StopCondition

private

Initial value:

{
    StopConditionGradientDescentOptimizerEnum::MaximumNumberOfIterations
  }

Methods to configure the cost function.

Definition at line 187 of file itkGradientDescentOptimizer.h.

◆ m_StopConditionDescription

std::ostringstream itk::GradientDescentOptimizer::m_StopConditionDescription

private

Methods to configure the cost function.

Definition at line 192 of file itkGradientDescentOptimizer.h.

◆ m_Value

double itk::GradientDescentOptimizer::m_Value { 0.0 }

private

Methods to configure the cost function.

Definition at line 186 of file itkGradientDescentOptimizer.h.

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

itkGradientDescentOptimizer.h

Public Types

Public Member Functions

Static Public Member Functions

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ ConstPointer

◆ Pointer

◆ Self

◆ StopConditionGradientDescentOptimizerEnum

◆ Superclass

Constructor & Destructor Documentation

◆ GradientDescentOptimizer()

◆ ~GradientDescentOptimizer()

Member Function Documentation

◆ AdvanceOneStep()

◆ CreateAnother()

◆ GetCurrentIteration()

◆ GetGradient()

◆ GetLearningRate()

◆ GetMaximize()

◆ GetMinimize()

◆ GetNameOfClass()

◆ GetNumberOfIterations()

◆ GetStopCondition()

◆ GetStopConditionDescription()

◆ GetValue()

◆ MaximizeOff()

◆ MaximizeOn()

◆ MinimizeOff()

◆ MinimizeOn()

◆ New()

◆ PrintSelf()

◆ ResumeOptimization()

◆ SetLearningRate()

◆ SetMaximize()

◆ SetMinimize()

◆ SetNumberOfIterations()

◆ StartOptimization()

◆ StopOptimization()

Member Data Documentation

◆ m_CurrentIteration

◆ m_Gradient

◆ m_LearningRate

◆ m_Maximize

◆ m_NumberOfIterations

◆ m_Stop

◆ m_StopCondition

◆ m_StopConditionDescription

◆ m_Value