#include <itkGradientDescentOptimizer.h>

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

Definition at line 72 of file 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 void	AdvanceOneStep ()

virtual SizeValueType	GetCurrentIteration () const

virtual const DerivativeType &	GetGradient () const

virtual const double &	GetLearningRate () const

const char *	GetNameOfClass () const override

virtual const SizeValueType &	GetNumberOfIterations () const

virtual const double &	GetValue () const

void	ResumeOptimization ()

virtual void	SetLearningRate (double _arg)

virtual void	SetNumberOfIterations (SizeValueType _arg)

void	StartOptimization () override

void	StopOptimization ()


virtual const bool &	GetMaximize () const

virtual void	SetMaximize (bool _arg)

virtual void	MaximizeOn ()

bool	GetMinimize () const

void	SetMinimize (bool v)

void	MinimizeOn ()

void	MinimizeOff ()


virtual const StopConditionGradientDescentOptimizerEnum &	GetStopCondition () const

std::string	GetStopConditionDescription () const override

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
	GradientDescentOptimizer ()

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

	~GradientDescentOptimizer () 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
DerivativeType	m_Gradient {}

double	m_LearningRate { 1.0 }

bool	m_Maximize { false }

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 {}

Private Attributes
SizeValueType	m_CurrentIteration { 0 }

SizeValueType	m_NumberOfIterations { 100 }

bool	m_Stop { false }

StopConditionGradientDescentOptimizerEnum	m_StopCondition

std::ostringstream	m_StopConditionDescription {}

double	m_Value { 0.0 }

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 89 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

◆ ~GradientDescentOptimizer()

itk::GradientDescentOptimizer::~GradientDescentOptimizer ( )

overrideprotecteddefault

Member Function Documentation

◆ AdvanceOneStep()

virtual void itk::GradientDescentOptimizer::AdvanceOneStep ( )

virtual

Advance one step following the gradient direction.

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()

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

overridevirtual

See also: LightObject::GetNameOfClass()

Reimplemented from itk::Object.

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()

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

overridevirtual

Get Stop condition.

Reimplemented from itk::Optimizer.

◆ GetValue()

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

virtual

Get the current value.

◆ 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 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::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

Definition at line 191 of file itkGradientDescentOptimizer.h.

◆ m_Gradient

DerivativeType itk::GradientDescentOptimizer::m_Gradient {}

protected

Definition at line 178 of file itkGradientDescentOptimizer.h.

◆ m_LearningRate

double itk::GradientDescentOptimizer::m_LearningRate { 1.0 }

protected

Definition at line 182 of file itkGradientDescentOptimizer.h.

◆ m_Maximize

bool itk::GradientDescentOptimizer::m_Maximize { false }

protected

Definition at line 180 of file itkGradientDescentOptimizer.h.

◆ m_NumberOfIterations

SizeValueType itk::GradientDescentOptimizer::m_NumberOfIterations { 100 }

private

Definition at line 190 of file itkGradientDescentOptimizer.h.

◆ m_Stop

bool itk::GradientDescentOptimizer::m_Stop { false }

private

Definition at line 185 of file itkGradientDescentOptimizer.h.

◆ m_StopCondition

StopConditionGradientDescentOptimizerEnum itk::GradientDescentOptimizer::m_StopCondition

private

Initial value:

{
    StopConditionGradientDescentOptimizerEnum::MaximumNumberOfIterations
  }

Definition at line 187 of file itkGradientDescentOptimizer.h.

◆ m_StopConditionDescription

std::ostringstream itk::GradientDescentOptimizer::m_StopConditionDescription {}

private

Definition at line 192 of file itkGradientDescentOptimizer.h.

◆ m_Value

double itk::GradientDescentOptimizer::m_Value { 0.0 }

private

Definition at line 186 of file itkGradientDescentOptimizer.h.

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

itkGradientDescentOptimizer.h

Detailed Description

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Protected Attributes

Private Attributes

Member Typedef Documentation

◆ ConstPointer

◆ Pointer

◆ Self

◆ StopConditionGradientDescentOptimizerEnum

◆ Superclass

Constructor & Destructor Documentation

◆ GradientDescentOptimizer()

◆ ~GradientDescentOptimizer()

Member Function Documentation

◆ AdvanceOneStep()

◆ GetCurrentIteration()

◆ GetGradient()

◆ GetLearningRate()

◆ GetMaximize()

◆ GetMinimize()

◆ GetNameOfClass()

◆ GetNumberOfIterations()

◆ GetStopCondition()

◆ GetStopConditionDescription()

◆ GetValue()

◆ 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