#include <itkGradientDescentOptimizer2.h>

Detailed Description

Implement a gradient descent optimizer.

GradientDescentOptimizer2 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 of the $\partial f / \partial p$ but setting a scaling vector using method SetScale().

The difference of this class with the itk::GradientDescentOptimizer is that it's based on the ScaledSingleValuedNonLinearOptimizer

See also: ScaledSingleValuedNonLinearOptimizer

Definition at line 54 of file itkGradientDescentOptimizer2.h.

Inheritance diagram for itk::GradientDescentOptimizer2:

Public Types
typedef SmartPointer< const Self >	ConstPointer

typedef Superclass::CostFunctionType	CostFunctionType

typedef Superclass::DerivativeType	DerivativeType

typedef Superclass::MeasureType	MeasureType

typedef Superclass::ParametersType	ParametersType

typedef SmartPointer< Self >	Pointer

typedef Superclass::ScaledCostFunctionPointer	ScaledCostFunctionPointer

typedef Superclass::ScaledCostFunctionType	ScaledCostFunctionType

typedef Superclass::ScalesType	ScalesType

typedef GradientDescentOptimizer2	Self

enum	StopConditionType { MaximumNumberOfIterations , MetricError , MinimumStepSize }

typedef ScaledSingleValuedNonLinearOptimizer	Superclass

Public Types inherited from itk::ScaledSingleValuedNonLinearOptimizer
typedef SmartPointer< const Self >	ConstPointer

typedef Superclass::CostFunctionType	CostFunctionType

typedef Superclass::DerivativeType	DerivativeType

typedef Superclass::MeasureType	MeasureType

typedef Superclass::ParametersType	ParametersType

typedef SmartPointer< Self >	Pointer

typedef ScaledCostFunctionType::Pointer	ScaledCostFunctionPointer

typedef ScaledSingleValuedCostFunction	ScaledCostFunctionType

typedef NonLinearOptimizer::ScalesType	ScalesType

typedef ScaledSingleValuedNonLinearOptimizer	Self

typedef SingleValuedNonLinearOptimizer	Superclass

Public Member Functions
virtual void	AdvanceOneStep (void)

virtual const char *	GetClassName () const

virtual unsigned int	GetCurrentIteration () const

virtual const DerivativeType &	GetGradient ()

virtual const double &	GetLearningRate ()

virtual const unsigned long &	GetNumberOfIterations ()

virtual const DerivativeType &	GetSearchDirection ()

virtual const StopConditionType &	GetStopCondition ()

virtual const double &	GetValue ()

virtual void	MetricErrorResponse (ExceptionObject &err)

virtual void	ResumeOptimization (void)

virtual void	SetLearningRate (double _arg)

virtual void	SetNumberOfIterations (unsigned long _arg)

virtual void	SetUseOpenMP (bool _arg)

void	StartOptimization (void) override

virtual void	StopOptimization (void)

Public Member Functions inherited from itk::ScaledSingleValuedNonLinearOptimizer
virtual const char *	GetClassName () const

const ParametersType &	GetCurrentPosition (void) const override

virtual bool	GetMaximize () const

virtual const ScaledCostFunctionType *	GetScaledCostFunction ()

virtual const ParametersType &	GetScaledCurrentPosition ()

bool	GetUseScales (void) const

virtual void	InitializeScales (void)

virtual void	MaximizeOff ()

virtual void	MaximizeOn ()

void	SetCostFunction (CostFunctionType *costFunction) override

virtual void	SetMaximize (bool _arg)

virtual void	SetUseScales (bool arg)

Static Public Member Functions
static Pointer	New ()

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

Protected Member Functions
	GradientDescentOptimizer2 ()

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

	~GradientDescentOptimizer2 () override

Protected Member Functions inherited from itk::ScaledSingleValuedNonLinearOptimizer
virtual void	GetScaledDerivative (const ParametersType &parameters, DerivativeType &derivative) const

virtual MeasureType	GetScaledValue (const ParametersType &parameters) const

virtual void	GetScaledValueAndDerivative (const ParametersType &parameters, MeasureType &value, DerivativeType &derivative) const

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

	ScaledSingleValuedNonLinearOptimizer ()

void	SetCurrentPosition (const ParametersType &param) override

virtual void	SetScaledCurrentPosition (const ParametersType &parameters)

	~ScaledSingleValuedNonLinearOptimizer () override

Protected Attributes
unsigned long	m_CurrentIteration

DerivativeType	m_Gradient

double	m_LearningRate

unsigned long	m_NumberOfIterations

DerivativeType	m_SearchDirection

bool	m_Stop

StopConditionType	m_StopCondition

double	m_Value

Protected Attributes inherited from itk::ScaledSingleValuedNonLinearOptimizer
ScaledCostFunctionPointer	m_ScaledCostFunction

ParametersType	m_ScaledCurrentPosition

Private Member Functions
	GradientDescentOptimizer2 (const Self &)

void	operator= (const Self &)

Private Attributes
bool	m_UseOpenMP

Member Typedef Documentation

◆ ConstPointer

typedef SmartPointer< const Self > itk::GradientDescentOptimizer2::ConstPointer

Definition at line 63 of file itkGradientDescentOptimizer2.h.

◆ CostFunctionType

typedef Superclass::CostFunctionType itk::GradientDescentOptimizer2::CostFunctionType

Definition at line 75 of file itkGradientDescentOptimizer2.h.

◆ DerivativeType

typedef Superclass::DerivativeType itk::GradientDescentOptimizer2::DerivativeType

Definition at line 74 of file itkGradientDescentOptimizer2.h.

◆ MeasureType

typedef Superclass::MeasureType itk::GradientDescentOptimizer2::MeasureType

Typedefs inherited from the superclass.

Definition at line 72 of file itkGradientDescentOptimizer2.h.

◆ ParametersType

typedef Superclass::ParametersType itk::GradientDescentOptimizer2::ParametersType

Definition at line 73 of file itkGradientDescentOptimizer2.h.

◆ Pointer

typedef SmartPointer< Self > itk::GradientDescentOptimizer2::Pointer

Definition at line 62 of file itkGradientDescentOptimizer2.h.

◆ ScaledCostFunctionPointer

typedef Superclass::ScaledCostFunctionPointer itk::GradientDescentOptimizer2::ScaledCostFunctionPointer

Definition at line 78 of file itkGradientDescentOptimizer2.h.

◆ ScaledCostFunctionType

typedef Superclass::ScaledCostFunctionType itk::GradientDescentOptimizer2::ScaledCostFunctionType

Definition at line 77 of file itkGradientDescentOptimizer2.h.

◆ ScalesType

typedef Superclass::ScalesType itk::GradientDescentOptimizer2::ScalesType

Definition at line 76 of file itkGradientDescentOptimizer2.h.

◆ Self

typedef GradientDescentOptimizer2 itk::GradientDescentOptimizer2::Self

Standard class typedefs.

Definition at line 60 of file itkGradientDescentOptimizer2.h.

◆ Superclass

typedef ScaledSingleValuedNonLinearOptimizer itk::GradientDescentOptimizer2::Superclass

Definition at line 61 of file itkGradientDescentOptimizer2.h.

Member Enumeration Documentation

◆ StopConditionType

enum itk::GradientDescentOptimizer2::StopConditionType

Codes of stopping conditions The MinimumStepSize stopcondition never occurs, but may be implemented in inheriting classes

Enumerator
MaximumNumberOfIterations
MetricError
MinimumStepSize

Definition at line 83 of file itkGradientDescentOptimizer2.h.

Constructor & Destructor Documentation

◆ GradientDescentOptimizer2() [1/2]

itk::GradientDescentOptimizer2::GradientDescentOptimizer2 ( )

protected

◆ ~GradientDescentOptimizer2()

itk::GradientDescentOptimizer2::~GradientDescentOptimizer2 ( )

inlineoverrideprotected

Definition at line 139 of file itkGradientDescentOptimizer2.h.

◆ GradientDescentOptimizer2() [2/2]

itk::GradientDescentOptimizer2::GradientDescentOptimizer2 ( const Self & )

private

Member Function Documentation

◆ AdvanceOneStep()

virtual void itk::GradientDescentOptimizer2::AdvanceOneStep ( void )

virtual

Advance one step following the gradient direction.

Reimplemented in elastix::AdaGrad< TElastix >, elastix::PreconditionedStochasticGradientDescent< TElastix >, and itk::StandardGradientDescentOptimizer.

◆ GetClassName()

virtual const char * itk::GradientDescentOptimizer2::GetClassName ( ) const

virtual

Run-time type information (and related methods).

Reimplemented from itk::ScaledSingleValuedNonLinearOptimizer.

Reimplemented in elastix::AdaGrad< TElastix >, itk::AdaptiveStepsizeOptimizer, elastix::AdaptiveStochasticGradientDescent< TElastix >, itk::AdaptiveStochasticGradientDescentOptimizer, elastix::PreconditionedStochasticGradientDescent< TElastix >, itk::PreconditionedASGDOptimizer, elastix::StandardGradientDescent< TElastix >, and itk::StandardGradientDescentOptimizer.

◆ GetCurrentIteration()

virtual unsigned int itk::GradientDescentOptimizer2::GetCurrentIteration ( ) const

virtual

Get the current iteration number.

◆ GetGradient()

virtual const DerivativeType & itk::GradientDescentOptimizer2::GetGradient ( )

virtual

Get current gradient.

◆ GetLearningRate()

virtual const double & itk::GradientDescentOptimizer2::GetLearningRate ( )

virtual

Get the learning rate.

◆ GetNumberOfIterations()

virtual const unsigned long & itk::GradientDescentOptimizer2::GetNumberOfIterations ( )

virtual

Get the number of iterations.

◆ GetSearchDirection()

virtual const DerivativeType & itk::GradientDescentOptimizer2::GetSearchDirection ( )

virtual

Get current search direction

◆ GetStopCondition()

virtual const StopConditionType & itk::GradientDescentOptimizer2::GetStopCondition ( )

virtual

Get Stop condition.

◆ GetValue()

virtual const double & itk::GradientDescentOptimizer2::GetValue ( )

virtual

Get the current value.

◆ MetricErrorResponse()

virtual void itk::GradientDescentOptimizer2::MetricErrorResponse ( ExceptionObject & err )

virtual

Stop optimization and pass on exception.

◆ New()

static Pointer itk::GradientDescentOptimizer2::New ( )

static

Method for creation through the object factory.

◆ operator=()

void itk::GradientDescentOptimizer2::operator= ( const Self & )

private

◆ PrintSelf()

void itk::GradientDescentOptimizer2::PrintSelf	(	std::ostream &	os,
		Indent	indent
	)		const

overrideprotected

◆ ResumeOptimization()

virtual void itk::GradientDescentOptimizer2::ResumeOptimization ( void )

virtual

Resume previously stopped optimization with current parameters

See also: StopOptimization.

Reimplemented in elastix::AdaGrad< TElastix >, elastix::AdaptiveStochasticGradientDescent< TElastix >, and elastix::PreconditionedStochasticGradientDescent< TElastix >.

◆ SetLearningRate()

virtual void itk::GradientDescentOptimizer2::SetLearningRate ( double _arg )

virtual

Set the learning rate.

◆ SetNumberOfIterations()

virtual void itk::GradientDescentOptimizer2::SetNumberOfIterations ( unsigned long _arg )

virtual

Set the number of iterations.

◆ SetUseOpenMP()

virtual void itk::GradientDescentOptimizer2::SetUseOpenMP ( bool _arg )

virtual

Set use OpenMP or not.

◆ StartOptimization()

void itk::GradientDescentOptimizer2::StartOptimization ( void )

override

Start optimization.

◆ StopOptimization()

virtual void itk::GradientDescentOptimizer2::StopOptimization ( void )

virtual

Stop optimization.

See also: ResumeOptimization

Field Documentation

◆ m_CurrentIteration

unsigned long itk::GradientDescentOptimizer2::m_CurrentIteration

protected

Definition at line 151 of file itkGradientDescentOptimizer2.h.

◆ m_Gradient

DerivativeType itk::GradientDescentOptimizer2::m_Gradient

protected

Definition at line 144 of file itkGradientDescentOptimizer2.h.

◆ m_LearningRate

double itk::GradientDescentOptimizer2::m_LearningRate

protected

Definition at line 146 of file itkGradientDescentOptimizer2.h.

◆ m_NumberOfIterations

unsigned long itk::GradientDescentOptimizer2::m_NumberOfIterations

protected

Definition at line 150 of file itkGradientDescentOptimizer2.h.

◆ m_SearchDirection

DerivativeType itk::GradientDescentOptimizer2::m_SearchDirection

protected

Definition at line 145 of file itkGradientDescentOptimizer2.h.

◆ m_Stop

bool itk::GradientDescentOptimizer2::m_Stop

protected

Definition at line 149 of file itkGradientDescentOptimizer2.h.

◆ m_StopCondition

StopConditionType itk::GradientDescentOptimizer2::m_StopCondition

protected

Definition at line 147 of file itkGradientDescentOptimizer2.h.

◆ m_UseOpenMP

bool itk::GradientDescentOptimizer2::m_UseOpenMP

private

Definition at line 158 of file itkGradientDescentOptimizer2.h.

◆ m_Value

double itk::GradientDescentOptimizer2::m_Value

protected

Definition at line 143 of file itkGradientDescentOptimizer2.h.

Detailed Description

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Protected Attributes

Private Member Functions

Private Attributes

Member Typedef Documentation

◆ ConstPointer

◆ CostFunctionType

◆ DerivativeType

◆ MeasureType

◆ ParametersType

◆ Pointer

◆ ScaledCostFunctionPointer

◆ ScaledCostFunctionType

◆ ScalesType

◆ Self

◆ Superclass

Member Enumeration Documentation

◆ StopConditionType

Constructor & Destructor Documentation

◆ GradientDescentOptimizer2() [1/2]

◆ ~GradientDescentOptimizer2()

◆ GradientDescentOptimizer2() [2/2]

Member Function Documentation

◆ AdvanceOneStep()

◆ GetClassName()

◆ GetCurrentIteration()

◆ GetGradient()

◆ GetLearningRate()

◆ GetNumberOfIterations()

◆ GetSearchDirection()

◆ GetStopCondition()

◆ GetValue()

◆ MetricErrorResponse()

◆ New()

◆ operator=()

◆ PrintSelf()

◆ ResumeOptimization()

◆ SetLearningRate()

◆ SetNumberOfIterations()

◆ SetUseOpenMP()

◆ StartOptimization()

◆ StopOptimization()

Field Documentation

◆ m_CurrentIteration

◆ m_Gradient

◆ m_LearningRate

◆ m_NumberOfIterations

◆ m_SearchDirection

◆ m_Stop

◆ m_StopCondition

◆ m_UseOpenMP

◆ m_Value