#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 53 of file itkGradientDescentOptimizer2.h.

Inheritance diagram for itk::GradientDescentOptimizer2:

Data Structures
struct	MultiThreaderParameterType

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)

void	SetNumberOfThreads (ThreadIdType numberOfThreads)

virtual void	SetUseEigen (bool _arg)

virtual void	SetUseMultiThread (bool _arg)

virtual void	SetUseOpenMP (bool _arg)

virtual void	StartOptimization (void)

virtual void	StopOptimization (void)

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

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 ()

virtual void	SetCostFunction (CostFunctionType *costFunction)

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 Types
typedef itk::MultiThreader	ThreaderType

typedef ThreaderType::ThreadInfoStruct	ThreadInfoType

Protected Member Functions
	GradientDescentOptimizer2 ()

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

virtual	~GradientDescentOptimizer2 ()

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

	ScaledSingleValuedNonLinearOptimizer ()

virtual void	SetCurrentPosition (const ParametersType &param)

virtual void	SetScaledCurrentPosition (const ParametersType &parameters)

virtual	~ScaledSingleValuedNonLinearOptimizer ()

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

ThreaderType::Pointer	m_Threader

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 &)

void	ThreadedAdvanceOneStep (ThreadIdType threadId, ParametersType &newPosition)

Static Private Member Functions
static ITK_THREAD_RETURN_TYPE	AdvanceOneStepThreaderCallback (void *arg)

Private Attributes
bool	m_UseEigen

bool	m_UseMultiThread

bool	m_UseOpenMP

Member Typedef Documentation

◆ ConstPointer

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

Definition at line 62 of file itkGradientDescentOptimizer2.h.

◆ CostFunctionType

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

Definition at line 74 of file itkGradientDescentOptimizer2.h.

◆ DerivativeType

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

Definition at line 73 of file itkGradientDescentOptimizer2.h.

◆ MeasureType

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

Typedefs inherited from the superclass.

Definition at line 68 of file itkGradientDescentOptimizer2.h.

◆ ParametersType

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

Definition at line 72 of file itkGradientDescentOptimizer2.h.

◆ Pointer

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

Definition at line 61 of file itkGradientDescentOptimizer2.h.

◆ ScaledCostFunctionPointer

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

Definition at line 77 of file itkGradientDescentOptimizer2.h.

◆ ScaledCostFunctionType

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

Definition at line 76 of file itkGradientDescentOptimizer2.h.

◆ ScalesType

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

Definition at line 75 of file itkGradientDescentOptimizer2.h.

◆ Self

typedef GradientDescentOptimizer2 itk::GradientDescentOptimizer2::Self

Standard class typedefs.

Definition at line 59 of file itkGradientDescentOptimizer2.h.

◆ Superclass

typedef ScaledSingleValuedNonLinearOptimizer itk::GradientDescentOptimizer2::Superclass

Definition at line 60 of file itkGradientDescentOptimizer2.h.

◆ ThreaderType

typedef itk::MultiThreader itk::GradientDescentOptimizer2::ThreaderType

protected

Typedefs for multi-threading.

Definition at line 151 of file itkGradientDescentOptimizer2.h.

◆ ThreadInfoType

typedef ThreaderType::ThreadInfoStruct itk::GradientDescentOptimizer2::ThreadInfoType

protected

Definition at line 152 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 82 of file itkGradientDescentOptimizer2.h.

Constructor & Destructor Documentation

◆ GradientDescentOptimizer2() [1/2]

itk::GradientDescentOptimizer2::GradientDescentOptimizer2 ( )

protected

◆ ~GradientDescentOptimizer2()

virtual itk::GradientDescentOptimizer2::~GradientDescentOptimizer2 ( )

inlineprotectedvirtual

Definition at line 147 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 itk::StandardGradientDescentOptimizer.

◆ AdvanceOneStepThreaderCallback()

static ITK_THREAD_RETURN_TYPE itk::GradientDescentOptimizer2::AdvanceOneStepThreaderCallback ( void * arg )

staticprivate

The callback function.

◆ GetClassName()

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

virtual

Run-time type information (and related methods).

Reimplemented from itk::ScaledSingleValuedNonLinearOptimizer.

Reimplemented in elastix::AdaptiveStochasticGradientDescent< TElastix >, itk::AdaptiveStochasticGradientDescentOptimizer, 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

protected

◆ ResumeOptimization()

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

virtual

Resume previously stopped optimization with current parameters

See also: StopOptimization.

Reimplemented in elastix::AdaptiveStochasticGradientDescent< 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.

◆ SetNumberOfThreads()

void itk::GradientDescentOptimizer2::SetNumberOfThreads ( ThreadIdType numberOfThreads )

inline

Set the number of threads.

Definition at line 133 of file itkGradientDescentOptimizer2.h.

◆ SetUseEigen()

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

virtual

◆ SetUseMultiThread()

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

virtual

◆ SetUseOpenMP()

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

virtual

◆ StartOptimization()

virtual void itk::GradientDescentOptimizer2::StartOptimization ( void )

virtual

Start optimization.

Reimplemented in elastix::AdaptiveStochasticGradientDescent< TElastix >, elastix::StandardGradientDescent< TElastix >, and itk::StandardGradientDescentOptimizer.

◆ StopOptimization()

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

virtual

Stop optimization.

See also: ResumeOptimization

◆ ThreadedAdvanceOneStep()

void itk::GradientDescentOptimizer2::ThreadedAdvanceOneStep	(	ThreadIdType	threadId,
		ParametersType &	newPosition
	)

inlineprivate

The threaded implementation of AdvanceOneStep().

Field Documentation

◆ m_CurrentIteration

unsigned long itk::GradientDescentOptimizer2::m_CurrentIteration

protected

Definition at line 165 of file itkGradientDescentOptimizer2.h.

◆ m_Gradient

DerivativeType itk::GradientDescentOptimizer2::m_Gradient

protected

Definition at line 156 of file itkGradientDescentOptimizer2.h.

◆ m_LearningRate

double itk::GradientDescentOptimizer2::m_LearningRate

protected

Definition at line 158 of file itkGradientDescentOptimizer2.h.

◆ m_NumberOfIterations

unsigned long itk::GradientDescentOptimizer2::m_NumberOfIterations

protected

Definition at line 164 of file itkGradientDescentOptimizer2.h.

◆ m_SearchDirection

DerivativeType itk::GradientDescentOptimizer2::m_SearchDirection

protected

Definition at line 157 of file itkGradientDescentOptimizer2.h.

◆ m_Stop

bool itk::GradientDescentOptimizer2::m_Stop

protected

Definition at line 163 of file itkGradientDescentOptimizer2.h.

◆ m_StopCondition

StopConditionType itk::GradientDescentOptimizer2::m_StopCondition

protected

Definition at line 159 of file itkGradientDescentOptimizer2.h.

◆ m_Threader

ThreaderType::Pointer itk::GradientDescentOptimizer2::m_Threader

protected

Definition at line 161 of file itkGradientDescentOptimizer2.h.

◆ m_UseEigen

bool itk::GradientDescentOptimizer2::m_UseEigen

private

Definition at line 181 of file itkGradientDescentOptimizer2.h.

◆ m_UseMultiThread

bool itk::GradientDescentOptimizer2::m_UseMultiThread

private

Definition at line 173 of file itkGradientDescentOptimizer2.h.

◆ m_UseOpenMP

bool itk::GradientDescentOptimizer2::m_UseOpenMP

private

Definition at line 180 of file itkGradientDescentOptimizer2.h.

◆ m_Value

double itk::GradientDescentOptimizer2::m_Value

protected

Definition at line 155 of file itkGradientDescentOptimizer2.h.

Detailed Description

Data Structures

Public Types

Public Member Functions

Static Public Member Functions

Protected Types

Protected Member Functions

Protected Attributes

Private Member Functions

Static Private Member Functions

Private Attributes

Member Typedef Documentation

◆ ConstPointer

◆ CostFunctionType

◆ DerivativeType

◆ MeasureType

◆ ParametersType

◆ Pointer

◆ ScaledCostFunctionPointer

◆ ScaledCostFunctionType

◆ ScalesType

◆ Self

◆ Superclass

◆ ThreaderType

◆ ThreadInfoType

Member Enumeration Documentation

◆ StopConditionType

Constructor & Destructor Documentation

◆ GradientDescentOptimizer2() [1/2]

◆ ~GradientDescentOptimizer2()

◆ GradientDescentOptimizer2() [2/2]

Member Function Documentation

◆ AdvanceOneStep()

◆ AdvanceOneStepThreaderCallback()

◆ GetClassName()

◆ GetCurrentIteration()

◆ GetGradient()

◆ GetLearningRate()

◆ GetNumberOfIterations()

◆ GetSearchDirection()

◆ GetStopCondition()

◆ GetValue()

◆ MetricErrorResponse()

◆ New()

◆ operator=()

◆ PrintSelf()

◆ ResumeOptimization()

◆ SetLearningRate()

◆ SetNumberOfIterations()

◆ SetNumberOfThreads()

◆ SetUseEigen()

◆ SetUseMultiThread()

◆ SetUseOpenMP()

◆ StartOptimization()

◆ StopOptimization()

◆ ThreadedAdvanceOneStep()

Field Documentation

◆ m_CurrentIteration

◆ m_Gradient

◆ m_LearningRate

◆ m_NumberOfIterations

◆ m_SearchDirection

◆ m_Stop

◆ m_StopCondition

◆ m_Threader

◆ m_UseEigen

◆ m_UseMultiThread

◆ m_UseOpenMP

◆ m_Value