#include <itkGradientDescentOptimizer.h>

Inheritance diagram for itk::GradientDescentOptimizer:

Collaboration diagram for itk::GradientDescentOptimizer:

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 of the df / dp but setting a scaling vector using method SetScale().

See Also: RegularStepGradientDescentOptimizer

Definition at line 50 of file itkGradientDescentOptimizer.h.

Public Types
typedef SmartPointer< const Self >	ConstPointer

typedef SmartPointer< Self >	Pointer

typedef GradientDescentOptimizer	Self

enum	StopConditionType { MaximumNumberOfIterations, MetricError }

typedef SingleValuedNonLinearOptimizer	Superclass

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

typedef CostFunctionType::Pointer	CostFunctionPointer

typedef SingleValuedCostFunction	CostFunctionType

typedef CostFunctionType::DerivativeType	DerivativeType

typedef CostFunctionType::MeasureType	MeasureType

typedef Superclass::ParametersType	ParametersType

typedef SmartPointer< Self >	Pointer

typedef SingleValuedNonLinearOptimizer	Self

typedef NonLinearOptimizer	Superclass

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

typedef Superclass::ParametersType	ParametersType

typedef SmartPointer< Self >	Pointer

typedef Superclass::ScalesType	ScalesType

typedef NonLinearOptimizer	Self

typedef Optimizer	Superclass

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

typedef OptimizerParameters < double >	ParametersType

typedef SmartPointer< Self >	Pointer

typedef Array< double >	ScalesType

typedef Optimizer	Self

typedef Object	Superclass

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

typedef SmartPointer< Self >	Pointer

typedef Object	Self

typedef LightObject	Superclass

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

typedef SmartPointer< Self >	Pointer

typedef LightObject	Self

Public Member Functions
virtual void	AdvanceOneStep (void)

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

virtual SizeValueType	GetCurrentIteration () const

virtual const DerivativeType &	GetGradient ()

virtual const double &	GetLearningRate ()

virtual const char *	GetNameOfClass () const

virtual const SizeValueType &	GetNumberOfIterations ()

virtual const double &	GetValue ()

void	ResumeOptimization (void)

virtual void	SetLearningRate (double _arg)

virtual void	SetNumberOfIterations (SizeValueType _arg)

void	StartOptimization (void)

void	StopOptimization (void)


virtual const bool &	GetMaximize ()

virtual void	SetMaximize (bool _arg)

virtual void	MaximizeOn ()

virtual void	MaximizeOff ()

bool	GetMinimize () const

void	SetMinimize (bool v)

void	MinimizeOn ()

void	MinimizeOff ()


virtual const StopConditionType &	GetStopCondition ()

const std::string	GetStopConditionDescription () const

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

virtual const CostFunctionType *	GetCostFunction () const

virtual CostFunctionType *	GetModifiableCostFunction ()

MeasureType	GetValue (const ParametersType &parameters) const

virtual void	SetCostFunction (CostFunctionType *costFunction)

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 flag)

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

virtual	~GradientDescentOptimizer ()

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

	SingleValuedNonLinearOptimizer ()

virtual	~SingleValuedNonLinearOptimizer ()

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

virtual	~NonLinearOptimizer ()

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

virtual void	SetCurrentPosition (const ParametersType &param)

virtual	~Optimizer ()

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

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

virtual void	SetTimeStamp (const TimeStamp &time)

virtual	~Object ()

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
DerivativeType	m_Gradient

double	m_LearningRate

bool	m_Maximize

Protected Attributes inherited from itk::SingleValuedNonLinearOptimizer
CostFunctionPointer	m_CostFunction

Private Member Functions
	GradientDescentOptimizer (const Self &)

void	operator= (const Self &)

Private Attributes
SizeValueType	m_CurrentIteration

SizeValueType	m_NumberOfIterations

bool	m_Stop

StopConditionType	m_StopCondition

std::ostringstream	m_StopConditionDescription

double	m_Value

Additional Inherited Members
Protected Types inherited from itk::LightObject
typedef int	InternalReferenceCountType

Member Typedef Documentation

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

Definition at line 58 of file itkGradientDescentOptimizer.h.

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

Definition at line 57 of file itkGradientDescentOptimizer.h.

typedef GradientDescentOptimizer itk::GradientDescentOptimizer::Self

Standard class typedefs.

Definition at line 55 of file itkGradientDescentOptimizer.h.

typedef SingleValuedNonLinearOptimizer itk::GradientDescentOptimizer::Superclass

Definition at line 56 of file itkGradientDescentOptimizer.h.

Member Enumeration Documentation

enum itk::GradientDescentOptimizer::StopConditionType

Codes of stopping conditions

Enumerator
MaximumNumberOfIterations
MetricError

Definition at line 67 of file itkGradientDescentOptimizer.h.

Constructor & Destructor Documentation

itk::GradientDescentOptimizer::GradientDescentOptimizer ( )

protected

virtual itk::GradientDescentOptimizer::~GradientDescentOptimizer ( )

inlineprotectedvirtual

Definition at line 128 of file itkGradientDescentOptimizer.h.

itk::GradientDescentOptimizer::GradientDescentOptimizer ( const Self & )

private

Member Function Documentation

virtual void itk::GradientDescentOptimizer::AdvanceOneStep ( void )

virtual

Advance one step following the gradient direction.

Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer.

virtual::itk::LightObject::Pointer itk::GradientDescentOptimizer::CreateAnother ( void ) 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.

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

virtual

Get the current iteration number.

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

virtual

Get Gradient condition.

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

virtual

Get the learning rate.

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

virtual

Methods to configure the cost function.

bool itk::GradientDescentOptimizer::GetMinimize ( ) const

inline

Methods to configure the cost function.

Definition at line 76 of file itkGradientDescentOptimizer.h.

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

virtual

Run-time type information (and related methods).

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer.

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

virtual

Get the number of iterations.

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

virtual

Get Stop condition.

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

virtual

Get Stop condition.

Reimplemented from itk::Optimizer.

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

virtual

Get the current value.

virtual void itk::GradientDescentOptimizer::MaximizeOff ( )

virtual

Methods to configure the cost function.

virtual void itk::GradientDescentOptimizer::MaximizeOn ( )

virtual

Methods to configure the cost function.

void itk::GradientDescentOptimizer::MinimizeOff ( )

inline

Methods to configure the cost function.

Definition at line 82 of file itkGradientDescentOptimizer.h.

void itk::GradientDescentOptimizer::MinimizeOn ( )

inline

Methods to configure the cost function.

Definition at line 80 of file itkGradientDescentOptimizer.h.

static Pointer itk::GradientDescentOptimizer::New ( )

static

Method for creation through the object factory.

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

private

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

protectedvirtual

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.

void itk::GradientDescentOptimizer::ResumeOptimization ( void )

Resume previously stopped optimization with current parameters