#include <itkRegularStepGradientDescentBaseOptimizer.h>

Inheritance diagram for itk::RegularStepGradientDescentBaseOptimizer:

Collaboration diagram for itk::RegularStepGradientDescentBaseOptimizer:

Detailed Description

Implement a gradient descent optimizer.

Definition at line 32 of file itkRegularStepGradientDescentBaseOptimizer.h.

Public Types
typedef SmartPointer< const Self >	ConstPointer

typedef SmartPointer< Self >	Pointer

typedef RegularStepGradientDescentBaseOptimizer	Self

enum	StopConditionType { GradientMagnitudeTolerance = 1, StepTooSmall = 2, ImageNotAvailable = 3, CostFunctionError = 4, MaximumNumberOfIterations = 5, Unknown = 6 }

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

virtual const char *	GetNameOfClass () const

virtual const std::string	GetStopConditionDescription () const

void	ResumeOptimization (void)

void	StartOptimization (void)

void	StopOptimization (void)


virtual void	SetMaximize (bool _arg)

virtual const bool &	GetMaximize ()

virtual void	MaximizeOn ()

virtual void	MaximizeOff ()

bool	GetMinimize () const

void	SetMinimize (bool v)

void	MinimizeOn (void)

void	MinimizeOff (void)


virtual void	SetMaximumStepLength (double _arg)

virtual void	SetMinimumStepLength (double _arg)

virtual void	SetRelaxationFactor (double _arg)

virtual void	SetNumberOfIterations (SizeValueType _arg)

virtual void	SetGradientMagnitudeTolerance (double _arg)

virtual const double &	GetCurrentStepLength ()

virtual const double &	GetMaximumStepLength ()

virtual const double &	GetMinimumStepLength ()

virtual const double &	GetRelaxationFactor ()

virtual const SizeValueType &	GetNumberOfIterations ()

virtual const double &	GetGradientMagnitudeTolerance ()

virtual unsigned int	GetCurrentIteration () const

virtual const StopConditionType &	GetStopCondition ()

virtual const MeasureType &	GetValue ()

virtual const DerivativeType &	GetGradient ()

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

virtual const CostFunctionType *	GetCostFunction ()

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
virtual void	AdvanceOneStep (void)

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

	RegularStepGradientDescentBaseOptimizer ()

virtual void	StepAlongGradient (double, const DerivativeType &)

virtual	~RegularStepGradientDescentBaseOptimizer ()

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
SizeValueType	m_CurrentIteration

double	m_CurrentStepLength

DerivativeType	m_Gradient

double	m_GradientMagnitudeTolerance

bool	m_Maximize

double	m_MaximumStepLength

double	m_MinimumStepLength

SizeValueType	m_NumberOfIterations

DerivativeType	m_PreviousGradient

double	m_RelaxationFactor

bool	m_Stop

StopConditionType	m_StopCondition

std::ostringstream	m_StopConditionDescription

MeasureType	m_Value

Protected Attributes inherited from itk::SingleValuedNonLinearOptimizer
CostFunctionPointer	m_CostFunction

Private Member Functions
void	operator= (const Self &)

	RegularStepGradientDescentBaseOptimizer (const Self &)

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

Member Typedef Documentation

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

Definition at line 40 of file itkRegularStepGradientDescentBaseOptimizer.h.

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

Definition at line 39 of file itkRegularStepGradientDescentBaseOptimizer.h.

typedef RegularStepGradientDescentBaseOptimizer itk::RegularStepGradientDescentBaseOptimizer::Self

Standard "Self" typedef.

Definition at line 37 of file itkRegularStepGradientDescentBaseOptimizer.h.

typedef SingleValuedNonLinearOptimizer itk::RegularStepGradientDescentBaseOptimizer::Superclass

Definition at line 38 of file itkRegularStepGradientDescentBaseOptimizer.h.

Member Enumeration Documentation

enum itk::RegularStepGradientDescentBaseOptimizer::StopConditionType

Codes of stopping conditions.

Enumerator:

GradientMagnitudeTolerance
StepTooSmall
ImageNotAvailable
CostFunctionError
MaximumNumberOfIterations
Unknown

Definition at line 50 of file itkRegularStepGradientDescentBaseOptimizer.h.

Constructor & Destructor Documentation

itk::RegularStepGradientDescentBaseOptimizer::RegularStepGradientDescentBaseOptimizer ( )

protected

virtual itk::RegularStepGradientDescentBaseOptimizer::~RegularStepGradientDescentBaseOptimizer ( )

inlineprotectedvirtual

Definition at line 107 of file itkRegularStepGradientDescentBaseOptimizer.h.

itk::RegularStepGradientDescentBaseOptimizer::RegularStepGradientDescentBaseOptimizer ( const Self & )

private

Member Function Documentation

virtual void itk::RegularStepGradientDescentBaseOptimizer::AdvanceOneStep ( void )

protectedvirtual

Advance one step following the gradient direction This method verifies if a change in direction is required and if a reduction in steplength is required.

virtual::itk::LightObject::Pointer itk::RegularStepGradientDescentBaseOptimizer::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::NonLinearOptimizer.

Reimplemented in itk::VersorTransformOptimizer, itk::VersorRigid3DTransformOptimizer, and itk::RegularStepGradientDescentOptimizer.

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

virtual

Set/Get parameters to control the optimization process.

virtual const double& itk::RegularStepGradientDescentBaseOptimizer::GetCurrentStepLength ( )

virtual

Set/Get parameters to control the optimization process.

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

virtual

Set/Get parameters to control the optimization process.

virtual const double& itk::RegularStepGradientDescentBaseOptimizer::GetGradientMagnitudeTolerance ( )

virtual

Set/Get parameters to control the optimization process.

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

virtual

Specify whether to minimize or maximize the cost function.

virtual const double& itk::RegularStepGradientDescentBaseOptimizer::GetMaximumStepLength ( )

virtual

Set/Get parameters to control the optimization process.

bool itk::RegularStepGradientDescentBaseOptimizer::GetMinimize ( ) const

inline

Specify whether to minimize or maximize the cost function.

Definition at line 63 of file itkRegularStepGradientDescentBaseOptimizer.h.

virtual const double& itk::RegularStepGradientDescentBaseOptimizer::GetMinimumStepLength ( )

virtual

Set/Get parameters to control the optimization process.

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

virtual

Run-time type information (and related methods).

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Reimplemented in itk::VersorTransformOptimizer, itk::VersorRigid3DTransformOptimizer, and itk::RegularStepGradientDescentOptimizer.

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

virtual

Set/Get parameters to control the optimization process.

virtual const double& itk::RegularStepGradientDescentBaseOptimizer::GetRelaxationFactor ( )

virtual

Set/Get parameters to control the optimization process.

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

virtual

Set/Get parameters to control the optimization process.

virtual const std::string itk::RegularStepGradientDescentBaseOptimizer::GetStopConditionDescription ( ) const

virtual

Get the reason for termination

Reimplemented from itk::Optimizer.

virtual const MeasureType& itk::RegularStepGradientDescentBaseOptimizer::GetValue ( )

virtual

Set/Get parameters to control the optimization process.

virtual void itk::RegularStepGradientDescentBaseOptimizer::MaximizeOff ( )

virtual

Specify whether to minimize or maximize the cost function.

virtual void itk::RegularStepGradientDescentBaseOptimizer::MaximizeOn ( )

virtual

Specify whether to minimize or maximize the cost function.

void itk::RegularStepGradientDescentBaseOptimizer::MinimizeOff ( void )

inline

Specify whether to minimize or maximize the cost function.

Definition at line 69 of file itkRegularStepGradientDescentBaseOptimizer.h.

void itk::RegularStepGradientDescentBaseOptimizer::MinimizeOn ( void )

inline

Specify whether to minimize or maximize the cost function.

Definition at line 67 of file itkRegularStepGradientDescentBaseOptimizer.h.

static Pointer itk::RegularStepGradientDescentBaseOptimizer::New ( )

static

Method for creation through the object factory.

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

private

void itk::RegularStepGradientDescentBaseOptimizer::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::Optimizer.

void itk::RegularStepGradientDescentBaseOptimizer::ResumeOptimization ( void )

Resume previously stopped optimization with current parameters.

See Also: StopOptimization

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetGradientMagnitudeTolerance ( double _arg )

virtual

Set/Get parameters to control the optimization process.

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

virtual

Specify whether to minimize or maximize the cost function.

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetMaximumStepLength ( double _arg )

virtual

Set/Get parameters to control the optimization process.

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

inline

Specify whether to minimize or maximize the cost function.

Definition at line 65 of file itkRegularStepGradientDescentBaseOptimizer.h.

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetMinimumStepLength ( double _arg )

virtual

Set/Get parameters to control the optimization process.

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

virtual

Set/Get parameters to control the optimization process.

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetRelaxationFactor ( double _arg )

virtual

Set/Get parameters to control the optimization process.

void itk::RegularStepGradientDescentBaseOptimizer::StartOptimization ( void )

virtual

Start optimization.

Reimplemented from itk::Optimizer.

virtual void itk::RegularStepGradientDescentBaseOptimizer::StepAlongGradient	(	double	,
		const DerivativeType &
	)

inlineprotectedvirtual

Advance one step along the corrected gradient taking into account the steplength represented by factor. This method is invoked by AdvanceOneStep. It is expected to be overrided by optimization methods in non-vector spaces