Implement a gradient descent optimizer. More...

#include <itkRegularStepGradientDescentBaseOptimizer.h>

Inheritance diagram for itk::RegularStepGradientDescentBaseOptimizer:

Collaboration diagram for itk::RegularStepGradientDescentBaseOptimizer:

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 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 ()
Static Public Member Functions
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 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
Private Member Functions
void	operator= (const Self &)
	RegularStepGradientDescentBaseOptimizer (const Self &)

Detailed Description

Implement a gradient descent optimizer.

Definition at line 32 of file itkRegularStepGradientDescentBaseOptimizer.h.

Member Typedef Documentation

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

Reimplemented from itk::SingleValuedNonLinearOptimizer.

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

Definition at line 40 of file itkRegularStepGradientDescentBaseOptimizer.h.

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

Reimplemented from itk::SingleValuedNonLinearOptimizer.

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

Definition at line 39 of file itkRegularStepGradientDescentBaseOptimizer.h.

typedef RegularStepGradientDescentBaseOptimizer itk::RegularStepGradientDescentBaseOptimizer::Self

Standard "Self" typedef.

Reimplemented from itk::SingleValuedNonLinearOptimizer.

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

Definition at line 37 of file itkRegularStepGradientDescentBaseOptimizer.h.

typedef SingleValuedNonLinearOptimizer itk::RegularStepGradientDescentBaseOptimizer::Superclass

Reimplemented from itk::SingleValuedNonLinearOptimizer.

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

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 ( ) [inline, protected, virtual]

Definition at line 107 of file itkRegularStepGradientDescentBaseOptimizer.h.

itk::RegularStepGradientDescentBaseOptimizer::RegularStepGradientDescentBaseOptimizer ( const Self & ) [private]

Member Function Documentation

virtual void itk::RegularStepGradientDescentBaseOptimizer::AdvanceOneStep ( void ) [protected, virtual]

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::SingleValuedNonLinearOptimizer.

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

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

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.

Reimplemented from itk::SingleValuedNonLinearOptimizer.

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

void itk::RegularStepGradientDescentBaseOptimizer::operator= ( const Self & ) [private]

Types inherited from the superclass

Reimplemented from itk::SingleValuedNonLinearOptimizer.

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

void itk::RegularStepGradientDescentBaseOptimizer::PrintSelf	(	std::ostream &	os,
		Indent	indent
	)		const `[protected, virtual]`

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::SingleValuedNonLinearOptimizer.

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 &
	)		`[inline, protected, virtual]`

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