#include <itkMultipleValuedNonLinearVnlOptimizer.h>

Inheritance diagram for itk::MultipleValuedNonLinearVnlOptimizer:

Collaboration diagram for itk::MultipleValuedNonLinearVnlOptimizer:

Public Types
typedef SmartPointer< const Self >	ConstPointer
typedef Superclass::ParametersType	ParametersType
typedef SmartPointer< Self >	Pointer
typedef MultipleValuedNonLinearVnlOptimizer	Self
typedef MultipleValuedNonLinearOptimizer	Superclass
Public Types inherited from itk::MultipleValuedNonLinearOptimizer
typedef CostFunctionType::Pointer	CostFunctionPointer
typedef MultipleValuedCostFunction	CostFunctionType
typedef Array2D< double >	DerivativeType
typedef Array< double >	MeasureType
Public Types inherited from itk::NonLinearOptimizer
typedef Superclass::ScalesType	ScalesType
Public Types inherited from itk::Optimizer
Public Types inherited from itk::Object
Public Types inherited from itk::LightObject

Public Member Functions
virtual const char *	GetNameOfClass () const
bool	GetUseCostFunctionGradient () const
virtual void	SetCostFunction (MultipleValuedCostFunction *costFunction)=0
void	SetUseCostFunctionGradient (bool)
void	UseCostFunctionGradientOff ()
void	UseCostFunctionGradientOn ()
Public Member Functions inherited from itk::MultipleValuedNonLinearOptimizer
virtual ::itk::LightObject::Pointer	CreateAnother (void) const
virtual void	SetCostFunction (CostFunctionType *costFunction)

Protected Types
typedef MultipleValuedVnlCostFunctionAdaptor	CostFunctionAdaptorType

Protected Member Functions
const CostFunctionAdaptorType *	GetCostFunctionAdaptor (void) const
CostFunctionAdaptorType *	GetCostFunctionAdaptor (void)
CostFunctionAdaptorType *	GetNonConstCostFunctionAdaptor (void) const
void	PrintSelf (std::ostream &os, Indent indent) const
void	SetCostFunctionAdaptor (CostFunctionAdaptorType *adaptor)
Protected Member Functions inherited from itk::MultipleValuedNonLinearOptimizer
	MultipleValuedNonLinearOptimizer ()
virtual	~MultipleValuedNonLinearOptimizer ()
	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 ()

Private Member Functions
void	IterationReport (const EventObject &event)

Private Attributes
ParametersType	m_CachedCurrentPosition
DerivativeType	m_CachedDerivative
MeasureType	m_CachedValue
CommandType::Pointer	m_Command
CostFunctionAdaptorType *	m_CostFunctionAdaptor
bool	m_UseGradient
virtual const MeasureType &	GetCachedValue ()
virtual const DerivativeType &	GetCachedDerivative ()
virtual const ParametersType &	GetCachedCurrentPosition ()
	MultipleValuedNonLinearVnlOptimizer ()
virtual	~MultipleValuedNonLinearVnlOptimizer ()
typedef ReceptorMemberCommand < Self >	CommandType
	MultipleValuedNonLinearVnlOptimizer (const Self &)
void	operator= (const Self &)

Additional Inherited Members
Static Public Member Functions inherited from itk::MultipleValuedNonLinearOptimizer
static Pointer	New ()
Protected Attributes inherited from itk::MultipleValuedNonLinearOptimizer
CostFunctionPointer	m_CostFunction

Detailed Description

This class is a base for the Optimization methods that optimize a multi-valued function.

It is an Adaptor class for optimizers provided by the vnl library

Definition at line 36 of file itkMultipleValuedNonLinearVnlOptimizer.h.

Member Typedef Documentation

typedef ReceptorMemberCommand< Self > itk::MultipleValuedNonLinearVnlOptimizer::CommandType

protected

Command observer that will interact with the ITKVNL cost-function adaptor in order to generate iteration events. This will allow to overcome the limitation of VNL optimizers not offering callbacks for every iteration

Definition at line 111 of file itkMultipleValuedNonLinearVnlOptimizer.h.

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

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

Reimplemented in itk::LevenbergMarquardtOptimizer.

Definition at line 44 of file itkMultipleValuedNonLinearVnlOptimizer.h.

typedef MultipleValuedVnlCostFunctionAdaptor itk::MultipleValuedNonLinearVnlOptimizer::CostFunctionAdaptorType

protected

Reimplemented in itk::LevenbergMarquardtOptimizer.

Definition at line 95 of file itkMultipleValuedNonLinearVnlOptimizer.h.

typedef Superclass::ParametersType itk::MultipleValuedNonLinearVnlOptimizer::ParametersType

ParametersType typedef. It defines a position in the optimization search space.

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

Definition at line 48 of file itkMultipleValuedNonLinearVnlOptimizer.h.

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

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

Reimplemented in itk::LevenbergMarquardtOptimizer.

Definition at line 43 of file itkMultipleValuedNonLinearVnlOptimizer.h.

typedef MultipleValuedNonLinearVnlOptimizer itk::MultipleValuedNonLinearVnlOptimizer::Self

Standard class typedefs.

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

Reimplemented in itk::LevenbergMarquardtOptimizer.

Definition at line 41 of file itkMultipleValuedNonLinearVnlOptimizer.h.

typedef MultipleValuedNonLinearOptimizer itk::MultipleValuedNonLinearVnlOptimizer::Superclass

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

Reimplemented in itk::LevenbergMarquardtOptimizer.

Definition at line 42 of file itkMultipleValuedNonLinearVnlOptimizer.h.

Constructor & Destructor Documentation

itk::MultipleValuedNonLinearVnlOptimizer::MultipleValuedNonLinearVnlOptimizer ( )

protected

Return Cached Values. These method have the advantage of not triggering a recomputation of the metric value, but it has the disadvantage of returning a value that may not be the one corresponding to the current parameters. For GUI update purposes, this method is a good option, for mathematical validation you should rather call GetValue().

virtual itk::MultipleValuedNonLinearVnlOptimizer::~MultipleValuedNonLinearVnlOptimizer ( )

protectedvirtual

Return Cached Values. These method have the advantage of not triggering a recomputation of the metric value, but it has the disadvantage of returning a value that may not be the one corresponding to the current parameters. For GUI update purposes, this method is a good option, for mathematical validation you should rather call GetValue().

itk::MultipleValuedNonLinearVnlOptimizer::MultipleValuedNonLinearVnlOptimizer ( const Self & )

private

Command observer that will interact with the ITKVNL cost-function adaptor in order to generate iteration events. This will allow to overcome the limitation of VNL optimizers not offering callbacks for every iteration

Member Function Documentation

virtual const ParametersType& itk::MultipleValuedNonLinearVnlOptimizer::GetCachedCurrentPosition ( )

virtual

Return Cached Values. These method have the advantage of not triggering a recomputation of the metric value, but it has the disadvantage of returning a value that may not be the one corresponding to the current parameters. For GUI update purposes, this method is a good option, for mathematical validation you should rather call GetValue().

virtual const DerivativeType& itk::MultipleValuedNonLinearVnlOptimizer::GetCachedDerivative ( )

virtual

Return Cached Values. These method have the advantage of not triggering a recomputation of the metric value, but it has the disadvantage of returning a value that may not be the one corresponding to the current parameters. For GUI update purposes, this method is a good option, for mathematical validation you should rather call GetValue().

virtual const MeasureType& itk::MultipleValuedNonLinearVnlOptimizer::GetCachedValue ( )

virtual

Return Cached Values. These method have the advantage of not triggering a recomputation of the metric value, but it has the disadvantage of returning a value that may not be the one corresponding to the current parameters. For GUI update purposes, this method is a good option, for mathematical validation you should rather call GetValue().

const CostFunctionAdaptorType* itk::MultipleValuedNonLinearVnlOptimizer::GetCostFunctionAdaptor ( void ) const

protected

CostFunctionAdaptorType* itk::MultipleValuedNonLinearVnlOptimizer::GetCostFunctionAdaptor ( void )

protected

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

virtual

Run-time type information (and related methods).

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

Reimplemented in itk::LevenbergMarquardtOptimizer.

CostFunctionAdaptorType* itk::MultipleValuedNonLinearVnlOptimizer::GetNonConstCostFunctionAdaptor ( void ) const

protected

The purpose of this method is to get around the lack of const correctness in vnl cost_functions and optimizers

bool itk::MultipleValuedNonLinearVnlOptimizer::GetUseCostFunctionGradient ( ) const

void itk::MultipleValuedNonLinearVnlOptimizer::IterationReport ( const EventObject & event )

private

Callback function for the Command Observer

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

private

Command observer that will interact with the ITKVNL cost-function adaptor in order to generate iteration events. This will allow to overcome the limitation of VNL optimizers not offering callbacks for every iteration

Reimplemented from itk::MultipleValuedNonLinearOptimizer.

Reimplemented in itk::LevenbergMarquardtOptimizer.

void itk::MultipleValuedNonLinearVnlOptimizer::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::MultipleValuedNonLinearOptimizer.

virtual void itk::MultipleValuedNonLinearVnlOptimizer::SetCostFunction ( MultipleValuedCostFunction * costFunction )

pure virtual

Set the cost Function. This method has to be overloaded by derived classes because the CostFunctionAdaptor requires to know the number of parameters at construction time. This number of parameters is obtained at run-time from the itkCostFunction. As a consequence each derived optimizer should construct its own CostFunctionAdaptor when overloading this method

Implemented in itk::LevenbergMarquardtOptimizer.

void itk::MultipleValuedNonLinearVnlOptimizer::SetCostFunctionAdaptor ( CostFunctionAdaptorType * adaptor )

protected

void itk::MultipleValuedNonLinearVnlOptimizer::SetUseCostFunctionGradient ( bool )

Define if the Cost function should provide a customized Gradient computation or the gradient can be computed internally using a default approach

void itk::MultipleValuedNonLinearVnlOptimizer::UseCostFunctionGradientOff ( )

inline

Definition at line 72 of file itkMultipleValuedNonLinearVnlOptimizer.h.

void itk::MultipleValuedNonLinearVnlOptimizer::UseCostFunctionGradientOn ( )

inline

Definition at line 67 of file itkMultipleValuedNonLinearVnlOptimizer.h.