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

#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 Member Functions
virtual const char *	GetNameOfClass () const
bool	GetUseCostFunctionGradient () const
virtual void	SetCostFunction (MultipleValuedCostFunction *costFunction)=0
void	SetUseCostFunctionGradient (bool)
void	UseCostFunctionGradientOff ()
void	UseCostFunctionGradientOn ()
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)
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 &)

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 ( ) [protected, 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().

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 `[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::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]