#include <itkSingleValuedNonLinearVnlOptimizer.h>

Inheritance diagram for itk::SingleValuedNonLinearVnlOptimizer:

Collaboration diagram for itk::SingleValuedNonLinearVnlOptimizer:

Detailed Description

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

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

Definition at line 37 of file itkSingleValuedNonLinearVnlOptimizer.h.

Public Types
using	CommandType = ReceptorMemberCommand< Self >

using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = SingleValuedNonLinearVnlOptimizer

using	Superclass = SingleValuedNonLinearOptimizer

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

using	CostFunctionPointer = CostFunctionType::Pointer

using	CostFunctionType = SingleValuedCostFunction

using	DerivativeType = CostFunctionType::DerivativeType

using	MeasureType = CostFunctionType::MeasureType

using	ParametersType = Superclass::ParametersType

using	Pointer = SmartPointer< Self >

using	Self = SingleValuedNonLinearOptimizer

using	Superclass = NonLinearOptimizer

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

using	ParametersType = Superclass::ParametersType

using	Pointer = SmartPointer< Self >

using	ScalesType = Superclass::ScalesType

using	Self = NonLinearOptimizer

using	Superclass = Optimizer

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

using	ParametersType = OptimizerParameters< double >

using	Pointer = SmartPointer< Self >

using	ScalesType = Array< double >

using	Self = Optimizer

using	Superclass = Object

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

using	Pointer = SmartPointer< Self >

using	Self = Object

using	Superclass = LightObject

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

using	Pointer = SmartPointer< Self >

using	Self = LightObject

Public Member Functions
virtual const char *	GetNameOfClass () const

void	SetCostFunction (SingleValuedCostFunction *costFunction) override=0


virtual const bool &	GetMaximize () const

virtual void	SetMaximize (bool _arg)

virtual void	MaximizeOn ()

virtual void	MaximizeOff ()

bool	GetMinimize () const

void	SetMinimize (bool v)

void	MinimizeOn ()

void	MinimizeOff ()


virtual const MeasureType &	GetCachedValue () const

virtual const DerivativeType &	GetCachedDerivative () const

virtual const ParametersType &	GetCachedCurrentPosition () const

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

virtual const CostFunctionType *	GetCostFunction () const

virtual CostFunctionType *	GetModifiableCostFunction ()

MeasureType	GetValue (const ParametersType &parameters) const

virtual void	SetCostFunction (CostFunctionType *costFunction)

Public Member Functions inherited from itk::Optimizer
virtual const ParametersType &	GetCurrentPosition () const

virtual const ParametersType &	GetInitialPosition () const

virtual const std::string	GetStopConditionDescription () const

virtual void	SetInitialPosition (const ParametersType &param)

void	SetScales (const ScalesType &scales)

virtual void	StartOptimization ()

virtual const ScalesType &	GetScales () const

virtual const ScalesType &	GetInverseScales () const

Public Member Functions inherited from itk::Object
unsigned long	AddObserver (const EventObject &event, Command *)

unsigned long	AddObserver (const EventObject &event, Command *) const

virtual void	DebugOff () const

virtual void	DebugOn () const

Command *	GetCommand (unsigned long tag)

bool	GetDebug () const

MetaDataDictionary &	GetMetaDataDictionary ()

const MetaDataDictionary &	GetMetaDataDictionary () const

virtual ModifiedTimeType	GetMTime () const

virtual const TimeStamp &	GetTimeStamp () const

bool	HasObserver (const EventObject &event) const

void	InvokeEvent (const EventObject &)

void	InvokeEvent (const EventObject &) const

virtual void	Modified () const

void	Register () const override

void	RemoveAllObservers ()

void	RemoveObserver (unsigned long tag)

void	SetDebug (bool debugFlag) const

void	SetReferenceCount (int) override

void	UnRegister () const noexceptoverride

void	SetMetaDataDictionary (const MetaDataDictionary &rhs)

void	SetMetaDataDictionary (MetaDataDictionary &&rrhs)

virtual void	SetObjectName (std::string _arg)

virtual const std::string &	GetObjectName () const

Public Member Functions inherited from itk::LightObject
virtual void	Delete ()

virtual int	GetReferenceCount () const

	itkCloneMacro (Self)

void	Print (std::ostream &os, Indent indent=0) const

Protected Types
using	CostFunctionAdaptorType = SingleValuedVnlCostFunctionAdaptor

Protected Member Functions
const CostFunctionAdaptorType *	GetCostFunctionAdaptor () const

CostFunctionAdaptorType *	GetCostFunctionAdaptor ()

CostFunctionAdaptorType *	GetNonConstCostFunctionAdaptor () const

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

void	SetCostFunctionAdaptor (CostFunctionAdaptorType *adaptor)

	SingleValuedNonLinearVnlOptimizer ()

	~SingleValuedNonLinearVnlOptimizer () override

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

	~SingleValuedNonLinearOptimizer () override=default

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

	~NonLinearOptimizer () override

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

virtual void	SetCurrentPosition (const ParametersType &param)

	~Optimizer () override=default

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

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

virtual void	SetTimeStamp (const TimeStamp &time)

	~Object () override

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_Maximize

Additional Inherited Members
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 Attributes inherited from itk::SingleValuedNonLinearOptimizer
CostFunctionPointer	m_CostFunction

Protected Attributes inherited from itk::Optimizer
ParametersType	m_CurrentPosition

bool	m_ScalesInitialized { false }

Protected Attributes inherited from itk::LightObject
std::atomic< int >	m_ReferenceCount

Member Typedef Documentation

using itk::SingleValuedNonLinearVnlOptimizer::CommandType = ReceptorMemberCommand< Self >

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 57 of file itkSingleValuedNonLinearVnlOptimizer.h.

using itk::SingleValuedNonLinearVnlOptimizer::ConstPointer = SmartPointer< const Self >

Definition at line 47 of file itkSingleValuedNonLinearVnlOptimizer.h.

using itk::SingleValuedNonLinearVnlOptimizer::CostFunctionAdaptorType = SingleValuedVnlCostFunctionAdaptor

protected

Definition at line 99 of file itkSingleValuedNonLinearVnlOptimizer.h.

using itk::SingleValuedNonLinearVnlOptimizer::Pointer = SmartPointer< Self >

Definition at line 46 of file itkSingleValuedNonLinearVnlOptimizer.h.

using itk::SingleValuedNonLinearVnlOptimizer::Self = SingleValuedNonLinearVnlOptimizer

Standard class type aliases.

Definition at line 44 of file itkSingleValuedNonLinearVnlOptimizer.h.

using itk::SingleValuedNonLinearVnlOptimizer::Superclass = SingleValuedNonLinearOptimizer

Definition at line 45 of file itkSingleValuedNonLinearVnlOptimizer.h.

Constructor & Destructor Documentation

itk::SingleValuedNonLinearVnlOptimizer::SingleValuedNonLinearVnlOptimizer ( )

protected

itk::SingleValuedNonLinearVnlOptimizer::~SingleValuedNonLinearVnlOptimizer ( )

overrideprotected

Member Function Documentation

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

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::SingleValuedNonLinearVnlOptimizer::GetCachedDerivative ( ) const

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::SingleValuedNonLinearVnlOptimizer::GetCachedValue ( ) const

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::SingleValuedNonLinearVnlOptimizer::GetCostFunctionAdaptor ( ) const

protected

CostFunctionAdaptorType* itk::SingleValuedNonLinearVnlOptimizer::GetCostFunctionAdaptor ( )

protected

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

virtual

Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.

bool itk::SingleValuedNonLinearVnlOptimizer::GetMinimize ( ) const

inline

Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.

Definition at line 75 of file itkSingleValuedNonLinearVnlOptimizer.h.

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

virtual

Run-time type information (and related methods).

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Reimplemented in itk::LBFGSOptimizer, itk::AmoebaOptimizer, itk::LBFGSBOptimizer, and itk::ConjugateGradientOptimizer.

CostFunctionAdaptorType* itk::SingleValuedNonLinearVnlOptimizer::GetNonConstCostFunctionAdaptor ( ) const

protected

The purpose of this method is to get around the lack of const-correctness in VNL cost-functions and optimizers

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

private

Callback function for the Command Observer

virtual void itk::SingleValuedNonLinearVnlOptimizer::MaximizeOff ( )

virtual

Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.

virtual void itk::SingleValuedNonLinearVnlOptimizer::MaximizeOn ( )

virtual

Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.

void itk::SingleValuedNonLinearVnlOptimizer::MinimizeOff ( )

inline

Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.

Definition at line 81 of file itkSingleValuedNonLinearVnlOptimizer.h.

void itk::SingleValuedNonLinearVnlOptimizer::MinimizeOn ( )

inline

Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.

Definition at line 79 of file itkSingleValuedNonLinearVnlOptimizer.h.

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

overrideprotectedvirtual

Print out internal state

Reimplemented from itk::SingleValuedNonLinearOptimizer.

void itk::SingleValuedNonLinearVnlOptimizer::SetCostFunction ( SingleValuedCostFunction * costFunction )

overridepure 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::LBFGSOptimizer, itk::LBFGSBOptimizer, itk::AmoebaOptimizer, and itk::ConjugateGradientOptimizer.

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

protected

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

virtual

Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.

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

inline

Methods to define whether the cost function will be maximized or minimized. By default the VNL amoeba optimizer is only a minimizer. Maximization is implemented here by notifying the CostFunctionAdaptor which in its turn will multiply the function values and its derivative by -1.0.

Definition at line 77 of file itkSingleValuedNonLinearVnlOptimizer.h.