itk::AmoebaOptimizerv4 Class Reference

#include <itkAmoebaOptimizerv4.h>

Inheritance diagram for itk::AmoebaOptimizerv4:

Collaboration diagram for itk::AmoebaOptimizerv4:

Detailed Description

Wrap of the vnl_amoeba algorithm.

AmoebaOptimizerv4 is a wrapper around the vnl_amoeba algorithm which is an implementation of the Nelder-Meade downhill simplex problem. For most problems, it is a few times slower than a Levenberg-Marquardt algorithm but does not require derivatives of its cost function. It works by creating a simplex (n+1 points in ND space). The cost function is evaluated at each corner of the simplex. The simplex is then modified (by reflecting a corner about the opposite edge, by shrinking the entire simplex, by contracting one edge of the simplex, or by expanding the simplex) in searching for the minimum of the cost function.

The methods AutomaticInitialSimplex() and SetInitialSimplexDelta() control whether the optimizer defines the initial simplex automatically (by constructing a very small simplex around the initial position) or uses a user supplied simplex size.

The method SetOptimizeWithRestarts() indicates that the amoeabe algorithm should be rerun after if converges. This heuristic increases the chances of escaping from a local optimum. Each time the simplex is initialized with the best solution obtained by the previous runs. The edge length is half of that from the previous iteration. The heuristic is terminated if the total number of iterations is greater-equal than the maximal number of iterations (SetNumberOfIterations) or the difference between the current function value and the best function value is less than a threshold (SetFunctionConvergenceTolerance) and max(|best_parameters_i - current_parameters_i|) is less than a threshold (SetParametersConvergenceTolerance).

Definition at line 60 of file itkAmoebaOptimizerv4.h.

Public Types
using	ConstPointer = SmartPointer< const Self >
using	InternalParametersType = vnl_vector< double >
using	ParametersType = Superclass::ParametersType
using	Pointer = SmartPointer< Self >
using	Self = AmoebaOptimizerv4
using	Superclass = SingleValuedNonLinearVnlOptimizerv4
Public Types inherited from itk::SingleValuedNonLinearVnlOptimizerv4
using	CommandType = ReceptorMemberCommand< Self >
using	ConstPointer = SmartPointer< const Self >
using	DerivativeType = Superclass::DerivativeType
using	MetricType = Superclass::MetricType
using	ParametersType = Superclass::ParametersType
using	Pointer = SmartPointer< Self >
using	ScalesType = Superclass::ScalesType
using	Self = SingleValuedNonLinearVnlOptimizerv4
using	StopConditionDescriptionType = Superclass::StopConditionDescriptionType
using	StopConditionReturnStringType = Superclass::StopConditionReturnStringType
using	Superclass = ObjectToObjectOptimizerBase
Public Types inherited from itk::ObjectToObjectOptimizerBaseTemplate< double >
using	ConstPointer = SmartPointer< const Self >
using	DerivativeType = typename MetricType::DerivativeType
using	MeasureType = typename MetricType::MeasureType
using	MetricType = ObjectToObjectMetricBaseTemplate< double >
using	MetricTypePointer = typename MetricType::Pointer
using	NumberOfParametersType = typename MetricType::NumberOfParametersType
using	ParametersType = OptimizerParameters< double >
using	Pointer = SmartPointer< Self >
using	ScalesEstimatorType = OptimizerParameterScalesEstimatorTemplate< double >
using	ScalesType = OptimizerParameters< double >
using	Self = ObjectToObjectOptimizerBaseTemplate
using	StopConditionDescriptionType = std::ostringstream
using	StopConditionReturnStringType = std::string
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 ::itk::LightObject::Pointer	CreateAnother () const
virtual const char *	GetNameOfClass () const
vnl_amoeba *	GetOptimizer () const
const std::string	GetStopConditionDescription () const override
void	SetMetric (MetricType *metric) override
void	StartOptimization (bool doOnlyInitialization=false) override
virtual void	SetAutomaticInitialSimplex (bool _arg)
virtual void	AutomaticInitialSimplexOn ()
virtual void	AutomaticInitialSimplexOff ()
virtual bool	GetAutomaticInitialSimplex () const
virtual void	SetOptimizeWithRestarts (bool _arg)
virtual void	OptimizeWithRestartsOn ()
virtual void	OptimizeWithRestartsOff ()
virtual bool	GetOptimizeWithRestarts () const
void	SetInitialSimplexDelta (ParametersType initialSimplexDelta, bool automaticInitialSimplex=false)
virtual ParametersType	GetInitialSimplexDelta () const
virtual void	SetParametersConvergenceTolerance (double _arg)
virtual double	GetParametersConvergenceTolerance () const
virtual void	SetFunctionConvergenceTolerance (double _arg)
virtual double	GetFunctionConvergenceTolerance () const
Public Member Functions inherited from itk::SingleValuedNonLinearVnlOptimizerv4
void	StartOptimization (bool doOnlyInitialization=false) override
virtual const DerivativeType &	GetCachedDerivative () const
virtual const ParametersType &	GetCachedCurrentPosition () const
Public Member Functions inherited from itk::ObjectToObjectOptimizerBaseTemplate< double >
virtual SizeValueType	GetCurrentIteration () const
virtual const MeasureType &	GetCurrentMetricValue () const
virtual const ParametersType &	GetCurrentPosition () const
virtual SizeValueType	GetNumberOfIterations () const
virtual const ThreadIdType &	GetNumberOfWorkUnits () const
virtual const ScalesType &	GetScales () const
virtual const bool &	GetScalesAreIdentity () const
bool	GetScalesInitialized () const
virtual const MeasureType &	GetValue () const
virtual const ScalesType &	GetWeights () const
virtual const bool &	GetWeightsAreIdentity () const
virtual void	SetNumberOfIterations (SizeValueType _arg)
virtual void	SetNumberOfWorkUnits (ThreadIdType number)
virtual void	SetScalesEstimator (ScalesEstimatorType *_arg)
virtual void	SetWeights (ScalesType _arg)
virtual void	SetMetric (MetricType *_arg)
virtual MetricType *	GetModifiableMetric ()
virtual const MetricType *	GetMetric () const
virtual void	SetScales (const ScalesType &scales)
virtual void	SetDoEstimateScales (bool _arg)
virtual const bool &	GetDoEstimateScales () const
virtual void	DoEstimateScalesOn ()
virtual void	DoEstimateScalesOff ()
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

Static Public Member Functions
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 Types
using	CostFunctionAdaptorType = Superclass::CostFunctionAdaptorType
Protected Types inherited from itk::SingleValuedNonLinearVnlOptimizerv4
using	CostFunctionAdaptorType = SingleValuedVnlCostFunctionAdaptorv4

Protected Member Functions
	AmoebaOptimizerv4 ()
void	PrintSelf (std::ostream &os, Indent indent) const override
	~AmoebaOptimizerv4 () override
Protected Member Functions inherited from itk::SingleValuedNonLinearVnlOptimizerv4
const CostFunctionAdaptorType *	GetCostFunctionAdaptor () const
CostFunctionAdaptorType *	GetCostFunctionAdaptor ()
CostFunctionAdaptorType *	GetNonConstCostFunctionAdaptor () const
void	PrintSelf (std::ostream &os, Indent indent) const override
void	SetCostFunctionAdaptor (CostFunctionAdaptorType *adaptor)
	SingleValuedNonLinearVnlOptimizerv4 ()
	~SingleValuedNonLinearVnlOptimizerv4 () override
Protected Member Functions inherited from itk::ObjectToObjectOptimizerBaseTemplate< double >
void	PrintSelf (std::ostream &os, Indent indent) const override
	ObjectToObjectOptimizerBaseTemplate ()
	~ObjectToObjectOptimizerBaseTemplate () override
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	ValidateSettings ()

Private Attributes
bool	m_AutomaticInitialSimplex
MeasureType	m_FunctionConvergenceTolerance
ParametersType	m_InitialSimplexDelta
bool	m_OptimizeWithRestarts
ParametersType::ValueType	m_ParametersConvergenceTolerance
std::ostringstream	m_StopConditionDescription
vnl_amoeba *	m_VnlOptimizer

Additional Inherited Members
Protected Attributes inherited from itk::ObjectToObjectOptimizerBaseTemplate< double >
SizeValueType	m_CurrentIteration
MeasureType	m_CurrentMetricValue
bool	m_DoEstimateScales
MetricTypePointer	m_Metric
SizeValueType	m_NumberOfIterations
ThreadIdType	m_NumberOfWorkUnits
ScalesType	m_Scales
bool	m_ScalesAreIdentity
ScalesEstimatorType::Pointer	m_ScalesEstimator
ScalesType	m_Weights
bool	m_WeightsAreIdentity
Protected Attributes inherited from itk::LightObject
std::atomic< int >	m_ReferenceCount

Member Typedef Documentation

using itk::AmoebaOptimizerv4::ConstPointer = SmartPointer< const Self >

Definition at line 70 of file itkAmoebaOptimizerv4.h.

using itk::AmoebaOptimizerv4::CostFunctionAdaptorType = Superclass::CostFunctionAdaptorType

protected

Definition at line 149 of file itkAmoebaOptimizerv4.h.

using itk::AmoebaOptimizerv4::InternalParametersType = vnl_vector< double >

InternalParameters type alias.

Definition at line 83 of file itkAmoebaOptimizerv4.h.

using itk::AmoebaOptimizerv4::ParametersType = Superclass::ParametersType

Parameters type. It defines a position in the optimization search space.

Definition at line 80 of file itkAmoebaOptimizerv4.h.

using itk::AmoebaOptimizerv4::Pointer = SmartPointer< Self >

Definition at line 69 of file itkAmoebaOptimizerv4.h.

using itk::AmoebaOptimizerv4::Self = AmoebaOptimizerv4

Standard "Self" type alias.

Definition at line 67 of file itkAmoebaOptimizerv4.h.

using itk::AmoebaOptimizerv4::Superclass = SingleValuedNonLinearVnlOptimizerv4

Definition at line 68 of file itkAmoebaOptimizerv4.h.

Constructor & Destructor Documentation

itk::AmoebaOptimizerv4::AmoebaOptimizerv4 ( )

protected

itk::AmoebaOptimizerv4::~AmoebaOptimizerv4 ( )

overrideprotected

Member Function Documentation

virtual void itk::AmoebaOptimizerv4::AutomaticInitialSimplexOff ( )

virtual

Set/Get the mode which determines how the amoeba algorithm defines the initial simplex. Default is AutomaticInitialSimplexOn. If AutomaticInitialSimplex is on, the initial simplex is created with a default size. If AutomaticInitialSimplex is off, then InitialSimplexDelta will be used to define the initial simplex, setting the ith corner of the simplex as [x0[0], x0[1], ..., x0[i]+InitialSimplexDelta[i], ..., x0[d-1]].

virtual void itk::AmoebaOptimizerv4::AutomaticInitialSimplexOn ( )

virtual

Set/Get the mode which determines how the amoeba algorithm defines the initial simplex. Default is AutomaticInitialSimplexOn. If AutomaticInitialSimplex is on, the initial simplex is created with a default size. If AutomaticInitialSimplex is off, then InitialSimplexDelta will be used to define the initial simplex, setting the ith corner of the simplex as [x0[0], x0[1], ..., x0[i]+InitialSimplexDelta[i], ..., x0[d-1]].

virtual::itk::LightObject::Pointer itk::AmoebaOptimizerv4::CreateAnother ( ) 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::Object.

virtual bool itk::AmoebaOptimizerv4::GetAutomaticInitialSimplex ( ) const

virtual

Set/Get the mode which determines how the amoeba algorithm defines the initial simplex. Default is AutomaticInitialSimplexOn. If AutomaticInitialSimplex is on, the initial simplex is created with a default size. If AutomaticInitialSimplex is off, then InitialSimplexDelta will be used to define the initial simplex, setting the ith corner of the simplex as [x0[0], x0[1], ..., x0[i]+InitialSimplexDelta[i], ..., x0[d-1]].

virtual double itk::AmoebaOptimizerv4::GetFunctionConvergenceTolerance ( ) const

virtual

The optimization algorithm will terminate when the simplex diameter and the difference in cost function values at the corners of the simplex falls below user specified thresholds. The cost function convergence threshold is set via SetFunctionConvergenceTolerance().

virtual ParametersType itk::AmoebaOptimizerv4::GetInitialSimplexDelta ( ) const

virtual

Set/Get the deltas that are used to define the initial simplex when AutomaticInitialSimplex is off.

virtual const char* itk::AmoebaOptimizerv4::GetNameOfClass ( ) const

virtual

Run-time type information (and related methods).

Reimplemented from itk::SingleValuedNonLinearVnlOptimizerv4.

vnl_amoeba* itk::AmoebaOptimizerv4::GetOptimizer

(

)

const

Method for getting access to the internal optimizer.

virtual bool itk::AmoebaOptimizerv4::GetOptimizeWithRestarts ( ) const

virtual

Set/Get the mode that determines if we want to use multiple runs of the Amoeba optimizer. If true, then the optimizer is rerun after it converges. The additional runs are performed using a simplex initialized with the best solution obtained by the previous runs. The edge length is half of that from the previous iteration.

virtual double itk::AmoebaOptimizerv4::GetParametersConvergenceTolerance ( ) const

virtual

The optimization algorithm will terminate when the simplex diameter and the difference in cost function values at the corners of the simplex falls below user specified thresholds. The simplex diameter threshold is set via SetParametersConvergenceTolerance().

const std::string itk::AmoebaOptimizerv4::GetStopConditionDescription ( ) const

overridevirtual

Report the reason for stopping.

Implements itk::SingleValuedNonLinearVnlOptimizerv4.

static Pointer itk::AmoebaOptimizerv4::New ( )

static

Method for creation through the object factory.

virtual void itk::AmoebaOptimizerv4::OptimizeWithRestartsOff ( )

virtual

Set/Get the mode that determines if we want to use multiple runs of the Amoeba optimizer. If true, then the optimizer is rerun after it converges. The additional runs are performed using a simplex initialized with the best solution obtained by the previous runs. The edge length is half of that from the previous iteration.

virtual void itk::AmoebaOptimizerv4::OptimizeWithRestartsOn ( )

virtual

Set/Get the mode that determines if we want to use multiple runs of the Amoeba optimizer. If true, then the optimizer is rerun after it converges. The additional runs are performed using a simplex initialized with the best solution obtained by the previous runs. The edge length is half of that from the previous iteration.

void itk::AmoebaOptimizerv4::PrintSelf ( std::ostream &  os, Indent  indent  ) const

overrideprotectedvirtual

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::Object.

virtual void itk::AmoebaOptimizerv4::SetAutomaticInitialSimplex ( bool  _arg )

virtual

Set/Get the mode which determines how the amoeba algorithm defines the initial simplex. Default is AutomaticInitialSimplexOn. If AutomaticInitialSimplex is on, the initial simplex is created with a default size. If AutomaticInitialSimplex is off, then InitialSimplexDelta will be used to define the initial simplex, setting the ith corner of the simplex as [x0[0], x0[1], ..., x0[i]+InitialSimplexDelta[i], ..., x0[d-1]].

virtual void itk::AmoebaOptimizerv4::SetFunctionConvergenceTolerance ( double  _arg )

virtual

The optimization algorithm will terminate when the simplex diameter and the difference in cost function values at the corners of the simplex falls below user specified thresholds. The cost function convergence threshold is set via SetFunctionConvergenceTolerance().

void itk::AmoebaOptimizerv4::SetInitialSimplexDelta	(	ParametersType	initialSimplexDelta,
		bool	automaticInitialSimplex = false
	)

Set/Get the deltas that are used to define the initial simplex when AutomaticInitialSimplex is off.

void itk::AmoebaOptimizerv4::SetMetric ( MetricType *  metric )

overridevirtual

Plug in a Cost Function into the optimizer

Implements itk::SingleValuedNonLinearVnlOptimizerv4.

virtual void itk::AmoebaOptimizerv4::SetOptimizeWithRestarts ( bool  _arg )

virtual

Set/Get the mode that determines if we want to use multiple runs of the Amoeba optimizer. If true, then the optimizer is rerun after it converges. The additional runs are performed using a simplex initialized with the best solution obtained by the previous runs. The edge length is half of that from the previous iteration.

virtual void itk::AmoebaOptimizerv4::SetParametersConvergenceTolerance ( double  _arg )

virtual

The optimization algorithm will terminate when the simplex diameter and the difference in cost function values at the corners of the simplex falls below user specified thresholds. The simplex diameter threshold is set via SetParametersConvergenceTolerance().

void itk::AmoebaOptimizerv4::StartOptimization ( bool  doOnlyInitialization = false )

overridevirtual

Start optimization with an initial value.

Reimplemented from itk::ObjectToObjectOptimizerBaseTemplate< double >.

void itk::AmoebaOptimizerv4::ValidateSettings ( )

private

Check that the settings are valid. If not throw an exception.

Member Data Documentation

bool itk::AmoebaOptimizerv4::m_AutomaticInitialSimplex

private

Definition at line 157 of file itkAmoebaOptimizerv4.h.

MeasureType itk::AmoebaOptimizerv4::m_FunctionConvergenceTolerance

private

Definition at line 156 of file itkAmoebaOptimizerv4.h.

ParametersType itk::AmoebaOptimizerv4::m_InitialSimplexDelta

private

Definition at line 158 of file itkAmoebaOptimizerv4.h.

bool itk::AmoebaOptimizerv4::m_OptimizeWithRestarts

private

Definition at line 159 of file itkAmoebaOptimizerv4.h.

ParametersType::ValueType itk::AmoebaOptimizerv4::m_ParametersConvergenceTolerance

private

Definition at line 155 of file itkAmoebaOptimizerv4.h.

std::ostringstream itk::AmoebaOptimizerv4::m_StopConditionDescription

private

Definition at line 162 of file itkAmoebaOptimizerv4.h.

vnl_amoeba* itk::AmoebaOptimizerv4::m_VnlOptimizer

private

Definition at line 160 of file itkAmoebaOptimizerv4.h.

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The documentation for this class was generated from the following file:

• itkAmoebaOptimizerv4.h