ITK  5.4.0
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itk::AmoebaOptimizerv4 Class Reference

#include <itkAmoebaOptimizerv4.h>

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 amoeba 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 62 of file itkAmoebaOptimizerv4.h.

+ Inheritance diagram for itk::AmoebaOptimizerv4:
+ Collaboration diagram for itk::AmoebaOptimizerv4:

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

vnl_amoeba * GetOptimizer () const
 
const std::string GetStopConditionDescription () const override
 
 itkOverrideGetNameOfClassMacro (AmoebaOptimizerv4)
 
void SetMetric (MetricType *metric) override
 
void StartOptimization (bool doOnlyInitialization=false) override
 
virtual void SetAutomaticInitialSimplex (bool _arg)
 
virtual void AutomaticInitialSimplexOn ()
 
virtual bool GetAutomaticInitialSimplex () const
 
virtual void SetOptimizeWithRestarts (bool _arg)
 
virtual void OptimizeWithRestartsOn ()
 
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
 itkOverrideGetNameOfClassMacro (SingleValuedNonLinearVnlOptimizerv4)
 
void StartOptimization (bool doOnlyInitialization=false) override
 
virtual const DerivativeTypeGetCachedDerivative () const
 
virtual const ParametersTypeGetCachedCurrentPosition () const
 
- Public Member Functions inherited from itk::ObjectToObjectOptimizerBaseTemplate< double >
virtual bool CanUseScales () const
 
virtual SizeValueType GetCurrentIteration () const
 
virtual const MeasureTypeGetCurrentMetricValue () const
 
virtual const ParametersTypeGetCurrentPosition () const
 
virtual SizeValueType GetNumberOfIterations () const
 
virtual const ThreadIdTypeGetNumberOfWorkUnits () const
 
virtual const ScalesTypeGetScales () const
 
virtual const bool & GetScalesAreIdentity () const
 
bool GetScalesInitialized () const
 
virtual const MeasureTypeGetValue () const
 
virtual const ScalesTypeGetWeights () const
 
virtual const bool & GetWeightsAreIdentity () const
 
 itkOverrideGetNameOfClassMacro (ObjectToObjectOptimizerBaseTemplate)
 
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 MetricTypeGetModifiableMetric ()
 
virtual void SetScales (const ScalesType &scales)
 
virtual void SetDoEstimateScales (bool _arg)
 
virtual const bool & GetDoEstimateScales () const
 
virtual void DoEstimateScalesOn ()
 
- Public Member Functions inherited from itk::Object
unsigned long AddObserver (const EventObject &event, Command *)
 
unsigned long AddObserver (const EventObject &event, Command *) const
 
unsigned long AddObserver (const EventObject &event, std::function< void(const EventObject &)> function) const
 
LightObject::Pointer CreateAnother () const override
 
virtual void DebugOff () const
 
virtual void DebugOn () const
 
CommandGetCommand (unsigned long tag)
 
bool GetDebug () const
 
MetaDataDictionaryGetMetaDataDictionary ()
 
const MetaDataDictionaryGetMetaDataDictionary () const
 
virtual ModifiedTimeType GetMTime () const
 
virtual const TimeStampGetTimeStamp () const
 
bool HasObserver (const EventObject &event) const
 
void InvokeEvent (const EventObject &)
 
void InvokeEvent (const EventObject &) const
 
 itkOverrideGetNameOfClassMacro (Object)
 
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 noexcept override
 
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
Pointer Clone () const
 
virtual void Delete ()
 
virtual int GetReferenceCount () const
 
 itkVirtualGetNameOfClassMacro (LightObject)
 
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 val)
 
- 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
CostFunctionAdaptorTypeGetCostFunctionAdaptor ()
 
const CostFunctionAdaptorTypeGetCostFunctionAdaptor () const
 
CostFunctionAdaptorTypeGetNonConstCostFunctionAdaptor () 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 &timeStamp)
 
 ~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 {}
 
std::unique_ptr< 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

◆ ConstPointer

Definition at line 71 of file itkAmoebaOptimizerv4.h.

◆ CostFunctionAdaptorType

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

Definition at line 155 of file itkAmoebaOptimizerv4.h.

◆ InternalParametersType

InternalParameters type alias.

Definition at line 84 of file itkAmoebaOptimizerv4.h.

◆ ParametersType

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

Definition at line 81 of file itkAmoebaOptimizerv4.h.

◆ Pointer

Definition at line 70 of file itkAmoebaOptimizerv4.h.

◆ Self

Standard "Self" type alias.

Definition at line 68 of file itkAmoebaOptimizerv4.h.

◆ Superclass

Definition at line 69 of file itkAmoebaOptimizerv4.h.

Constructor & Destructor Documentation

◆ AmoebaOptimizerv4()

itk::AmoebaOptimizerv4::AmoebaOptimizerv4 ( )
protected

◆ ~AmoebaOptimizerv4()

itk::AmoebaOptimizerv4::~AmoebaOptimizerv4 ( )
overrideprotected

Member Function Documentation

◆ AutomaticInitialSimplexOn()

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]].

◆ GetAutomaticInitialSimplex()

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]].

◆ GetFunctionConvergenceTolerance()

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().

◆ GetInitialSimplexDelta()

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

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

◆ GetOptimizer()

vnl_amoeba* itk::AmoebaOptimizerv4::GetOptimizer ( ) const

Method for getting access to the internal optimizer.

◆ GetOptimizeWithRestarts()

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.

◆ GetParametersConvergenceTolerance()

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().

◆ GetStopConditionDescription()

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

Report the reason for stopping.

Implements itk::SingleValuedNonLinearVnlOptimizerv4.

◆ itkOverrideGetNameOfClassMacro()

itk::AmoebaOptimizerv4::itkOverrideGetNameOfClassMacro ( AmoebaOptimizerv4  )

Run-time type information (and related methods).

◆ New()

static Pointer itk::AmoebaOptimizerv4::New ( )
static

Method for creation through the object factory.

◆ OptimizeWithRestartsOn()

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.

◆ PrintSelf()

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.

◆ SetAutomaticInitialSimplex()

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]].

◆ SetFunctionConvergenceTolerance()

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().

◆ SetInitialSimplexDelta()

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.

◆ SetMetric()

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

Plug in a Cost Function into the optimizer

Implements itk::SingleValuedNonLinearVnlOptimizerv4.

◆ SetOptimizeWithRestarts()

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.

◆ SetParametersConvergenceTolerance()

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().

◆ StartOptimization()

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

Start optimization with an initial value.

Reimplemented from itk::ObjectToObjectOptimizerBaseTemplate< double >.

◆ ValidateSettings()

void itk::AmoebaOptimizerv4::ValidateSettings ( )
private

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

Member Data Documentation

◆ m_AutomaticInitialSimplex

bool itk::AmoebaOptimizerv4::m_AutomaticInitialSimplex {}
private

Definition at line 164 of file itkAmoebaOptimizerv4.h.

◆ m_FunctionConvergenceTolerance

MeasureType itk::AmoebaOptimizerv4::m_FunctionConvergenceTolerance {}
private

Definition at line 163 of file itkAmoebaOptimizerv4.h.

◆ m_InitialSimplexDelta

ParametersType itk::AmoebaOptimizerv4::m_InitialSimplexDelta {}
private

Definition at line 165 of file itkAmoebaOptimizerv4.h.

◆ m_OptimizeWithRestarts

bool itk::AmoebaOptimizerv4::m_OptimizeWithRestarts {}
private

Definition at line 166 of file itkAmoebaOptimizerv4.h.

◆ m_ParametersConvergenceTolerance

ParametersType::ValueType itk::AmoebaOptimizerv4::m_ParametersConvergenceTolerance {}
private

Definition at line 162 of file itkAmoebaOptimizerv4.h.

◆ m_StopConditionDescription

std::ostringstream itk::AmoebaOptimizerv4::m_StopConditionDescription {}
private

Definition at line 169 of file itkAmoebaOptimizerv4.h.

◆ m_VnlOptimizer

std::unique_ptr<vnl_amoeba> itk::AmoebaOptimizerv4::m_VnlOptimizer
private

Definition at line 167 of file itkAmoebaOptimizerv4.h.


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