#include <itkParticleSwarmOptimizerBase.h>

Detailed Description

Abstract implementation of a Particle Swarm Optimization (PSO) algorithm.

The PSO algorithm was originally presented in:
J. Kennedy, R. Eberhart, "Particle Swarm Optimization", Proc. IEEE Int. Neural Networks, 1995.

The algorithm is a stochastic global search optimization approach. Optimization is performed by maintaining a swarm of particles that traverse the parameter space, searching for the optimal function value. Associated with each particle are its location and speed, in parameter space.

Swarm initialization is performed within the user supplied parameter bounds using either a uniform distribution or a normal distribution centered on the initial parameter values supplied by the user. The search terminates when the maximal number of iterations has been reached or when the change in the best value in the past \(g\) generations is below a threshold and the swarm has collapsed (i.e. best personal particle locations are close to the swarm's best location in parameter space).

The actual optimization procedure, updating the swarm, is performed in the subclasses, required to implement the UpdateSwarm() method.

NOTE: This implementation only performs minimization.

Definition at line 56 of file itkParticleSwarmOptimizerBase.h.

Inheritance diagram for itk::ParticleSwarmOptimizerBase:

Collaboration diagram for itk::ParticleSwarmOptimizerBase:

Classes
struct	ParticleData

Public Types
using	ConstPointer = SmartPointer< const Self >

using	MeasureType = CostFunctionType::MeasureType

using	NumberOfGenerationsType = unsigned int

using	NumberOfIterationsType = unsigned int

using	NumberOfParticlesType = unsigned int

using	ParameterBoundsType = std::vector< std::pair< ParametersType::ValueType, ParametersType::ValueType > >

using	Pointer = SmartPointer< Self >

using	RandomVariateGeneratorType = Statistics::MersenneTwisterRandomVariateGenerator

using	Self = ParticleSwarmOptimizerBase

using	Superclass = SingleValuedNonLinearOptimizer

using	SwarmType = std::vector< ParticleData >

using	ValueType = ParametersType::ValueType

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 MeasureType	GetFunctionConvergenceTolerance ()

const char *	GetNameOfClass () const override

ParameterBoundsType	GetParameterBounds () const

std::string	GetStopConditionDescription () const override

MeasureType	GetValue () const

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

virtual void	SetFunctionConvergenceTolerance (MeasureType _arg)

void	StartOptimization () override


virtual void	SetInitializeNormalDistribution (bool _arg)

virtual bool	GetInitializeNormalDistribution ()

virtual void	InitializeNormalDistributionOn ()


void	SetInitialSwarm (const SwarmType &initialSwarm)

void	ClearSwarm ()


virtual void	SetPrintSwarm (bool _arg)

virtual bool	GetPrintSwarm ()

virtual void	PrintSwarmOn ()


void	SetNumberOfParticles (NumberOfParticlesType n)

virtual NumberOfParticlesType	GetNumberOfParticles ()


virtual void	SetMaximalNumberOfIterations (NumberOfIterationsType _arg)

virtual NumberOfIterationsType	GetMaximalNumberOfIterations ()


virtual void	SetNumberOfGenerationsWithMinimalImprovement (NumberOfGenerationsType _arg)

virtual NumberOfGenerationsType	GetNumberOfGenerationsWithMinimalImprovement ()


virtual void	SetParameterBounds (ParameterBoundsType &bounds)

void	SetParameterBounds (std::pair< ParametersType::ValueType, ParametersType::ValueType > &bounds, unsigned int n)


void	SetParametersConvergenceTolerance (ValueType convergenceTolerance, unsigned int sz)

virtual void	SetParametersConvergenceTolerance (ParametersType _arg)

virtual ParametersType	GetParametersConvergenceTolerance ()

virtual double	GetPercentageParticlesConverged ()

virtual void	SetPercentageParticlesConverged (double _arg)


virtual void	SetSeed (RandomVariateGeneratorType::IntegerType _arg)

virtual RandomVariateGeneratorType::IntegerType	GetSeed ()


virtual void	SetUseSeed (bool _arg)

virtual bool	GetUseSeed ()

virtual void	UseSeedOn ()

Public Member Functions inherited from itk::SingleValuedNonLinearOptimizer
virtual CostFunctionType *	GetModifiableCostFunction ()

const char *	GetNameOfClass () const override

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 void	SetInitialPosition (const ParametersType &param)

void	SetScales (const ScalesType &scales)

virtual const ScalesType &	GetScales () const

virtual const ScalesType &	GetInverseScales () const

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

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) const

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

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

Protected Member Functions
void	FileInitialization ()

virtual void	Initialize ()

	ParticleSwarmOptimizerBase ()

void	PrintParamtersType (const ParametersType &x, std::ostream &os) const

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

void	RandomInitialization ()

virtual void	UpdateSwarm ()=0

virtual void	ValidateSettings ()

	~ParticleSwarmOptimizerBase () override

Protected Member Functions inherited from itk::SingleValuedNonLinearOptimizer
void	PrintSelf (std::ostream &os, Indent indent) const override

	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 &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 ()

Protected Attributes
CostFunctionType::MeasureType	m_FunctionBestValue { 0 }

std::vector< MeasureType >	m_FunctionBestValueMemory {}

CostFunctionType::MeasureType	m_FunctionConvergenceTolerance {}

bool	m_InitializeNormalDistribution {}

NumberOfIterationsType	m_IterationIndex { 0 }

NumberOfIterationsType	m_MaximalNumberOfIterations {}

NumberOfGenerationsType	m_NumberOfGenerationsWithMinimalImprovement {}

NumberOfParticlesType	m_NumberOfParticles {}

ParameterBoundsType	m_ParameterBounds {}

ParametersType	m_ParametersBestValue {}

ParametersType	m_ParametersConvergenceTolerance {}

std::vector< ParticleData >	m_Particles {}

double	m_PercentageParticlesConverged {}

bool	m_PrintSwarm {}

RandomVariateGeneratorType::IntegerType	m_Seed {}

std::ostringstream	m_StopConditionDescription {}

bool	m_UseSeed {}

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 {}

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 val)

Static Public Member Functions inherited from itk::LightObject
static void	BreakOnError ()

static Pointer	New ()

Member Typedef Documentation

◆ ConstPointer

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

Definition at line 65 of file itkParticleSwarmOptimizerBase.h.

◆ MeasureType

using itk::ParticleSwarmOptimizerBase::MeasureType = CostFunctionType::MeasureType

Definition at line 85 of file itkParticleSwarmOptimizerBase.h.

◆ NumberOfGenerationsType

using itk::ParticleSwarmOptimizerBase::NumberOfGenerationsType = unsigned int

Definition at line 84 of file itkParticleSwarmOptimizerBase.h.

◆ NumberOfIterationsType

using itk::ParticleSwarmOptimizerBase::NumberOfIterationsType = unsigned int

Definition at line 82 of file itkParticleSwarmOptimizerBase.h.

◆ NumberOfParticlesType

using itk::ParticleSwarmOptimizerBase::NumberOfParticlesType = unsigned int

Definition at line 83 of file itkParticleSwarmOptimizerBase.h.

◆ ParameterBoundsType

using itk::ParticleSwarmOptimizerBase::ParameterBoundsType = std::vector<std::pair<ParametersType::ValueType, ParametersType::ValueType> >

Examples: Examples/IO/XML/itkParticleSwarmOptimizerDOMReader.cxx, and Examples/IO/XML/itkParticleSwarmOptimizerSAXReader.cxx.

Definition at line 70 of file itkParticleSwarmOptimizerBase.h.

◆ Pointer

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

Definition at line 64 of file itkParticleSwarmOptimizerBase.h.

◆ RandomVariateGeneratorType

using itk::ParticleSwarmOptimizerBase::RandomVariateGeneratorType = Statistics::MersenneTwisterRandomVariateGenerator

Definition at line 87 of file itkParticleSwarmOptimizerBase.h.

◆ Self

using itk::ParticleSwarmOptimizerBase::Self = ParticleSwarmOptimizerBase

Standard "Self" type alias.

Definition at line 62 of file itkParticleSwarmOptimizerBase.h.

◆ Superclass

using itk::ParticleSwarmOptimizerBase::Superclass = SingleValuedNonLinearOptimizer

Definition at line 63 of file itkParticleSwarmOptimizerBase.h.

◆ SwarmType

using itk::ParticleSwarmOptimizerBase::SwarmType = std::vector<ParticleData>

Definition at line 81 of file itkParticleSwarmOptimizerBase.h.

◆ ValueType

using itk::ParticleSwarmOptimizerBase::ValueType = ParametersType::ValueType

Definition at line 86 of file itkParticleSwarmOptimizerBase.h.

Constructor & Destructor Documentation

◆ ParticleSwarmOptimizerBase()

itk::ParticleSwarmOptimizerBase::ParticleSwarmOptimizerBase ( )

protected

◆ ~ParticleSwarmOptimizerBase()

itk::ParticleSwarmOptimizerBase::~ParticleSwarmOptimizerBase ( )

overrideprotected

Member Function Documentation

◆ ClearSwarm()

void itk::ParticleSwarmOptimizerBase::ClearSwarm ( )

Specify the initial swarm. Useful for evaluating PSO variants. If the initial swarm is set it will be used. To revert to random initialization (uniform or normal particle distributions) set using an empty swarm.

◆ FileInitialization()

void itk::ParticleSwarmOptimizerBase::FileInitialization ( )

protected

◆ GetFunctionConvergenceTolerance()

virtual MeasureType itk::ParticleSwarmOptimizerBase::GetFunctionConvergenceTolerance ( )

virtual

◆ GetInitializeNormalDistribution()

virtual bool itk::ParticleSwarmOptimizerBase::GetInitializeNormalDistribution ( )

virtual

Specify whether to initialize the particles using a normal distribution centered on the user supplied initial value or a uniform distribution. If the optimum is expected to be near the initial value it is likely that initializing with a normal distribution will result in faster convergence.

◆ GetMaximalNumberOfIterations()

virtual NumberOfIterationsType itk::ParticleSwarmOptimizerBase::GetMaximalNumberOfIterations ( )

virtual

Set/Get maximal number of iterations - the maximal number of function evaluations is m_MaximalNumberOfIterations*m_NumberOfParticles

◆ GetNameOfClass()

const char* itk::ParticleSwarmOptimizerBase::GetNameOfClass ( ) const

overridevirtual

See also: LightObject::GetNameOfClass()

Reimplemented from itk::NonLinearOptimizer.

◆ GetNumberOfGenerationsWithMinimalImprovement()

virtual NumberOfGenerationsType itk::ParticleSwarmOptimizerBase::GetNumberOfGenerationsWithMinimalImprovement ( )

virtual

Set/Get the number of generations to continue with minimal improvement in the function value, |f_best(g_i) - f_best(g_k)|<threshold where k <= i+NumberOfGenerationsWithMinimalImprovement Minimal value is one.

◆ GetNumberOfParticles()

virtual NumberOfParticlesType itk::ParticleSwarmOptimizerBase::GetNumberOfParticles ( )

virtual

Set/Get number of particles in the swarm - the maximal number of function evaluations is m_MaximalNumberOfIterations*m_NumberOfParticles

◆ GetParameterBounds()

ParameterBoundsType itk::ParticleSwarmOptimizerBase::GetParameterBounds ( ) const

◆ GetParametersConvergenceTolerance()

virtual ParametersType itk::ParticleSwarmOptimizerBase::GetParametersConvergenceTolerance ( )

virtual

Set parameters convergence tolerance using the same value for all, sz, parameters

◆ GetPercentageParticlesConverged()

virtual double itk::ParticleSwarmOptimizerBase::GetPercentageParticlesConverged ( )

virtual

Set parameters convergence tolerance using the same value for all, sz, parameters

◆ GetPrintSwarm()

virtual bool itk::ParticleSwarmOptimizerBase::GetPrintSwarm ( )

virtual

Indicate whether or not to output the swarm information when printing an object. By default this option is turned off as it generates too much information.

◆ GetSeed()

virtual RandomVariateGeneratorType::IntegerType itk::ParticleSwarmOptimizerBase::GetSeed ( )

virtual

Set the random number seed for the swarm. Use this method to produce repeatable results, typically, for testing.

◆ GetStopConditionDescription()

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

overridevirtual

Get the reason for termination

Reimplemented from itk::Optimizer.

◆ GetUseSeed()

virtual bool itk::ParticleSwarmOptimizerBase::GetUseSeed ( )

virtual

Use a specific seed to initialize the random number generator. If On, use m_Seed to seed the random number generator. Default is Off.

◆ GetValue()

MeasureType itk::ParticleSwarmOptimizerBase::GetValue ( ) const

Get the function value for the current position. NOTE: This value is only valid during and after the execution of the StartOptimization() method.

◆ Initialize()

virtual void itk::ParticleSwarmOptimizerBase::Initialize ( )

protectedvirtual

Initialize the particle swarm, and seed the random number generator.

◆ InitializeNormalDistributionOn()

virtual void itk::ParticleSwarmOptimizerBase::InitializeNormalDistributionOn ( )

virtual

Specify whether to initialize the particles using a normal distribution centered on the user supplied initial value or a uniform distribution. If the optimum is expected to be near the initial value it is likely that initializing with a normal distribution will result in faster convergence.

◆ PrintParamtersType()

void itk::ParticleSwarmOptimizerBase::PrintParamtersType	(	const ParametersType &	x,
		std::ostream &	os
	)		const

protected

◆ PrintSelf()

void itk::ParticleSwarmOptimizerBase::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::Optimizer.

◆ PrintSwarm()

void itk::ParticleSwarmOptimizerBase::PrintSwarm	(	std::ostream &	os,
		Indent	indent
	)		const

Print the swarm information to the given output stream. Each line (particle data) is of the form: current_parameters current_velocity current_value best_parameters best_value

◆ PrintSwarmOn()

virtual void itk::ParticleSwarmOptimizerBase::PrintSwarmOn ( )

virtual

Indicate whether or not to output the swarm information when printing an object. By default this option is turned off as it generates too much information.

◆ RandomInitialization()

void itk::ParticleSwarmOptimizerBase::RandomInitialization ( )

protected

◆ SetFunctionConvergenceTolerance()

virtual void itk::ParticleSwarmOptimizerBase::SetFunctionConvergenceTolerance ( MeasureType _arg )

virtual

The optimization algorithm will terminate when the function improvement in the last m_NumberOfGenerationsWithMinimalImprovement generations is less than m_FunctionConvergenceTolerance and the maximal distance between particles and the best particle in each dimension is less than m_ParametersConvergenceTolerance[i] for the specified percentage of the particles. That is, we haven't improved the best function value for a while and in the parameter space most (m%) of our particles attained their best value close to the swarm's best value. NOTE: The use of different tolerances for each dimension is desired when optimizing over non-commensurate parameters (e.g. rotation and translation). Alternatively, we could use ITK's parameter scaling approach. The current approach seems more intuitive.

◆ SetInitializeNormalDistribution()

virtual void itk::ParticleSwarmOptimizerBase::SetInitializeNormalDistribution ( bool _arg )

virtual

Specify whether to initialize the particles using a normal distribution centered on the user supplied initial value or a uniform distribution. If the optimum is expected to be near the initial value it is likely that initializing with a normal distribution will result in faster convergence.

◆ SetInitialSwarm()

void itk::ParticleSwarmOptimizerBase::SetInitialSwarm ( const SwarmType & initialSwarm )

Specify the initial swarm. Useful for evaluating PSO variants. If the initial swarm is set it will be used. To revert to random initialization (uniform or normal particle distributions) set using an empty swarm.

◆ SetMaximalNumberOfIterations()

virtual void itk::ParticleSwarmOptimizerBase::SetMaximalNumberOfIterations ( NumberOfIterationsType _arg )

virtual

Set/Get maximal number of iterations - the maximal number of function evaluations is m_MaximalNumberOfIterations*m_NumberOfParticles

◆ SetNumberOfGenerationsWithMinimalImprovement()

virtual void itk::ParticleSwarmOptimizerBase::SetNumberOfGenerationsWithMinimalImprovement ( NumberOfGenerationsType _arg )

virtual

Set/Get the number of generations to continue with minimal improvement in the function value, |f_best(g_i) - f_best(g_k)|<threshold where k <= i+NumberOfGenerationsWithMinimalImprovement Minimal value is one.

◆ SetNumberOfParticles()

void itk::ParticleSwarmOptimizerBase::SetNumberOfParticles ( NumberOfParticlesType n )

Set/Get number of particles in the swarm - the maximal number of function evaluations is m_MaximalNumberOfIterations*m_NumberOfParticles

◆ SetParameterBounds() [1/2]

virtual void itk::ParticleSwarmOptimizerBase::SetParameterBounds ( ParameterBoundsType & bounds )

virtual

Set/Get the parameter bounds. Search for optimal value is inside these bounds. NOTE: It is assumed that the first entry is the minimal value, second is the maximal value.

◆ SetParameterBounds() [2/2]

void itk::ParticleSwarmOptimizerBase::SetParameterBounds	(	std::pair< ParametersType::ValueType, ParametersType::ValueType > &	bounds,
		unsigned int	n
	)

Set/Get the parameter bounds. Search for optimal value is inside these bounds. NOTE: It is assumed that the first entry is the minimal value, second is the maximal value.

◆ SetParametersConvergenceTolerance() [1/2]

virtual void itk::ParticleSwarmOptimizerBase::SetParametersConvergenceTolerance ( ParametersType _arg )

virtual

Set parameters convergence tolerance using the same value for all, sz, parameters

◆ SetParametersConvergenceTolerance() [2/2]

void itk::ParticleSwarmOptimizerBase::SetParametersConvergenceTolerance	(	ValueType	convergenceTolerance,
		unsigned int	sz
	)

Set parameters convergence tolerance using the same value for all, sz, parameters

◆ SetPercentageParticlesConverged()

virtual void itk::ParticleSwarmOptimizerBase::SetPercentageParticlesConverged ( double _arg )

virtual

Set parameters convergence tolerance using the same value for all, sz, parameters

◆ SetPrintSwarm()

virtual void itk::ParticleSwarmOptimizerBase::SetPrintSwarm ( bool _arg )

virtual

Indicate whether or not to output the swarm information when printing an object. By default this option is turned off as it generates too much information.

◆ SetSeed()

virtual void itk::ParticleSwarmOptimizerBase::SetSeed ( RandomVariateGeneratorType::IntegerType _arg )

virtual

Set the random number seed for the swarm. Use this method to produce repeatable results, typically, for testing.

◆ SetUseSeed()

virtual void itk::ParticleSwarmOptimizerBase::SetUseSeed ( bool _arg )

virtual

Use a specific seed to initialize the random number generator. If On, use m_Seed to seed the random number generator. Default is Off.

◆ StartOptimization()

void itk::ParticleSwarmOptimizerBase::StartOptimization ( )

overridevirtual

Start optimization.

Reimplemented from itk::Optimizer.

◆ UpdateSwarm()

virtual void itk::ParticleSwarmOptimizerBase::UpdateSwarm ( )

protectedpure virtual

Implement your update rule in this function.

Implemented in itk::InitializationBiasedParticleSwarmOptimizer, and itk::ParticleSwarmOptimizer.

◆ UseSeedOn()

virtual void itk::ParticleSwarmOptimizerBase::UseSeedOn ( )

virtual

Use a specific seed to initialize the random number generator. If On, use m_Seed to seed the random number generator. Default is Off.

◆ ValidateSettings()

virtual void itk::ParticleSwarmOptimizerBase::ValidateSettings ( )

protectedvirtual

Member Data Documentation

◆ m_FunctionBestValue

CostFunctionType::MeasureType itk::ParticleSwarmOptimizerBase::m_FunctionBestValue { 0 }

protected

Definition at line 255 of file itkParticleSwarmOptimizerBase.h.

◆ m_FunctionBestValueMemory

std::vector<MeasureType> itk::ParticleSwarmOptimizerBase::m_FunctionBestValueMemory {}

protected

Definition at line 256 of file itkParticleSwarmOptimizerBase.h.

◆ m_FunctionConvergenceTolerance

CostFunctionType::MeasureType itk::ParticleSwarmOptimizerBase::m_FunctionConvergenceTolerance {}

protected

Definition at line 253 of file itkParticleSwarmOptimizerBase.h.

◆ m_InitializeNormalDistribution

bool itk::ParticleSwarmOptimizerBase::m_InitializeNormalDistribution {}

protected

Definition at line 246 of file itkParticleSwarmOptimizerBase.h.

◆ m_IterationIndex

NumberOfIterationsType itk::ParticleSwarmOptimizerBase::m_IterationIndex { 0 }

protected

Definition at line 258 of file itkParticleSwarmOptimizerBase.h.

◆ m_MaximalNumberOfIterations

NumberOfIterationsType itk::ParticleSwarmOptimizerBase::m_MaximalNumberOfIterations {}

protected

Definition at line 248 of file itkParticleSwarmOptimizerBase.h.

◆ m_NumberOfGenerationsWithMinimalImprovement

NumberOfGenerationsType itk::ParticleSwarmOptimizerBase::m_NumberOfGenerationsWithMinimalImprovement {}

protected

Definition at line 249 of file itkParticleSwarmOptimizerBase.h.

◆ m_NumberOfParticles

NumberOfParticlesType itk::ParticleSwarmOptimizerBase::m_NumberOfParticles {}

protected

Definition at line 247 of file itkParticleSwarmOptimizerBase.h.

◆ m_ParameterBounds

ParameterBoundsType itk::ParticleSwarmOptimizerBase::m_ParameterBounds {}

protected

Definition at line 250 of file itkParticleSwarmOptimizerBase.h.

◆ m_ParametersBestValue

ParametersType itk::ParticleSwarmOptimizerBase::m_ParametersBestValue {}

protected

Definition at line 257 of file itkParticleSwarmOptimizerBase.h.

◆ m_ParametersConvergenceTolerance

ParametersType itk::ParticleSwarmOptimizerBase::m_ParametersConvergenceTolerance {}

protected

Definition at line 251 of file itkParticleSwarmOptimizerBase.h.

◆ m_Particles

std::vector<ParticleData> itk::ParticleSwarmOptimizerBase::m_Particles {}

protected

Definition at line 254 of file itkParticleSwarmOptimizerBase.h.

◆ m_PercentageParticlesConverged

double itk::ParticleSwarmOptimizerBase::m_PercentageParticlesConverged {}

protected

Definition at line 252 of file itkParticleSwarmOptimizerBase.h.

◆ m_PrintSwarm

bool itk::ParticleSwarmOptimizerBase::m_PrintSwarm {}

protected

Definition at line 244 of file itkParticleSwarmOptimizerBase.h.

◆ m_Seed

RandomVariateGeneratorType::IntegerType itk::ParticleSwarmOptimizerBase::m_Seed {}

protected

Definition at line 259 of file itkParticleSwarmOptimizerBase.h.

◆ m_StopConditionDescription

std::ostringstream itk::ParticleSwarmOptimizerBase::m_StopConditionDescription {}

protected

Definition at line 245 of file itkParticleSwarmOptimizerBase.h.

◆ m_UseSeed

bool itk::ParticleSwarmOptimizerBase::m_UseSeed {}

protected

Definition at line 260 of file itkParticleSwarmOptimizerBase.h.

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

itkParticleSwarmOptimizerBase.h

Detailed Description

Classes

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Additional Inherited Members

Member Typedef Documentation

◆ ConstPointer

◆ MeasureType

◆ NumberOfGenerationsType

◆ NumberOfIterationsType

◆ NumberOfParticlesType

◆ ParameterBoundsType

◆ Pointer

◆ RandomVariateGeneratorType

◆ Self

◆ Superclass

◆ SwarmType

◆ ValueType

Constructor & Destructor Documentation

◆ ParticleSwarmOptimizerBase()

◆ ~ParticleSwarmOptimizerBase()

Member Function Documentation

◆ ClearSwarm()

◆ FileInitialization()

◆ GetFunctionConvergenceTolerance()

◆ GetInitializeNormalDistribution()

◆ GetMaximalNumberOfIterations()

◆ GetNameOfClass()

◆ GetNumberOfGenerationsWithMinimalImprovement()

◆ GetNumberOfParticles()

◆ GetParameterBounds()

◆ GetParametersConvergenceTolerance()

◆ GetPercentageParticlesConverged()

◆ GetPrintSwarm()

◆ GetSeed()

◆ GetStopConditionDescription()

◆ GetUseSeed()

◆ GetValue()

◆ Initialize()

◆ InitializeNormalDistributionOn()

◆ PrintParamtersType()

◆ PrintSelf()

◆ PrintSwarm()

◆ PrintSwarmOn()

◆ RandomInitialization()

◆ SetFunctionConvergenceTolerance()

◆ SetInitializeNormalDistribution()

◆ SetInitialSwarm()

◆ SetMaximalNumberOfIterations()

◆ SetNumberOfGenerationsWithMinimalImprovement()

◆ SetNumberOfParticles()

◆ SetParameterBounds() [1/2]

◆ SetParameterBounds() [2/2]

◆ SetParametersConvergenceTolerance() [1/2]

◆ SetParametersConvergenceTolerance() [2/2]

◆ SetPercentageParticlesConverged()

◆ SetPrintSwarm()

◆ SetSeed()

◆ SetUseSeed()

◆ StartOptimization()

◆ UpdateSwarm()

◆ UseSeedOn()

◆ ValidateSettings()

Member Data Documentation

◆ m_FunctionBestValue

◆ m_FunctionBestValueMemory

◆ m_FunctionConvergenceTolerance

◆ m_InitializeNormalDistribution

◆ m_IterationIndex

◆ m_MaximalNumberOfIterations

◆ m_NumberOfGenerationsWithMinimalImprovement

◆ m_NumberOfParticles

◆ m_ParameterBounds

◆ m_ParametersBestValue

◆ m_ParametersConvergenceTolerance

◆ m_Particles

◆ m_PercentageParticlesConverged

◆ m_PrintSwarm