ITK  4.8.0
Insight Segmentation and Registration Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Protected Attributes | Private Member Functions | Private Attributes | List of all members
itk::SPSAOptimizer Class Reference
Optimizers | Module ITKOptimizers

#include <itkSPSAOptimizer.h>

+ Inheritance diagram for itk::SPSAOptimizer:
+ Collaboration diagram for itk::SPSAOptimizer:

Detailed Description

An optimizer based on simultaneous perturbation...

This optimizer is an implementation of the Simultaneous Perturbation Stochastic Approximation method, described in:

Definition at line 44 of file itkSPSAOptimizer.h.

Public Types

typedef SmartPointer< const Self > ConstPointer
 
typedef SmartPointer< Self > Pointer
 
typedef SPSAOptimizer Self
 
enum  StopConditionType {
  Unknown,
  MaximumNumberOfIterations,
  BelowTolerance,
  MetricError
}
 
typedef
SingleValuedNonLinearOptimizer 		Superclass
 
- Public Types inherited from itk::SingleValuedNonLinearOptimizer
typedef SmartPointer< const Self > ConstPointer
 
typedef CostFunctionType::Pointer CostFunctionPointer
 
typedef SingleValuedCostFunction CostFunctionType
 
typedef
CostFunctionType::DerivativeType 		DerivativeType
 
typedef
CostFunctionType::MeasureType 		MeasureType
 
typedef Superclass::ParametersType ParametersType
 
typedef SmartPointer< Self > Pointer
 
typedef
SingleValuedNonLinearOptimizer 		Self
 
typedef NonLinearOptimizer Superclass
 
- Public Types inherited from itk::NonLinearOptimizer
typedef SmartPointer< const Self > ConstPointer
 
typedef Superclass::ParametersType ParametersType
 
typedef SmartPointer< Self > Pointer
 
typedef Superclass::ScalesType ScalesType
 
typedef NonLinearOptimizer Self
 
typedef Optimizer Superclass
 
- Public Types inherited from itk::Optimizer
typedef SmartPointer< const Self > ConstPointer
 
typedef OptimizerParameters
< double > 		ParametersType
 
typedef SmartPointer< Self > Pointer
 
typedef Array< double > ScalesType
 
typedef Optimizer Self
 
typedef Object Superclass
 
- Public Types inherited from itk::Object
typedef SmartPointer< const Self > ConstPointer
 
typedef SmartPointer< Self > Pointer
 
typedef Object Self
 
typedef LightObject Superclass
 
- Public Types inherited from itk::LightObject
typedef SmartPointer< const Self > ConstPointer
 
typedef SmartPointer< Self > Pointer
 
typedef LightObject Self
 

Public Member Functions

virtual void AdvanceOneStep ()
 
virtual ::itk::LightObject::Pointer CreateAnother () const
 
virtual SizeValueType GetCurrentIteration () const
 
virtual const DerivativeType & GetGradient () const
 
virtual double GetGradientMagnitude () const
 
virtual double GetLearningRate () const
 
virtual const char * GetNameOfClass () const
 
virtual double GetStateOfConvergence () const
 
virtual StopConditionType GetStopCondition () const
 
virtual const std::string GetStopConditionDescription () const override
 
virtual MeasureType GetValue () const
 
virtual MeasureType GetValue (const ParametersType &parameters) const
 
virtual void GuessParameters (SizeValueType numberOfGradientEstimates, double initialStepSize)
 
void ResumeOptimization ()
 
virtual void StartOptimization (void) override
 
void StopOptimization ()
 
virtual void SetSa (double _arg)
 
virtual double GetSa () const
 
void Seta (double a)
 
double Geta ()
 
virtual void SetSc (double _arg)
 
virtual double GetSc () const
 
void Setc (double c)
 
double Getc ()
 
virtual void SetA (double _arg)
 
virtual double GetA () const
 
virtual void SetAlpha (double _arg)
 
virtual double GetAlpha () const
 
virtual void SetGamma (double _arg)
 
virtual double GetGamma () const
 
virtual 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 void SetNumberOfPerturbations (SizeValueType _arg)
 
virtual SizeValueType GetNumberOfPerturbations () const
 
virtual void SetStateOfConvergenceDecayRate (double _arg)
 
virtual double GetStateOfConvergenceDecayRate () const
 
virtual void SetMinimumNumberOfIterations (SizeValueType _arg)
 
virtual SizeValueType GetMinimumNumberOfIterations () const
 
virtual void SetMaximumNumberOfIterations (SizeValueType _arg)
 
virtual SizeValueType GetMaximumNumberOfIterations () const
 
virtual void SetTolerance (double _arg)
 
virtual double GetTolerance () const
 
- Public Member Functions inherited from itk::SingleValuedNonLinearOptimizer
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 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 *)
 
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
 
virtual void Register () const override
 
void RemoveAllObservers ()
 
void RemoveObserver (unsigned long tag)
 
void SetDebug (bool debugFlag) const
 
void SetMetaDataDictionary (const MetaDataDictionary &rhs)
 
virtual void SetReferenceCount (int) override
 
virtual void UnRegister () const noexceptoverride
 
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::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 Member Functions

virtual double Compute_a (SizeValueType k) const
 
virtual double Compute_c (SizeValueType k) const
 
virtual void ComputeGradient (const ParametersType &parameters, DerivativeType &gradient)
 
virtual void GenerateDelta (const unsigned int spaceDimension)
 
virtual void PrintSelf (std::ostream &os, Indent indent) const override
 
 SPSAOptimizer ()
 
virtual ~SPSAOptimizer ()
 
- Protected Member Functions inherited from itk::SingleValuedNonLinearOptimizer
 SingleValuedNonLinearOptimizer ()
 
virtual ~SingleValuedNonLinearOptimizer ()
 
- Protected Member Functions inherited from itk::NonLinearOptimizer
 NonLinearOptimizer ()
 
virtual ~NonLinearOptimizer ()
 
- Protected Member Functions inherited from itk::Optimizer
 Optimizer ()
 
virtual void SetCurrentPosition (const ParametersType &param)
 
virtual ~Optimizer ()
 
- Protected Member Functions inherited from itk::Object
 Object ()
 
bool PrintObservers (std::ostream &os, Indent indent) const
 
virtual void SetTimeStamp (const TimeStamp &time)
 
virtual ~Object ()
 
- 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

SizeValueType m_CurrentIteration
 
DerivativeType m_Delta
 
Statistics::MersenneTwisterRandomVariateGenerator::Pointer m_Generator
 
DerivativeType m_Gradient
 
double m_LearningRate
 
double m_StateOfConvergence
 
bool m_Stop
 
StopConditionType m_StopCondition
 
- Protected Attributes inherited from itk::SingleValuedNonLinearOptimizer
CostFunctionPointer m_CostFunction
 
- Protected Attributes inherited from itk::Optimizer
ParametersType m_CurrentPosition
 
bool m_ScalesInitialized
 
- Protected Attributes inherited from itk::LightObject
AtomicInt< int > m_ReferenceCount
 

Private Member Functions

void operator= (const Self &)
 
 SPSAOptimizer (const Self &)
 

Private Attributes

double m_A
 
double m_Alpha
 
double m_Gamma
 
double m_GradientMagnitude
 
bool m_Maximize
 
SizeValueType m_MaximumNumberOfIterations
 
SizeValueType m_MinimumNumberOfIterations
 
SizeValueType m_NumberOfPerturbations
 
double m_Sa
 
double m_Sc
 
double m_StateOfConvergenceDecayRate
 
double m_Tolerance
 

Member Typedef Documentation

typedef SmartPointer< const Self > itk::SPSAOptimizer::ConstPointer

Definition at line 53 of file itkSPSAOptimizer.h.

typedef SmartPointer< Self > itk::SPSAOptimizer::Pointer

Definition at line 52 of file itkSPSAOptimizer.h.

typedef SPSAOptimizer itk::SPSAOptimizer::Self

Standard class typedefs.

Definition at line 50 of file itkSPSAOptimizer.h.

typedef SingleValuedNonLinearOptimizer itk::SPSAOptimizer::Superclass

Definition at line 51 of file itkSPSAOptimizer.h.

Member Enumeration Documentation

enum itk::SPSAOptimizer::StopConditionType

Codes of stopping conditions

Enumerator
Unknown 
MaximumNumberOfIterations 
BelowTolerance 
MetricError 

Definition at line 62 of file itkSPSAOptimizer.h.

Constructor & Destructor Documentation

itk::SPSAOptimizer::SPSAOptimizer ( )
protected
virtual itk::SPSAOptimizer::~SPSAOptimizer ( )
inlineprotectedvirtual

Definition at line 214 of file itkSPSAOptimizer.h.

itk::SPSAOptimizer::SPSAOptimizer ( const Self &  )
private

Member Function Documentation

virtual void itk::SPSAOptimizer::AdvanceOneStep ( )
virtual

Advance one step following the gradient direction.

virtual double itk::SPSAOptimizer::Compute_a ( SizeValueType  k) const
protectedvirtual

Method to compute the learning rate at iteration k (a_k).

virtual double itk::SPSAOptimizer::Compute_c ( SizeValueType  k) const
protectedvirtual

Method to compute the gain factor for the perturbation at iteration k (c_k).

virtual void itk::SPSAOptimizer::ComputeGradient ( const ParametersType &  parameters,
DerivativeType &  gradient 
)
protectedvirtual

Compute the gradient at a position. m_NumberOfPerturbations are used, and scales are taken into account.

virtual::itk::LightObject::Pointer itk::SPSAOptimizer::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::SingleValuedNonLinearOptimizer.

virtual void itk::SPSAOptimizer::GenerateDelta ( const unsigned int  spaceDimension)
protectedvirtual

Method to generate a perturbation vector. Takes scales into account.

double itk::SPSAOptimizer::Geta ( )
inline

Set/Get a.

Definition at line 126 of file itkSPSAOptimizer.h.

virtual double itk::SPSAOptimizer::GetA ( ) const
virtual

Set/Get A.

virtual double itk::SPSAOptimizer::GetAlpha ( ) const
virtual

Set/Get alpha.

double itk::SPSAOptimizer::Getc ( )
inline

Set/Get c.

Definition at line 134 of file itkSPSAOptimizer.h.

virtual SizeValueType itk::SPSAOptimizer::GetCurrentIteration ( ) const
virtual

Get the current iteration number.

virtual double itk::SPSAOptimizer::GetGamma ( ) const
virtual

Set/Get gamma.

virtual const DerivativeType& itk::SPSAOptimizer::GetGradient ( ) const
virtual

Get the latest computed gradient

virtual double itk::SPSAOptimizer::GetGradientMagnitude ( ) const
virtual

Get the GradientMagnitude of the latest computed gradient

virtual double itk::SPSAOptimizer::GetLearningRate ( ) const
virtual

Get the current LearningRate (a_k)

virtual bool itk::SPSAOptimizer::GetMaximize ( ) const
virtual

Methods to configure the cost function.

virtual SizeValueType itk::SPSAOptimizer::GetMaximumNumberOfIterations ( ) const
virtual

Set/Get the maximum number of iterations.

bool itk::SPSAOptimizer::GetMinimize ( ) const
inline

Methods to configure the cost function.

Definition at line 156 of file itkSPSAOptimizer.h.

virtual SizeValueType itk::SPSAOptimizer::GetMinimumNumberOfIterations ( ) const
virtual

Set/Get the minimum number of iterations

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

Run-time type information (and related methods).

Reimplemented from itk::SingleValuedNonLinearOptimizer.

virtual SizeValueType itk::SPSAOptimizer::GetNumberOfPerturbations ( ) const
virtual

Set/Get the number of perturbation used to construct a gradient estimate g_k. q = NumberOfPerturbations g_k = 1/q sum_{j=1..q} g^(j)_k

virtual double itk::SPSAOptimizer::GetSa ( ) const
virtual

Set/Get a.

virtual double itk::SPSAOptimizer::GetSc ( ) const
virtual

Set/Get c.

virtual double itk::SPSAOptimizer::GetStateOfConvergence ( ) const
virtual

Get the state of convergence in the last iteration. When the StateOfConvergence is lower than the Tolerance, and the minimum number of iterations has been performed, the optimization stops.

The state of convergence (SOC) is initialized with 0.0 and updated after each iteration as follows: SOC *= SOCDecayRate SOC += a_k * GradientMagnitude

virtual double itk::SPSAOptimizer::GetStateOfConvergenceDecayRate ( ) const
virtual

Set/Get StateOfConvergenceDecayRate (number between 0 and 1).

virtual StopConditionType itk::SPSAOptimizer::GetStopCondition ( ) const
virtual

Get Stop condition.

virtual const std::string itk::SPSAOptimizer::GetStopConditionDescription ( ) const
overridevirtual

Get the reason for termination

Reimplemented from itk::Optimizer.

virtual double itk::SPSAOptimizer::GetTolerance ( ) const
virtual

Set/Get Tolerance

virtual MeasureType itk::SPSAOptimizer::GetValue ( ) const
virtual

Get the cost function value at the current position.

virtual MeasureType itk::SPSAOptimizer::GetValue ( const ParametersType &  parameters) const
virtual

Get the cost function value at any position

virtual void itk::SPSAOptimizer::GuessParameters ( SizeValueType  numberOfGradientEstimates,
double  initialStepSize 
)
virtual

Guess the parameters a and A. This function needs the number of GradientEstimates used for estimating a and A and and the expected initial step size (where step size is defined as the maximum of the absolute values of the parameter update). Make sure you set c, Alpha, Gamma, the MaximumNumberOfIterations, the Scales, and the the InitialPosition before calling this method.

Described in: Spall, J.C. (1998), "Implementation of the Simultaneous Perturbation Algorithm for Stochastic Optimization", IEEE Trans. Aerosp. Electron. Syst. 34(3), 817-823.

virtual void itk::SPSAOptimizer::MaximizeOff ( )
virtual

Methods to configure the cost function.

virtual void itk::SPSAOptimizer::MaximizeOn ( )
virtual

Methods to configure the cost function.

void itk::SPSAOptimizer::MinimizeOff ( )
inline

Methods to configure the cost function.

Definition at line 162 of file itkSPSAOptimizer.h.

void itk::SPSAOptimizer::MinimizeOn ( )
inline

Methods to configure the cost function.

Definition at line 160 of file itkSPSAOptimizer.h.

static Pointer itk::SPSAOptimizer::New ( )
static

Method for creation through the object factory.

void itk::SPSAOptimizer::operator= ( const Self &  )
private
virtual void itk::SPSAOptimizer::PrintSelf ( std::ostream &  os,
Indent  indent 
) const
overrideprotectedvirtual

PrintSelf method.

Reimplemented from itk::SingleValuedNonLinearOptimizer.

void itk::SPSAOptimizer::ResumeOptimization ( )

Resume previously stopped optimization with current parameters

See Also
StopOptimization.
void itk::SPSAOptimizer::Seta ( double  a)
inline

Set/Get a.

Definition at line 125 of file itkSPSAOptimizer.h.

virtual void itk::SPSAOptimizer::SetA ( double  _arg)
virtual

Set/Get A.

virtual void itk::SPSAOptimizer::SetAlpha ( double  _arg)
virtual

Set/Get alpha.

void itk::SPSAOptimizer::Setc ( double  c)
inline

Set/Get c.

Definition at line 133 of file itkSPSAOptimizer.h.

virtual void itk::SPSAOptimizer::SetGamma ( double  _arg)
virtual

Set/Get gamma.

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

Methods to configure the cost function.

virtual void itk::SPSAOptimizer::SetMaximumNumberOfIterations ( SizeValueType  _arg)
virtual

Set/Get the maximum number of iterations.

void itk::SPSAOptimizer::SetMinimize ( bool  v)
inline

Methods to configure the cost function.

Definition at line 158 of file itkSPSAOptimizer.h.

virtual void itk::SPSAOptimizer::SetMinimumNumberOfIterations ( SizeValueType  _arg)
virtual

Set/Get the minimum number of iterations

virtual void itk::SPSAOptimizer::SetNumberOfPerturbations ( SizeValueType  _arg)
virtual

Set/Get the number of perturbation used to construct a gradient estimate g_k. q = NumberOfPerturbations g_k = 1/q sum_{j=1..q} g^(j)_k

virtual void itk::SPSAOptimizer::SetSa ( double  _arg)
virtual

Set/Get a.

virtual void itk::SPSAOptimizer::SetSc ( double  _arg)
virtual

Set/Get c.

virtual void itk::SPSAOptimizer::SetStateOfConvergenceDecayRate ( double  _arg)
virtual

Set/Get StateOfConvergenceDecayRate (number between 0 and 1).

virtual void itk::SPSAOptimizer::SetTolerance ( double  _arg)
virtual

Set/Get Tolerance

virtual void itk::SPSAOptimizer::StartOptimization ( void  )
overridevirtual

Start optimization.

Reimplemented from itk::Optimizer.

void itk::SPSAOptimizer::StopOptimization ( )

Stop optimization.

See Also
ResumeOptimization

Member Data Documentation

double itk::SPSAOptimizer::m_A
private

Definition at line 274 of file itkSPSAOptimizer.h.

double itk::SPSAOptimizer::m_Alpha
private

Definition at line 275 of file itkSPSAOptimizer.h.

SizeValueType itk::SPSAOptimizer::m_CurrentIteration
protected

Definition at line 232 of file itkSPSAOptimizer.h.

DerivativeType itk::SPSAOptimizer::m_Delta
protected

Definition at line 224 of file itkSPSAOptimizer.h.

double itk::SPSAOptimizer::m_Gamma
private

Definition at line 276 of file itkSPSAOptimizer.h.

Statistics::MersenneTwisterRandomVariateGenerator::Pointer itk::SPSAOptimizer::m_Generator
protected

Random number generator

Definition at line 235 of file itkSPSAOptimizer.h.

DerivativeType itk::SPSAOptimizer::m_Gradient
protected

Variables updated during optimization

Definition at line 220 of file itkSPSAOptimizer.h.

double itk::SPSAOptimizer::m_GradientMagnitude
private

Definition at line 268 of file itkSPSAOptimizer.h.

double itk::SPSAOptimizer::m_LearningRate
protected

Definition at line 222 of file itkSPSAOptimizer.h.

bool itk::SPSAOptimizer::m_Maximize
private

Definition at line 267 of file itkSPSAOptimizer.h.

SizeValueType itk::SPSAOptimizer::m_MaximumNumberOfIterations
private

Definition at line 264 of file itkSPSAOptimizer.h.

SizeValueType itk::SPSAOptimizer::m_MinimumNumberOfIterations
private

Settings.

Definition at line 263 of file itkSPSAOptimizer.h.

SizeValueType itk::SPSAOptimizer::m_NumberOfPerturbations
private

Definition at line 269 of file itkSPSAOptimizer.h.

double itk::SPSAOptimizer::m_Sa
private

Parameters, as described by Spall.

Definition at line 272 of file itkSPSAOptimizer.h.

double itk::SPSAOptimizer::m_Sc
private

Definition at line 273 of file itkSPSAOptimizer.h.

double itk::SPSAOptimizer::m_StateOfConvergence
protected

Definition at line 230 of file itkSPSAOptimizer.h.

double itk::SPSAOptimizer::m_StateOfConvergenceDecayRate
private

Definition at line 265 of file itkSPSAOptimizer.h.

bool itk::SPSAOptimizer::m_Stop
protected

Definition at line 226 of file itkSPSAOptimizer.h.

StopConditionType itk::SPSAOptimizer::m_StopCondition
protected

Definition at line 228 of file itkSPSAOptimizer.h.

double itk::SPSAOptimizer::m_Tolerance
private

Definition at line 266 of file itkSPSAOptimizer.h.

The documentation for this class was generated from the following file:
Tarballs of the nightly generated Doxygen documentation are available for the html, xml, and tag file.
Generated on Fri Jul 3 2015 04:26:26 for ITK by   doxygen 1.8.5