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itk::SPSAOptimizer Class Reference
[Optimizers]

An optimizer based on simultaneous perturbation... More...

#include <itkSPSAOptimizer.h>

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List of all members.

Public Types

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 Superclass::ScalesType ScalesType
typedef SPSAOptimizer Self
enum  StopConditionType {
  Unknown,
  MaximumNumberOfIterations,
  BelowTolerance,
  MetricError
}
typedef
SingleValuedNonLinearOptimizer 		Superclass

Public Member Functions

virtual void AdvanceOneStep (void)
virtual LightObject::Pointer CreateAnother () const
virtual void DebugOff () const
virtual void DebugOn () const
virtual void Delete ()
Command * GetCommand (unsigned long tag)
virtual const CostFunctionType * GetCostFunction ()
virtual unsigned long GetCurrentIteration () const
virtual const ParametersType & GetCurrentPosition ()
bool GetDebug () const
virtual const DerivativeType & GetGradient ()
virtual double GetGradientMagnitude () const
virtual const ParametersType & GetInitialPosition ()
virtual double GetLearningRate () const
MetaDataDictionary & GetMetaDataDictionary (void)
const MetaDataDictionary & GetMetaDataDictionary (void) const
virtual unsigned long GetMTime () const
virtual const char * GetNameOfClass () const
virtual int GetReferenceCount () const
virtual const ScalesType & GetScales ()
virtual double GetStateOfConvergence () const
virtual StopConditionType GetStopCondition () const
const std::string GetStopConditionDescription () const
virtual MeasureType GetValue (void) const
virtual MeasureType GetValue (const ParametersType &parameters) const
virtual void GuessParameters (unsigned long numberOfGradientEstimates, double initialStepSize)
bool HasObserver (const EventObject &event) const
void InvokeEvent (const EventObject &)
void InvokeEvent (const EventObject &) const
virtual void Modified () const
void Print (std::ostream &os, Indent indent=0) const
virtual void Register () const
void RemoveAllObservers ()
void RemoveObserver (unsigned long tag)
void ResumeOptimization (void)
virtual void SetCostFunction (CostFunctionType *costFunction)
void SetDebug (bool debugFlag) const
virtual void SetInitialPosition (const ParametersType &param)
void SetMetaDataDictionary (const MetaDataDictionary &rhs)
virtual void SetReferenceCount (int)
void SetScales (const ScalesType &scales)
void StartOptimization (void)
void StopOptimization (void)
virtual void UnRegister () const

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 (unsigned long _arg)
virtual unsigned long GetNumberOfPerturbations () const

virtual void SetStateOfConvergenceDecayRate (double _arg)
virtual double GetStateOfConvergenceDecayRate () const

virtual void SetMinimumNumberOfIterations (unsigned long _arg)
virtual unsigned long GetMinimumNumberOfIterations () const

virtual void SetMaximumNumberOfIterations (unsigned long _arg)
virtual unsigned long GetMaximumNumberOfIterations () const

virtual void SetTolerance (double _arg)
virtual double GetTolerance () const

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

Static Public Member Functions

static void BreakOnError ()
static Pointer New ()

static void SetGlobalWarningDisplay (bool flag)
static bool GetGlobalWarningDisplay ()
static void GlobalWarningDisplayOn ()
static void GlobalWarningDisplayOff ()

Protected Types

typedef int InternalReferenceCountType

Protected Member Functions

virtual double Compute_a (unsigned long k) const
virtual double Compute_c (unsigned long k) const
virtual void ComputeGradient (const ParametersType &parameters, DerivativeType &gradient)
virtual void GenerateDelta (const unsigned int spaceDimension)
bool PrintObservers (std::ostream &os, Indent indent) const
void PrintSelf (std::ostream &os, Indent indent) const
virtual void SetCurrentPosition (const ParametersType &param)
 SPSAOptimizer ()
virtual ~SPSAOptimizer ()

virtual void PrintHeader (std::ostream &os, Indent indent) const
virtual void PrintTrailer (std::ostream &os, Indent indent) const

Protected Attributes

CostFunctionPointer m_CostFunction
unsigned long m_CurrentIteration
ParametersType m_CurrentPosition
DerivativeType m_Delta
Statistics::MersenneTwisterRandomVariateGenerator::Pointer m_Generator
DerivativeType m_Gradient
double m_LearningRate
InternalReferenceCountType m_ReferenceCount
SimpleFastMutexLock m_ReferenceCountLock
bool m_ScalesInitialized
double m_StateOfConvergence
bool m_Stop
StopConditionType m_StopCondition

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 43 of file itkSPSAOptimizer.h.

Member Typedef Documentation

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

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Definition at line 52 of file itkSPSAOptimizer.h.

typedef CostFunctionType::Pointer itk::SingleValuedNonLinearOptimizer::CostFunctionPointer [inherited]

Reimplemented in itk::FRPROptimizer, itk::OnePlusOneEvolutionaryOptimizer, itk::PowellOptimizer, and itk::RegularStepGradientDescentOptimizer.

Definition at line 56 of file itkSingleValuedNonLinearOptimizer.h.

typedef SingleValuedCostFunction itk::SingleValuedNonLinearOptimizer::CostFunctionType [inherited]

Type of the Cost Function

Reimplemented in itk::FRPROptimizer, itk::OnePlusOneEvolutionaryOptimizer, itk::PowellOptimizer, and itk::RegularStepGradientDescentOptimizer.

Definition at line 55 of file itkSingleValuedNonLinearOptimizer.h.

typedef CostFunctionType::DerivativeType itk::SingleValuedNonLinearOptimizer::DerivativeType [inherited]

Derivative type. It defines a type used to return the cost function derivative.

Definition at line 64 of file itkSingleValuedNonLinearOptimizer.h.

typedef int itk::LightObject::InternalReferenceCountType [protected, inherited]

Define the type of the reference count according to the target. This allows the use of atomic operations

Definition at line 139 of file itkLightObject.h.

typedef CostFunctionType::MeasureType itk::SingleValuedNonLinearOptimizer::MeasureType [inherited]

Measure type. It defines a type used to return the cost function value.

Definition at line 60 of file itkSingleValuedNonLinearOptimizer.h.

typedef Superclass::ParametersType itk::SingleValuedNonLinearOptimizer::ParametersType [inherited]

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

Reimplemented from itk::NonLinearOptimizer.

Reimplemented in itk::AmoebaOptimizer, itk::FRPROptimizer, itk::PowellOptimizer, and itk::QuaternionRigidTransformGradientDescentOptimizer.

Definition at line 48 of file itkSingleValuedNonLinearOptimizer.h.

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

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Definition at line 51 of file itkSPSAOptimizer.h.

typedef Superclass::ScalesType itk::NonLinearOptimizer::ScalesType [inherited]

Scale type. This array defines scale to be applied to parameters before being evaluated in the cost function. This allows to map to a more convenient space. In particular this is used to normalize parameter spaces in which some parameters have a different dynamic range.

Reimplemented from itk::Optimizer.

Definition at line 52 of file itkNonLinearOptimizer.h.

typedef SPSAOptimizer itk::SPSAOptimizer::Self

Standard class typedefs.

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Definition at line 49 of file itkSPSAOptimizer.h.

typedef SingleValuedNonLinearOptimizer itk::SPSAOptimizer::Superclass

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Definition at line 50 of file itkSPSAOptimizer.h.

Member Enumeration Documentation

enum itk::SPSAOptimizer::StopConditionType

Codes of stopping conditions

Enumerator:
Unknown 
MaximumNumberOfIterations 
BelowTolerance 
MetricError 

Definition at line 61 of file itkSPSAOptimizer.h.

Constructor & Destructor Documentation

itk::SPSAOptimizer::SPSAOptimizer (  )  [protected]
virtual itk::SPSAOptimizer::~SPSAOptimizer (  )  [inline, protected, virtual]

Definition at line 213 of file itkSPSAOptimizer.h.

Member Function Documentation

unsigned long itk::Object::AddObserver ( const EventObject &  event,
Command *   
) [inherited]

Allow people to add/remove/invoke observers (callbacks) to any ITK object. This is an implementation of the subject/observer design pattern. An observer is added by specifying an event to respond to and an itk::Command to execute. It returns an unsigned long tag which can be used later to remove the event or retrieve the command. The memory for the Command becomes the responsibility of this object, so don't pass the same instance of a command to two different objects

unsigned long itk::Object::AddObserver ( const EventObject &  event,
Command *   
) const [inherited]

Allow people to add/remove/invoke observers (callbacks) to any ITK object. This is an implementation of the subject/observer design pattern. An observer is added by specifying an event to respond to and an itk::Command to execute. It returns an unsigned long tag which can be used later to remove the event or retrieve the command. The memory for the Command becomes the responsibility of this object, so don't pass the same instance of a command to two different objects

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

Advance one step following the gradient direction.

static void itk::LightObject::BreakOnError (  )  [static, inherited]

This method is called when itkExceptionMacro executes. It allows the debugger to break on error.

virtual double itk::SPSAOptimizer::Compute_a ( unsigned long  k  )  const [protected, virtual]

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

virtual double itk::SPSAOptimizer::Compute_c ( unsigned long  k  )  const [protected, virtual]

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

virtual void itk::SPSAOptimizer::ComputeGradient ( const ParametersType &  parameters,
DerivativeType &  gradient 
) [protected, virtual]

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

virtual LightObject::Pointer itk::Object::CreateAnother (  )  const [virtual, inherited]

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::LightObject.

Reimplemented in itk::BSplineDeformableTransform< TScalarType, NDimensions, VSplineOrder >, itk::CreateObjectFunction< T >, itk::TransformFactoryBase, itk::AnalyzeImageIOFactory, itk::BioRadImageIOFactory, itk::BMPImageIOFactory, itk::Brains2MaskImageIOFactory, itk::DICOMImageIO2Factory, itk::DicomImageIOFactory, itk::GDCMImageIOFactory, itk::GE4ImageIOFactory, itk::GE5ImageIOFactory, itk::GEAdwImageIOFactory, itk::GiplImageIOFactory, itk::JPEGImageIOFactory, itk::LSMImageIOFactory, itk::MetaImageIOFactory, itk::NiftiImageIOFactory, itk::NrrdImageIOFactory, itk::PNGImageIOFactory, itk::RawImageIOFactory< TPixel, VImageDimension >, itk::SiemensVisionImageIOFactory, itk::StimulateImageIOFactory, itk::TIFFImageIOFactory, itk::VTKImageIOFactory, itk::Bruker2DSEQImageIOFactory, itk::MatlabTransformIOFactory, itk::MINC2ImageIOFactory, itk::MRCImageIOFactory, itk::PhilipsRECImageIOFactory, itk::TxtTransformIOFactory, itk::VoxBoCUBImageIOFactory, itk::VTKImageIO2Factory, and itk::SpatialObjectFactoryBase.

virtual void itk::Object::DebugOff (  )  const [virtual, inherited]

Turn debugging output off.

virtual void itk::Object::DebugOn (  )  const [virtual, inherited]

Turn debugging output on.

virtual void itk::LightObject::Delete (  )  [virtual, inherited]

Delete an itk object. This method should always be used to delete an object when the new operator was used to create it. Using the C delete method will not work with reference counting.

virtual void itk::SPSAOptimizer::GenerateDelta ( const unsigned int  spaceDimension  )  [protected, virtual]

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

double itk::SPSAOptimizer::Geta (  )  [inline]

Set/Get a.

Definition at line 124 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 132 of file itkSPSAOptimizer.h.

Command* itk::Object::GetCommand ( unsigned long  tag  )  [inherited]

Get the command associated with the given tag. NOTE: This returns a pointer to a Command, but it is safe to asign this to a Command::Pointer. Since Command inherits from LightObject, at this point in the code, only a pointer or a reference to the Command can be used.

virtual const CostFunctionType* itk::SingleValuedNonLinearOptimizer::GetCostFunction (  )  [virtual, inherited]

Get the cost function.

virtual unsigned long itk::SPSAOptimizer::GetCurrentIteration (  )  const [virtual]

Get the current iteration number.

virtual const ParametersType& itk::Optimizer::GetCurrentPosition (  )  [virtual, inherited]

Get current position of the optimization.

bool itk::Object::GetDebug (  )  const [inherited]

Get the value of the debug flag.

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

Set/Get gamma.

static bool itk::Object::GetGlobalWarningDisplay (  )  [static, inherited]

This is a global flag that controls whether any debug, warning or error messages are displayed.

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

Get the latest computed gradient

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

Get the GradientMagnitude of the latest computed gradient

virtual const ParametersType& itk::Optimizer::GetInitialPosition (  )  [virtual, inherited]

Get the position to initialize the optimization.

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 unsigned long itk::SPSAOptimizer::GetMaximumNumberOfIterations (  )  const [virtual]

Set/Get the maximum number of iterations.

MetaDataDictionary& itk::Object::GetMetaDataDictionary ( void   )  [inherited]
Returns:
A reference to this objects MetaDataDictionary.
Warning:
This reference may be changed.
const MetaDataDictionary& itk::Object::GetMetaDataDictionary ( void   )  const [inherited]
Returns:
A constant reference to this objects MetaDataDictionary.
bool itk::SPSAOptimizer::GetMinimize (  )  const [inline]

Methods to configure the cost function.

Definition at line 154 of file itkSPSAOptimizer.h.

virtual unsigned long itk::SPSAOptimizer::GetMinimumNumberOfIterations (  )  const [virtual]

Set/Get the minimum number of iterations

virtual unsigned long itk::Object::GetMTime (  )  const [virtual, inherited]

Return this objects modified time.

Reimplemented in itk::ImageRegistrationMethod< TFixedImage, TMovingImage >, itk::ImageToSpatialObjectRegistrationMethod< TFixedImage, TMovingSpatialObject >, itk::MultiResolutionImageRegistrationMethod< TFixedImage, TMovingImage >, itk::PointSetToImageRegistrationMethod< TFixedPointSet, TMovingImage >, itk::PointSetToPointSetRegistrationMethod< TFixedPointSet, TMovingPointSet >, itk::DeformationFieldSource< TOutputImage >, itk::InverseDeformationFieldImageFilter< TInputImage, TOutputImage >, itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::VectorResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::BoundingBox< TPointIdentifier, VPointDimension, TCoordRep, TPointsContainer >, itk::ImageAdaptor< TImage, TAccessor >, itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::TransformToDeformationFieldSource< TOutputImage, TTransformPrecisionType >, itk::ImageSpatialObject< TDimension, TPixelType >, itk::MeshSpatialObject< TMesh >, itk::SceneSpatialObject< TSpaceDimension >, itk::SpatialObject< TDimension >, itk::ImageAdaptor< TImage, Accessor::AsinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::SqrtPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::TanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::CosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::VectorToRGBPixelAccessor< TImage::PixelType::ValueType > >, itk::ImageAdaptor< TImage, Accessor::RGBToVectorPixelAccessor< TImage::PixelType::ComponentType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToModulusPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AbsPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::SinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::LogPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToPhasePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< VectorImage< TPixelType, Dimension >, Accessor::VectorImageToImagePixelAccessor< TPixelType > >, itk::ImageAdaptor< TImage, Accessor::Log10PixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AtanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToRealPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToImaginaryPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ExpNegativePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ExpPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AcosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::RGBToLuminancePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AddPixelAccessor< TImage::PixelType > >, itk::ImageSpatialObject< TDimension, unsigned char >, itk::SpatialObject< 3 >, and itk::SpatialObject< ::itk::GetMeshDimension< TMesh >::PointDimension >.

Referenced by itk::SpatialObject< ::itk::GetMeshDimension< TMesh >::PointDimension >::GetObjectMTime().

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

Run-time type information (and related methods).

Reimplemented from itk::SingleValuedNonLinearOptimizer.

virtual unsigned long 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 int itk::LightObject::GetReferenceCount (  )  const [inline, virtual, inherited]

Gets the reference count on this object.

Definition at line 106 of file itkLightObject.h.

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

Set/Get a.

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

Set/Get c.

virtual const ScalesType& itk::Optimizer::GetScales (  )  [virtual, inherited]

Get current parameters scaling.

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.

const std::string itk::SPSAOptimizer::GetStopConditionDescription (  )  const [virtual]

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 ParametersType &  parameters  )  const [virtual]

Get the cost function value at any position

Reimplemented from itk::SingleValuedNonLinearOptimizer.

virtual MeasureType itk::SPSAOptimizer::GetValue ( void   )  const [virtual]

Get the cost function value at the current position.

static void itk::Object::GlobalWarningDisplayOff (  )  [inline, static, inherited]

This is a global flag that controls whether any debug, warning or error messages are displayed.

Definition at line 100 of file itkObject.h.

References itk::Object::SetGlobalWarningDisplay().

static void itk::Object::GlobalWarningDisplayOn (  )  [inline, static, inherited]

This is a global flag that controls whether any debug, warning or error messages are displayed.

Definition at line 98 of file itkObject.h.

References itk::Object::SetGlobalWarningDisplay().

virtual void itk::SPSAOptimizer::GuessParameters ( unsigned long  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.

bool itk::Object::HasObserver ( const EventObject &  event  )  const [inherited]

Return true if an observer is registered for this event.

void itk::Object::InvokeEvent ( const EventObject &   )  [inherited]

Call Execute on all the Commands observing this event id.

void itk::Object::InvokeEvent ( const EventObject &   )  const [inherited]

Call Execute on all the Commands observing this event id. The actions triggered by this call doesn't modify this object.

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 160 of file itkSPSAOptimizer.h.

void itk::SPSAOptimizer::MinimizeOn (  )  [inline]

Methods to configure the cost function.

Definition at line 158 of file itkSPSAOptimizer.h.

virtual void itk::Object::Modified (  )  const [virtual, inherited]

Update the modification time for this object. Many filters rely on the modification time to determine if they need to recompute their data.

Reimplemented in itk::NormalizeImageFilter< TInputImage, TOutputImage >, itk::ImageAdaptor< TImage, TAccessor >, itk::MiniPipelineSeparableImageFilter< TInputImage, TOutputImage, TFilter >, itk::GrayscaleDilateImageFilter< TInputImage, TOutputImage, TKernel >, itk::GrayscaleErodeImageFilter< TInputImage, TOutputImage, TKernel >, itk::GrayscaleMorphologicalClosingImageFilter< TInputImage, TOutputImage, TKernel >, itk::GrayscaleMorphologicalOpeningImageFilter< TInputImage, TOutputImage, TKernel >, itk::MorphologicalGradientImageFilter< TInputImage, TOutputImage, TKernel >, itk::ImageAdaptor< TImage, Accessor::AsinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::SqrtPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::TanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::CosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::VectorToRGBPixelAccessor< TImage::PixelType::ValueType > >, itk::ImageAdaptor< TImage, Accessor::RGBToVectorPixelAccessor< TImage::PixelType::ComponentType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToModulusPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AbsPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::SinPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::LogPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToPhasePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< VectorImage< TPixelType, Dimension >, Accessor::VectorImageToImagePixelAccessor< TPixelType > >, itk::ImageAdaptor< TImage, Accessor::Log10PixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AtanPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToRealPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ComplexToImaginaryPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ExpNegativePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::ExpPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AcosPixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::RGBToLuminancePixelAccessor< TImage::PixelType, TOutputPixelType > >, itk::ImageAdaptor< TImage, Accessor::AddPixelAccessor< TImage::PixelType > >, and itk::MiniPipelineSeparableImageFilter< TInputImage, TOutputImage, RankImageFilter< TInputImage, TInputImage, FlatStructuringElement< ::itk::GetImageDimension< TInputImage >::ImageDimension > > >.

Referenced by itk::NarrowBandImageFilterBase< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::InsertNarrowBandNode(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetCenter(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetMatrix(), itk::NarrowBandImageFilterBase< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBand(), itk::NarrowBandImageFilterBase< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBandInnerRadius(), itk::NarrowBandImageFilterBase< TInputImage, Image< TOutputPixelType,::itk::GetImageDimension< TInputImage >::ImageDimension > >::SetNarrowBandTotalRadius(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetOffset(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetRealThresholds(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetThresholds(), itk::Statistics::GoodnessOfFitFunctionBase< TInputHistogram >::SetTotalObservedScale(), and itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetTranslation().

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

Method for creation through the object factory.

Reimplemented from itk::SingleValuedNonLinearOptimizer.

void itk::LightObject::Print ( std::ostream &  os,
Indent  indent = 0 
) const [inherited]

Cause the object to print itself out.

Referenced by itk::WeakPointer< ProcessObject >::Print().

virtual void itk::LightObject::PrintHeader ( std::ostream &  os,
Indent  indent 
) const [protected, virtual, inherited]

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.

bool itk::Object::PrintObservers ( std::ostream &  os,
Indent  indent 
) const [protected, inherited]
void itk::SPSAOptimizer::PrintSelf ( std::ostream &  os,
Indent  indent 
) const [protected, virtual]

PrintSelf method.

Reimplemented from itk::SingleValuedNonLinearOptimizer.

virtual void itk::LightObject::PrintTrailer ( std::ostream &  os,
Indent  indent 
) const [protected, virtual, inherited]

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.

virtual void itk::Object::Register (  )  const [virtual, inherited]

Increase the reference count (mark as used by another object).

Reimplemented from itk::LightObject.

void itk::Object::RemoveAllObservers (  )  [inherited]

Remove all observers .

void itk::Object::RemoveObserver ( unsigned long  tag  )  [inherited]

Remove the observer with this tag value.

void itk::SPSAOptimizer::ResumeOptimization ( void   ) 

Resume previously stopped optimization with current parameters

See also:
StopOptimization.
void itk::SPSAOptimizer::Seta ( double  a  )  [inline]

Set/Get a.

Definition at line 123 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 131 of file itkSPSAOptimizer.h.

virtual void itk::SingleValuedNonLinearOptimizer::SetCostFunction ( CostFunctionType *  costFunction  )  [virtual, inherited]

Set the cost function.

virtual void itk::Optimizer::SetCurrentPosition ( const ParametersType &  param  )  [protected, virtual, inherited]

Set the current position.

void itk::Object::SetDebug ( bool  debugFlag  )  const [inherited]

Set the value of the debug flag. A non-zero value turns debugging on.

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

Set/Get gamma.

static void itk::Object::SetGlobalWarningDisplay ( bool  flag  )  [static, inherited]

This is a global flag that controls whether any debug, warning or error messages are displayed.

Referenced by itk::Object::GlobalWarningDisplayOff(), and itk::Object::GlobalWarningDisplayOn().

virtual void itk::Optimizer::SetInitialPosition ( const ParametersType &  param  )  [virtual, inherited]

Set the position to initialize the optimization.

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

Methods to configure the cost function.

virtual void itk::SPSAOptimizer::SetMaximumNumberOfIterations ( unsigned long  _arg  )  [virtual]

Set/Get the maximum number of iterations.

void itk::Object::SetMetaDataDictionary ( const MetaDataDictionary &  rhs  )  [inherited]
Returns:
Set the MetaDataDictionary
void itk::SPSAOptimizer::SetMinimize ( bool  v  )  [inline]

Methods to configure the cost function.

Definition at line 156 of file itkSPSAOptimizer.h.

virtual void itk::SPSAOptimizer::SetMinimumNumberOfIterations ( unsigned long  _arg  )  [virtual]

Set/Get the minimum number of iterations

virtual void itk::SPSAOptimizer::SetNumberOfPerturbations ( unsigned long  _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::Object::SetReferenceCount ( int   )  [virtual, inherited]

Sets the reference count (use with care)

Reimplemented from itk::LightObject.

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

Set/Get a.

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

Set/Get c.

void itk::Optimizer::SetScales ( const ScalesType &  scales  )  [inherited]

Set current parameters scaling.

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

void itk::SPSAOptimizer::StartOptimization ( void   )  [virtual]

Start optimization.

Reimplemented from itk::Optimizer.

void itk::SPSAOptimizer::StopOptimization ( void   ) 

Stop optimization.

See also:
ResumeOptimization
virtual void itk::Object::UnRegister (  )  const [virtual, inherited]

Decrease the reference count (release by another object).

Reimplemented from itk::LightObject.

Member Data Documentation

CostFunctionPointer itk::SingleValuedNonLinearOptimizer::m_CostFunction [protected, inherited]

Definition at line 80 of file itkSingleValuedNonLinearOptimizer.h.

unsigned long itk::SPSAOptimizer::m_CurrentIteration [protected]

Definition at line 225 of file itkSPSAOptimizer.h.

ParametersType itk::Optimizer::m_CurrentPosition [protected, inherited]

Definition at line 98 of file itkOptimizer.h.

DerivativeType itk::SPSAOptimizer::m_Delta [protected]

Definition at line 221 of file itkSPSAOptimizer.h.

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

Random number generator

Definition at line 228 of file itkSPSAOptimizer.h.

DerivativeType itk::SPSAOptimizer::m_Gradient [protected]

Variables updated during optimization

Definition at line 219 of file itkSPSAOptimizer.h.

double itk::SPSAOptimizer::m_LearningRate [protected]

Definition at line 220 of file itkSPSAOptimizer.h.

InternalReferenceCountType itk::LightObject::m_ReferenceCount [mutable, protected, inherited]

Number of uses of this object by other objects.

Definition at line 144 of file itkLightObject.h.

SimpleFastMutexLock itk::LightObject::m_ReferenceCountLock [mutable, protected, inherited]

Mutex lock to protect modification to the reference count

Definition at line 147 of file itkLightObject.h.

bool itk::Optimizer::m_ScalesInitialized [protected, inherited]

Definition at line 93 of file itkOptimizer.h.

double itk::SPSAOptimizer::m_StateOfConvergence [protected]

Definition at line 224 of file itkSPSAOptimizer.h.

bool itk::SPSAOptimizer::m_Stop [protected]

Definition at line 222 of file itkSPSAOptimizer.h.

StopConditionType itk::SPSAOptimizer::m_StopCondition [protected]

Definition at line 223 of file itkSPSAOptimizer.h.

The documentation for this class was generated from the following file:
Generated at Tue Jul 13 2010 02:28:00 for ITK by doxygen 1.7.1 written by Dimitri van Heesch, © 1997-2000