itk::VersorTransformOptimizer Class Reference
[Numerics]

#include <itkVersorTransformOptimizer.h>

Inheritance diagram for itk::VersorTransformOptimizer:

[legend]Collaboration diagram for itk::VersorTransformOptimizer:

[legend]List of all members.

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Detailed Description

Implement a gradient descent optimizer.

VersorTransformOptimizer is a variant of the gradient descent optimizer implmented in RegularStepGradientDescentOptimizer.

Versors are not in a vector space, for that reason, the classical gradient descent algorithm has to be modified in order to be applicable to Versors (unit quaternions) that form the group SO(3).

The Versor space has only three degrees of freedom, even though Versors are represented using four values.

This optimizer assumes that the CostFunction to be optimized has an itk::Versor as parameter.

See also:

RegularStepGradientDescentOptimizer

Versor

VersorTransform

Optimizers

Definition at line 50 of file itkVersorTransformOptimizer.h.

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 VersorTransformOptimizer	Self
enum	StopConditionType {   GradientMagnitudeTolerance = 1,   StepTooSmall = 2,   ImageNotAvailable = 3,   CostFunctionError = 4,   MaximumNumberOfIterations = 5 }
typedef RegularStepGradientDescentBaseOptimizer	Superclass
typedef VersorType::VectorType	VectorType
typedef Versor< double >	VersorType
Public Member Functions
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 int	GetCurrentIteration () const
virtual const ParametersType &	GetCurrentPosition ()
virtual const double &	GetCurrentStepLength ()
bool	GetDebug () const
virtual const DerivativeType &	GetGradient ()
virtual const double &	GetGradientMagnitudeTolerance ()
virtual const ParametersType &	GetInitialPosition ()
virtual const bool &	GetMaximize ()
virtual const double &	GetMaximumStepLength ()
const MetaDataDictionary &	GetMetaDataDictionary (void) const
MetaDataDictionary &	GetMetaDataDictionary (void)
bool	GetMinimize () const
virtual const double &	GetMinimumStepLength ()
virtual unsigned long	GetMTime () const
virtual const char *	GetNameOfClass () const
virtual const unsigned long &	GetNumberOfIterations ()
virtual int	GetReferenceCount () const
virtual const double &	GetRelaxationFactor ()
virtual const ScalesType &	GetScales ()
virtual const StopConditionType &	GetStopCondition ()
MeasureType	GetValue (const ParametersType &parameters) const
virtual const MeasureType &	GetValue ()
bool	HasObserver (const EventObject &event) const
void	InvokeEvent (const EventObject &) const
void	InvokeEvent (const EventObject &)
virtual void	MaximizeOff ()
virtual void	MaximizeOn ()
void	MinimizeOff (void)
void	MinimizeOn (void)
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	SetGradientMagnitudeTolerance (double _arg)
virtual void	SetInitialPosition (const ParametersType &param)
Specify whether to minimize or maximize the cost function *virtual void	SetMaximize (bool _arg)
Set Get parameters to control the optimization process *virtual void	SetMaximumStepLength (double _arg)
void	SetMetaDataDictionary (const MetaDataDictionary &rhs)
void	SetMinimize (bool v)
virtual void	SetMinimumStepLength (double _arg)
virtual void	SetNumberOfIterations (unsigned long _arg)
virtual void	SetReferenceCount (int)
virtual void	SetRelaxationFactor (double _arg)
void	SetScales (const ScalesType &scales)
void	StartOptimization (void)
virtual void	StepAlongGradient (double factor, const DerivativeType &transformedGradient)
void	StopOptimization (void)
virtual void	UnRegister () const
Static Public Member Functions
static void	BreakOnError ()
static bool	GetGlobalWarningDisplay ()
static void	GlobalWarningDisplayOff ()
static void	GlobalWarningDisplayOn ()
static Pointer	New ()
This is a global flag that controls whether any warning *or error messages are displayed *static void	SetGlobalWarningDisplay (bool flag)
Public Attributes
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 unsigned lon	AddObserver )(const EventObject &event, Command *) const
This is a global flag that controls whether any	debug
Protected Member Functions
virtual void	AdvanceOneStep (void)
bool	PrintObservers (std::ostream &os, Indent indent) const
void	PrintSelf (std::ostream &os, Indent indent) const
virtual void	PrintTrailer (std::ostream &os, Indent indent) const
virtual void	SetCurrentPosition (const ParametersType &param)
	VersorTransformOptimizer ()
virtual	~VersorTransformOptimizer ()
Protected Attributes
CostFunctionPointer	m_CostFunction
unsigned long	m_CurrentIteration
double	m_CurrentStepLength
DerivativeType	m_Gradient
double	m_GradientMagnitudeTolerance
bool	m_Maximize
double	m_MaximumStepLength
double	m_MinimumStepLength
unsigned long	m_NumberOfIterations
DerivativeType	m_PreviousGradient
int	m_ReferenceCount
SimpleFastMutexLock	m_ReferenceCountLock
double	m_RelaxationFactor
bool	m_ScalesInitialized
bool	m_Stop
StopConditionType	m_StopCondition
MeasureType	m_Value
Methods invoked by virtual 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 PrintSelf(std voi	PrintHeader )(std::ostream &os, Indent indent) const

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Member Typedef Documentation

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

Reimplemented from itk::RegularStepGradientDescentBaseOptimizer. Definition at line 58 of file itkVersorTransformOptimizer.h.

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

Reimplemented in itk::FRPROptimizer, itk::LBFGSBOptimizer, 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::LBFGSBOptimizer, 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 CostFunctionType::MeasureType itk::SingleValuedNonLinearOptimizer::MeasureType [inherited]

Measure type. It defines a type used to return the cost function value. Reimplemented in itk::LBFGSBOptimizer. 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::VersorTransformOptimizer::Pointer

Reimplemented from itk::RegularStepGradientDescentBaseOptimizer. Definition at line 57 of file itkVersorTransformOptimizer.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 VersorTransformOptimizer itk::VersorTransformOptimizer::Self

Standard class typedefs. Reimplemented from itk::RegularStepGradientDescentBaseOptimizer. Definition at line 55 of file itkVersorTransformOptimizer.h.

typedef RegularStepGradientDescentBaseOptimizer itk::VersorTransformOptimizer::Superclass

Reimplemented from itk::RegularStepGradientDescentBaseOptimizer. Definition at line 56 of file itkVersorTransformOptimizer.h.

typedef VersorType::VectorType itk::VersorTransformOptimizer::VectorType

Definition at line 69 of file itkVersorTransformOptimizer.h.

typedef Versor<double> itk::VersorTransformOptimizer::VersorType

Versor Type Definition at line 65 of file itkVersorTransformOptimizer.h.

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Member Enumeration Documentation

enum itk::RegularStepGradientDescentBaseOptimizer::StopConditionType [inherited]

Codes of stopping conditions. Enumeration values: GradientMagnitudeTolerance  StepTooSmall  ImageNotAvailable  CostFunctionError  MaximumNumberOfIterations  Definition at line 49 of file itkRegularStepGradientDescentBaseOptimizer.h.

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Constructor & Destructor Documentation

itk::VersorTransformOptimizer::VersorTransformOptimizer (   )  [inline, protected]

Definition at line 76 of file itkVersorTransformOptimizer.h.

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

Definition at line 77 of file itkVersorTransformOptimizer.h.

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Member Function Documentation

virtual void itk::RegularStepGradientDescentBaseOptimizer::AdvanceOneStep (  void   )  [protected, virtual, inherited]

Advance one step following the gradient direction This method verifies if a change in direction is required and if a reduction in steplength is required.

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

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

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.

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.

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 int itk::RegularStepGradientDescentBaseOptimizer::GetCurrentIteration (   )  const [virtual, inherited]

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

Get current position of the optimization.

virtual const double& itk::RegularStepGradientDescentBaseOptimizer::GetCurrentStepLength (   )  [virtual, inherited]

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

Get the value of the debug flag.

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

virtual const DerivativeType& itk::RegularStepGradientDescentBaseOptimizer::GetGradient (   )  [virtual, inherited]

virtual const double& itk::RegularStepGradientDescentBaseOptimizer::GetGradientMagnitudeTolerance (   )  [virtual, inherited]

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

Get the position to initialize the optimization.

virtual const bool& itk::RegularStepGradientDescentBaseOptimizer::GetMaximize (   )  [virtual, inherited]

virtual const double& itk::RegularStepGradientDescentBaseOptimizer::GetMaximumStepLength (   )  [virtual, inherited]

const MetaDataDictionary& itk::Object::GetMetaDataDictionary (  void   )  const [inherited]

Returns: A constant reference to this objects MetaDataDictionary.

MetaDataDictionary& itk::Object::GetMetaDataDictionary (  void   )  [inherited]

Returns: A reference to this objects MetaDataDictionary. Warning: This reference may be changed.

bool itk::RegularStepGradientDescentBaseOptimizer::GetMinimize (   )  const [inline, inherited]

Definition at line 61 of file itkRegularStepGradientDescentBaseOptimizer.h.

virtual const double& itk::RegularStepGradientDescentBaseOptimizer::GetMinimumStepLength (   )  [virtual, inherited]

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

Return this objects modified time. Reimplemented in itk::ImageRegistrationMethod< TFixedImage, TMovingImage >, itk::DeformationFieldSource< TOutputImage >, itk::InverseDeformationFieldImageFilter< TInputImage, TOutputImage >, itk::ResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::VectorResampleImageFilter< TInputImage, TOutputImage, TInterpolatorPrecisionType >, itk::BoundingBox< TPointIdentifier, VPointDimension, TCoordRep, TPointsContainer >, itk::SceneSpatialObject< SpaceDimension >, and itk::SceneSpatialObject< NDimensions >.

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

Run-time type information (and related methods). Reimplemented from itk::RegularStepGradientDescentBaseOptimizer.

virtual const unsigned long& itk::RegularStepGradientDescentBaseOptimizer::GetNumberOfIterations (   )  [virtual, inherited]

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

Gets the reference count on this object. Definition at line 98 of file itkLightObject.h.

virtual const double& itk::RegularStepGradientDescentBaseOptimizer::GetRelaxationFactor (   )  [virtual, inherited]

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

Get current parameters scaling.

virtual const StopConditionType& itk::RegularStepGradientDescentBaseOptimizer::GetStopCondition (   )  [virtual, inherited]

MeasureType itk::SingleValuedNonLinearOptimizer::GetValue (  const ParametersType &  parameters  )  const [inherited]

Get the cost function value at the given parameters. Reimplemented in itk::SPSAOptimizer.

virtual const MeasureType& itk::RegularStepGradientDescentBaseOptimizer::GetValue (   )  [virtual, inherited]

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

Definition at line 100 of file itkObject.h. References itk::Object::SetGlobalWarningDisplay().

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

Definition at line 98 of file itkObject.h. References itk::Object::SetGlobalWarningDisplay().

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 &   )  const [inherited]

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

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

Call Execute on all the Commands observing this event id.

virtual void itk::RegularStepGradientDescentBaseOptimizer::MaximizeOff (   )  [virtual, inherited]

virtual void itk::RegularStepGradientDescentBaseOptimizer::MaximizeOn (   )  [virtual, inherited]

void itk::RegularStepGradientDescentBaseOptimizer::MinimizeOff (  void   )  [inline, inherited]

Definition at line 67 of file itkRegularStepGradientDescentBaseOptimizer.h.

void itk::RegularStepGradientDescentBaseOptimizer::MinimizeOn (  void   )  [inline, inherited]

Definition at line 65 of file itkRegularStepGradientDescentBaseOptimizer.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. Referenced by itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetCenter(), itk::HistogramAlgorithmBase< TInputHistogram >::SetInputHistogram(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetMatrix(), itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetOffset(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetRealThresholds(), itk::CollidingFrontsImageFilter< TInputImage, TOutputImage >::SetSeedPoints1(), itk::CollidingFrontsImageFilter< TInputImage, TOutputImage >::SetSeedPoints2(), itk::NonUniformBSpline< TDimension >::SetSplineOrder(), itk::ThresholdLabelerImageFilter< TInputImage, TOutputImage >::SetThresholds(), itk::Statistics::GoodnessOfFitFunctionBase< typename ComponentType::HistogramType >::SetTotalObservedScale(), and itk::MatrixOffsetTransformBase< TScalarType, 3, 3 >::SetTranslation().

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

Method for creation through the object factory. Reimplemented from itk::RegularStepGradientDescentBaseOptimizer.

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

Cause the object to print itself out.

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

void itk::RegularStepGradientDescentBaseOptimizer::PrintSelf (  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. Reimplemented from itk::SingleValuedNonLinearOptimizer.

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

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::RegularStepGradientDescentBaseOptimizer::ResumeOptimization (  void   )  [inherited]

Resume previously stopped optimization with current parameters. See also: StopOptimization

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.

This is a global flag that controls whether any warning* or error messages are displayed* static void itk::Object::SetGlobalWarningDisplay (  bool  flag  )  [static, inherited]

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

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetGradientMagnitudeTolerance (  double  _arg  )  [virtual, inherited]

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

Set the position to initialize the optimization.

Specify whether to minimize or maximize the cost function* virtual void itk::RegularStepGradientDescentBaseOptimizer::SetMaximize (  bool  _arg  )  [virtual, inherited]

Set Get parameters to control the optimization process* virtual void itk::RegularStepGradientDescentBaseOptimizer::SetMaximumStepLength (  double  _arg  )  [virtual, inherited]

void itk::Object::SetMetaDataDictionary (  const MetaDataDictionary &  rhs  )  [inherited]

Returns: Set the MetaDataDictionary

void itk::RegularStepGradientDescentBaseOptimizer::SetMinimize (  bool  v  )  [inline, inherited]

Definition at line 63 of file itkRegularStepGradientDescentBaseOptimizer.h.

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetMinimumStepLength (  double  _arg  )  [virtual, inherited]

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetNumberOfIterations (  unsigned long  _arg  )  [virtual, inherited]

virtual void itk::Object::SetReferenceCount (  int   )  [virtual, inherited]

Sets the reference count (use with care) Reimplemented from itk::LightObject.

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetRelaxationFactor (  double  _arg  )  [virtual, inherited]

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

Set current parameters scaling. Reimplemented in itk::LBFGSBOptimizer.

void itk::RegularStepGradientDescentBaseOptimizer::StartOptimization (  void   )  [virtual, inherited]

Start optimization. Reimplemented from itk::Optimizer.

virtual void itk::VersorTransformOptimizer::StepAlongGradient (  double  factor, const DerivativeType &  transformedGradient )  [virtual]

Advance one step following the gradient direction. Reimplemented from itk::RegularStepGradientDescentBaseOptimizer.

void itk::RegularStepGradientDescentBaseOptimizer::StopOptimization (  void   )  [inherited]

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.

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Member Data Documentation

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

This is a global flag that controls whether any itk::Object::debug [inherited]

Definition at line 94 of file itkObject.h.

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

Definition at line 80 of file itkSingleValuedNonLinearOptimizer.h.

unsigned long itk::RegularStepGradientDescentBaseOptimizer::m_CurrentIteration [protected, inherited]

Definition at line 146 of file itkRegularStepGradientDescentBaseOptimizer.h.

double itk::RegularStepGradientDescentBaseOptimizer::m_CurrentStepLength [protected, inherited]

Definition at line 142 of file itkRegularStepGradientDescentBaseOptimizer.h.

DerivativeType itk::RegularStepGradientDescentBaseOptimizer::m_Gradient [protected, inherited]

Definition at line 133 of file itkRegularStepGradientDescentBaseOptimizer.h.

double itk::RegularStepGradientDescentBaseOptimizer::m_GradientMagnitudeTolerance [protected, inherited]

Definition at line 139 of file itkRegularStepGradientDescentBaseOptimizer.h.

bool itk::RegularStepGradientDescentBaseOptimizer::m_Maximize [protected, inherited]

Definition at line 137 of file itkRegularStepGradientDescentBaseOptimizer.h.

double itk::RegularStepGradientDescentBaseOptimizer::m_MaximumStepLength [protected, inherited]

Definition at line 140 of file itkRegularStepGradientDescentBaseOptimizer.h.

double itk::RegularStepGradientDescentBaseOptimizer::m_MinimumStepLength [protected, inherited]

Definition at line 141 of file itkRegularStepGradientDescentBaseOptimizer.h.

unsigned long itk::RegularStepGradientDescentBaseOptimizer::m_NumberOfIterations [protected, inherited]

Definition at line 145 of file itkRegularStepGradientDescentBaseOptimizer.h.

DerivativeType itk::RegularStepGradientDescentBaseOptimizer::m_PreviousGradient [protected, inherited]

Definition at line 134 of file itkRegularStepGradientDescentBaseOptimizer.h.

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

Number of uses of this object by other objects. Definition at line 119 of file itkLightObject.h.

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

Mutex lock to protect modification to the reference count Definition at line 122 of file itkLightObject.h.

double itk::RegularStepGradientDescentBaseOptimizer::m_RelaxationFactor [protected, inherited]

Definition at line 143 of file itkRegularStepGradientDescentBaseOptimizer.h.

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

Definition at line 90 of file itkOptimizer.h.

bool itk::RegularStepGradientDescentBaseOptimizer::m_Stop [protected, inherited]

Definition at line 136 of file itkRegularStepGradientDescentBaseOptimizer.h.

StopConditionType itk::RegularStepGradientDescentBaseOptimizer::m_StopCondition [protected, inherited]

Definition at line 144 of file itkRegularStepGradientDescentBaseOptimizer.h.

MeasureType itk::RegularStepGradientDescentBaseOptimizer::m_Value [protected, inherited]

Definition at line 138 of file itkRegularStepGradientDescentBaseOptimizer.h.

Methods invoked by virtual 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 PrintSelf(std voi itk::LightObject::PrintHeader)(std::ostream &os, Indent indent) const [protected, inherited]

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

• itkVersorTransformOptimizer.h

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