ITK  5.4.0
Insight Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Protected Attributes | List of all members

#include <itkRegularStepGradientDescentBaseOptimizer.h>

Detailed Description

Implement a gradient descent optimizer.

Definition at line 58 of file itkRegularStepGradientDescentBaseOptimizer.h.

+ Inheritance diagram for itk::RegularStepGradientDescentBaseOptimizer:
+ Collaboration diagram for itk::RegularStepGradientDescentBaseOptimizer:

Public Types

using ConstPointer = SmartPointer< const Self >
 
using Pointer = SmartPointer< Self >
 
using Self = RegularStepGradientDescentBaseOptimizer
 
using StopConditionEnum = RegularStepGradientDescentBaseOptimizerEnums::StopCondition
 
using Superclass = SingleValuedNonLinearOptimizer
 
- 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

const char * GetNameOfClass () const override
 
const std::string GetStopConditionDescription () const override
 
void ResumeOptimization ()
 
void StartOptimization () override
 
void StopOptimization ()
 
virtual void SetMaximize (bool _arg)
 
virtual const bool & GetMaximize () const
 
virtual void MaximizeOn ()
 
bool GetMinimize () const
 
void SetMinimize (bool v)
 
void MinimizeOn ()
 
void MinimizeOff ()
 
virtual void SetMaximumStepLength (double _arg)
 
virtual void SetMinimumStepLength (double _arg)
 
virtual void SetRelaxationFactor (double _arg)
 
virtual void SetNumberOfIterations (SizeValueType _arg)
 
virtual void SetGradientMagnitudeTolerance (double _arg)
 
virtual const double & GetCurrentStepLength () const
 
virtual const double & GetMaximumStepLength () const
 
virtual const double & GetMinimumStepLength () const
 
virtual const double & GetRelaxationFactor () const
 
virtual const SizeValueTypeGetNumberOfIterations () const
 
virtual const double & GetGradientMagnitudeTolerance () const
 
virtual unsigned int GetCurrentIteration () const
 
virtual const StopConditionEnumGetStopCondition () const
 
virtual const MeasureTypeGetValue () const
 
virtual const DerivativeTypeGetGradient () const
 
- Public Member Functions inherited from itk::SingleValuedNonLinearOptimizer
virtual CostFunctionTypeGetModifiableCostFunction ()
 
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 ParametersTypeGetCurrentPosition () const
 
virtual const ParametersTypeGetInitialPosition () const
 
virtual void SetInitialPosition (const ParametersType &param)
 
void SetScales (const ScalesType &scales)
 
virtual const ScalesTypeGetScales () const
 
virtual const ScalesTypeGetInverseScales () const
 
- Public Member Functions inherited from itk::Object
unsigned long AddObserver (const EventObject &event, Command *)
 
unsigned long AddObserver (const EventObject &event, Command *) const
 
unsigned long AddObserver (const EventObject &event, std::function< void(const EventObject &)> function) const
 
LightObject::Pointer CreateAnother () const override
 
virtual void DebugOff () const
 
virtual void DebugOn () const
 
CommandGetCommand (unsigned long tag)
 
bool GetDebug () const
 
MetaDataDictionaryGetMetaDataDictionary ()
 
const MetaDataDictionaryGetMetaDataDictionary () const
 
virtual ModifiedTimeType GetMTime () const
 
virtual const TimeStampGetTimeStamp () const
 
bool HasObserver (const EventObject &event) const
 
void InvokeEvent (const EventObject &)
 
void InvokeEvent (const EventObject &) const
 
virtual void Modified () const
 
void Register () const override
 
void RemoveAllObservers ()
 
void RemoveObserver (unsigned long tag)
 
void SetDebug (bool debugFlag) const
 
void SetReferenceCount (int) override
 
void UnRegister () const noexcept override
 
void SetMetaDataDictionary (const MetaDataDictionary &rhs)
 
void SetMetaDataDictionary (MetaDataDictionary &&rrhs)
 
virtual void SetObjectName (std::string _arg)
 
virtual const std::string & GetObjectName () const
 
- Public Member Functions inherited from itk::LightObject
Pointer Clone () const
 
virtual void Delete ()
 
virtual int GetReferenceCount () const
 
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 val)
 
- Static Public Member Functions inherited from itk::LightObject
static void BreakOnError ()
 
static Pointer New ()
 

Protected Member Functions

virtual void AdvanceOneStep ()
 
void PrintSelf (std::ostream &os, Indent indent) const override
 
 RegularStepGradientDescentBaseOptimizer ()
 
virtual void StepAlongGradient (double, const DerivativeType &)
 
 ~RegularStepGradientDescentBaseOptimizer () override=default
 
- 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

SizeValueType m_CurrentIteration {}
 
double m_CurrentStepLength {}
 
DerivativeType m_Gradient {}
 
double m_GradientMagnitudeTolerance {}
 
bool m_Maximize {}
 
double m_MaximumStepLength {}
 
double m_MinimumStepLength {}
 
SizeValueType m_NumberOfIterations {}
 
DerivativeType m_PreviousGradient {}
 
double m_RelaxationFactor {}
 
bool m_Stop { false }
 
StopConditionEnum m_StopCondition {}
 
std::ostringstream m_StopConditionDescription {}
 
MeasureType m_Value {}
 
- 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 {}
 

Member Typedef Documentation

◆ ConstPointer

Definition at line 67 of file itkRegularStepGradientDescentBaseOptimizer.h.

◆ Pointer

Definition at line 66 of file itkRegularStepGradientDescentBaseOptimizer.h.

◆ Self

Standard "Self" type alias.

Definition at line 64 of file itkRegularStepGradientDescentBaseOptimizer.h.

◆ StopConditionEnum

Definition at line 75 of file itkRegularStepGradientDescentBaseOptimizer.h.

◆ Superclass

Definition at line 65 of file itkRegularStepGradientDescentBaseOptimizer.h.

Constructor & Destructor Documentation

◆ RegularStepGradientDescentBaseOptimizer()

itk::RegularStepGradientDescentBaseOptimizer::RegularStepGradientDescentBaseOptimizer ( )
protected

◆ ~RegularStepGradientDescentBaseOptimizer()

itk::RegularStepGradientDescentBaseOptimizer::~RegularStepGradientDescentBaseOptimizer ( )
overrideprotecteddefault

Member Function Documentation

◆ AdvanceOneStep()

virtual void itk::RegularStepGradientDescentBaseOptimizer::AdvanceOneStep ( )
protectedvirtual

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.

◆ GetCurrentIteration()

virtual unsigned int itk::RegularStepGradientDescentBaseOptimizer::GetCurrentIteration ( ) const
virtual

Set/Get parameters to control the optimization process.

◆ GetCurrentStepLength()

virtual const double& itk::RegularStepGradientDescentBaseOptimizer::GetCurrentStepLength ( ) const
virtual

Set/Get parameters to control the optimization process.

◆ GetGradient()

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

Set/Get parameters to control the optimization process.

◆ GetGradientMagnitudeTolerance()

virtual const double& itk::RegularStepGradientDescentBaseOptimizer::GetGradientMagnitudeTolerance ( ) const
virtual

Set/Get parameters to control the optimization process.

◆ GetMaximize()

virtual const bool& itk::RegularStepGradientDescentBaseOptimizer::GetMaximize ( ) const
virtual

Specify whether to minimize or maximize the cost function.

◆ GetMaximumStepLength()

virtual const double& itk::RegularStepGradientDescentBaseOptimizer::GetMaximumStepLength ( ) const
virtual

Set/Get parameters to control the optimization process.

◆ GetMinimize()

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

Specify whether to minimize or maximize the cost function.

Definition at line 91 of file itkRegularStepGradientDescentBaseOptimizer.h.

◆ GetMinimumStepLength()

virtual const double& itk::RegularStepGradientDescentBaseOptimizer::GetMinimumStepLength ( ) const
virtual

Set/Get parameters to control the optimization process.

◆ GetNameOfClass()

const char* itk::RegularStepGradientDescentBaseOptimizer::GetNameOfClass ( ) const
overridevirtual

◆ GetNumberOfIterations()

virtual const SizeValueType& itk::RegularStepGradientDescentBaseOptimizer::GetNumberOfIterations ( ) const
virtual

Set/Get parameters to control the optimization process.

◆ GetRelaxationFactor()

virtual const double& itk::RegularStepGradientDescentBaseOptimizer::GetRelaxationFactor ( ) const
virtual

Set/Get parameters to control the optimization process.

◆ GetStopCondition()

virtual const StopConditionEnum& itk::RegularStepGradientDescentBaseOptimizer::GetStopCondition ( ) const
virtual

Set/Get parameters to control the optimization process.

◆ GetStopConditionDescription()

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

Get the reason for termination

Reimplemented from itk::Optimizer.

◆ GetValue()

virtual const MeasureType& itk::RegularStepGradientDescentBaseOptimizer::GetValue ( ) const
virtual

Set/Get parameters to control the optimization process.

◆ MaximizeOn()

virtual void itk::RegularStepGradientDescentBaseOptimizer::MaximizeOn ( )
virtual

Specify whether to minimize or maximize the cost function.

◆ MinimizeOff()

void itk::RegularStepGradientDescentBaseOptimizer::MinimizeOff ( )
inline

Specify whether to minimize or maximize the cost function.

Definition at line 106 of file itkRegularStepGradientDescentBaseOptimizer.h.

◆ MinimizeOn()

void itk::RegularStepGradientDescentBaseOptimizer::MinimizeOn ( )
inline

Specify whether to minimize or maximize the cost function.

Definition at line 101 of file itkRegularStepGradientDescentBaseOptimizer.h.

◆ New()

static Pointer itk::RegularStepGradientDescentBaseOptimizer::New ( )
static

Method for creation through the object factory.

◆ PrintSelf()

void itk::RegularStepGradientDescentBaseOptimizer::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.

◆ ResumeOptimization()

void itk::RegularStepGradientDescentBaseOptimizer::ResumeOptimization ( )

Resume previously stopped optimization with current parameters.

See also
StopOptimization

◆ SetGradientMagnitudeTolerance()

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetGradientMagnitudeTolerance ( double  _arg)
virtual

Set/Get parameters to control the optimization process.

◆ SetMaximize()

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

Specify whether to minimize or maximize the cost function.

◆ SetMaximumStepLength()

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetMaximumStepLength ( double  _arg)
virtual

Set/Get parameters to control the optimization process.

◆ SetMinimize()

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

Specify whether to minimize or maximize the cost function.

Definition at line 96 of file itkRegularStepGradientDescentBaseOptimizer.h.

◆ SetMinimumStepLength()

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetMinimumStepLength ( double  _arg)
virtual

Set/Get parameters to control the optimization process.

◆ SetNumberOfIterations()

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetNumberOfIterations ( SizeValueType  _arg)
virtual

Set/Get parameters to control the optimization process.

◆ SetRelaxationFactor()

virtual void itk::RegularStepGradientDescentBaseOptimizer::SetRelaxationFactor ( double  _arg)
virtual

Set/Get parameters to control the optimization process.

◆ StartOptimization()

void itk::RegularStepGradientDescentBaseOptimizer::StartOptimization ( )
overridevirtual

Start optimization.

Reimplemented from itk::Optimizer.

◆ StepAlongGradient()

virtual void itk::RegularStepGradientDescentBaseOptimizer::StepAlongGradient ( double  ,
const DerivativeType  
)
inlineprotectedvirtual

Advance one step along the corrected gradient taking into account the steplength represented by factor. This method is invoked by AdvanceOneStep. It is expected to be overridden by optimization methods in non-vector spaces

See also
AdvanceOneStep

Reimplemented in itk::VersorTransformOptimizer, and itk::RegularStepGradientDescentOptimizer.

Definition at line 166 of file itkRegularStepGradientDescentBaseOptimizer.h.

◆ StopOptimization()

void itk::RegularStepGradientDescentBaseOptimizer::StopOptimization ( )

Stop optimization.

See also
ResumeOptimization

Member Data Documentation

◆ m_CurrentIteration

SizeValueType itk::RegularStepGradientDescentBaseOptimizer::m_CurrentIteration {}
protected

◆ m_CurrentStepLength

double itk::RegularStepGradientDescentBaseOptimizer::m_CurrentStepLength {}
protected

◆ m_Gradient

DerivativeType itk::RegularStepGradientDescentBaseOptimizer::m_Gradient {}
protected

◆ m_GradientMagnitudeTolerance

double itk::RegularStepGradientDescentBaseOptimizer::m_GradientMagnitudeTolerance {}
protected

◆ m_Maximize

bool itk::RegularStepGradientDescentBaseOptimizer::m_Maximize {}
protected

◆ m_MaximumStepLength

double itk::RegularStepGradientDescentBaseOptimizer::m_MaximumStepLength {}
protected

◆ m_MinimumStepLength

double itk::RegularStepGradientDescentBaseOptimizer::m_MinimumStepLength {}
protected

◆ m_NumberOfIterations

SizeValueType itk::RegularStepGradientDescentBaseOptimizer::m_NumberOfIterations {}
protected

◆ m_PreviousGradient

DerivativeType itk::RegularStepGradientDescentBaseOptimizer::m_PreviousGradient {}
protected

◆ m_RelaxationFactor

double itk::RegularStepGradientDescentBaseOptimizer::m_RelaxationFactor {}
protected

◆ m_Stop

bool itk::RegularStepGradientDescentBaseOptimizer::m_Stop { false }
protected

◆ m_StopCondition

StopConditionEnum itk::RegularStepGradientDescentBaseOptimizer::m_StopCondition {}
protected

◆ m_StopConditionDescription

std::ostringstream itk::RegularStepGradientDescentBaseOptimizer::m_StopConditionDescription {}
protected

◆ m_Value

MeasureType itk::RegularStepGradientDescentBaseOptimizer::m_Value {}
protected

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