itk::GradientDescentOptimizer Class Reference

#include <itkGradientDescentOptimizer.h>

Detailed Description

Implement a gradient descent optimizer.

GradientDescentOptimizer implements a simple gradient descent optimizer. At each iteration the current position is updated according to

\[ p_{n+1} = p_n + \mbox{learningRate} \, \frac{\partial f(p_n) }{\partial p_n} \]

The learning rate is a fixed scalar defined via SetLearningRate(). The optimizer steps through a user defined number of iterations; no convergence checking is done.

Additionally, user can scale each component, \( \partial f / \partial p \), by setting a scaling vector using method SetScale().

See also

RegularStepGradientDescentOptimizer

Examples

Examples/RegistrationITKv4/ImageRegistration2.cxx, SphinxExamples/src/Core/Transform/MutualInformationAffine/Code.cxx, SphinxExamples/src/Registration/Common/MutualInformation/Code.cxx, and SphinxExamples/src/Registration/Common/PerformMultiModalityRegistrationWithMutualInformation/Code.cxx.

Definition at line 72 of file itkGradientDescentOptimizer.h.

Inheritance diagram for itk::GradientDescentOptimizer:

Collaboration diagram for itk::GradientDescentOptimizer:

Public Types
using	ConstPointer = SmartPointer< const Self >
using	Pointer = SmartPointer< Self >
using	Self = GradientDescentOptimizer
using	StopConditionGradientDescentOptimizerEnum = GradientDescentOptimizerEnums::StopConditionGradientDescentOptimizer
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
virtual void	AdvanceOneStep ()
virtual SizeValueType	GetCurrentIteration () const
virtual const DerivativeType &	GetGradient () const
virtual const double &	GetLearningRate () const
const char *	GetNameOfClass () const override
virtual const SizeValueType &	GetNumberOfIterations () const
virtual const double &	GetValue () const
void	ResumeOptimization ()
virtual void	SetLearningRate (double _arg)
virtual void	SetNumberOfIterations (SizeValueType _arg)
void	StartOptimization () override
void	StopOptimization ()
virtual const bool &	GetMaximize () const
virtual void	SetMaximize (bool _arg)
virtual void	MaximizeOn ()
bool	GetMinimize () const
void	SetMinimize (bool v)
void	MinimizeOn ()
void	MinimizeOff ()
virtual const StopConditionGradientDescentOptimizerEnum &	GetStopCondition () const
std::string	GetStopConditionDescription () const override
Public Member Functions inherited from itk::SingleValuedNonLinearOptimizer
virtual CostFunctionType *	GetModifiableCostFunction ()
const char *	GetNameOfClass () const override
MeasureType	GetValue (const ParametersType &parameters) const
virtual void	SetCostFunction (CostFunctionType *costFunction)
Public Member Functions inherited from itk::Optimizer
virtual const ParametersType &	GetCurrentPosition () const
virtual const ParametersType &	GetInitialPosition () const
virtual void	SetInitialPosition (const ParametersType &param)
void	SetScales (const ScalesType &scales)
virtual const ScalesType &	GetScales () const
virtual const ScalesType &	GetInverseScales () const
Public Member Functions inherited from itk::Object
unsigned long	AddObserver (const EventObject &event, Command *cmd) const
unsigned long	AddObserver (const EventObject &event, std::function< void(const EventObject &)> function) const
LightObject::Pointer	CreateAnother () const override
virtual void	DebugOff () const
virtual void	DebugOn () const
Command *	GetCommand (unsigned long tag)
bool	GetDebug () const
MetaDataDictionary &	GetMetaDataDictionary ()
const MetaDataDictionary &	GetMetaDataDictionary () const
virtual ModifiedTimeType	GetMTime () const
virtual const TimeStamp &	GetTimeStamp () const
bool	HasObserver (const EventObject &event) const
void	InvokeEvent (const EventObject &)
void	InvokeEvent (const EventObject &) const
virtual void	Modified () const
void	Register () const override
void	RemoveAllObservers ()
void	RemoveObserver (unsigned long tag) const
void	SetDebug (bool debugFlag) const
void	SetReferenceCount (int) override
void	UnRegister () const noexcept override
void	SetMetaDataDictionary (const MetaDataDictionary &rhs)
void	SetMetaDataDictionary (MetaDataDictionary &&rrhs)
virtual void	SetObjectName (std::string _arg)
virtual const std::string &	GetObjectName () const
Public Member Functions inherited from itk::LightObject
Pointer	Clone () const
virtual void	Delete ()
virtual int	GetReferenceCount () const
void	Print (std::ostream &os, Indent indent=0) const

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
	GradientDescentOptimizer ()
void	PrintSelf (std::ostream &os, Indent indent) const override
	~GradientDescentOptimizer () 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
DerivativeType	m_Gradient {}
double	m_LearningRate { 1.0 }
bool	m_Maximize { false }
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 {}

Private Attributes
SizeValueType	m_CurrentIteration { 0 }
SizeValueType	m_NumberOfIterations { 100 }
bool	m_Stop { false }
StopConditionGradientDescentOptimizerEnum	m_StopCondition
std::ostringstream	m_StopConditionDescription {}
double	m_Value { 0.0 }

Member Typedef Documentation

ConstPointer

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

Definition at line 81 of file itkGradientDescentOptimizer.h.

Pointer

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

Definition at line 80 of file itkGradientDescentOptimizer.h.

Self

using itk::GradientDescentOptimizer::Self = GradientDescentOptimizer

Standard class type aliases.

Definition at line 78 of file itkGradientDescentOptimizer.h.

StopConditionGradientDescentOptimizerEnum

using itk::GradientDescentOptimizer::StopConditionGradientDescentOptimizerEnum = GradientDescentOptimizerEnums::StopConditionGradientDescentOptimizer

Definition at line 90 of file itkGradientDescentOptimizer.h.

Superclass

using itk::GradientDescentOptimizer::Superclass = SingleValuedNonLinearOptimizer

Definition at line 79 of file itkGradientDescentOptimizer.h.

Constructor & Destructor Documentation

GradientDescentOptimizer()

itk::GradientDescentOptimizer::GradientDescentOptimizer ( )

protected

~GradientDescentOptimizer()

itk::GradientDescentOptimizer::~GradientDescentOptimizer ( )

overrideprotecteddefault

Member Function Documentation

AdvanceOneStep()

virtual void itk::GradientDescentOptimizer::AdvanceOneStep ( )

virtual

Advance one step following the gradient direction.

Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer.

GetCurrentIteration()

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

virtual

Get the current iteration number.

GetGradient()

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

virtual

Get Gradient condition.

GetLearningRate()

virtual const double& itk::GradientDescentOptimizer::GetLearningRate ( ) const

virtual

Get the learning rate.

GetMaximize()

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

virtual

Methods to configure the cost function.

GetMinimize()

bool itk::GradientDescentOptimizer::GetMinimize ( ) const

inline

Methods to configure the cost function.

Definition at line 105 of file itkGradientDescentOptimizer.h.

GetNameOfClass()

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

overridevirtual

See also

LightObject::GetNameOfClass()

Reimplemented from itk::Object.

Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer.

GetNumberOfIterations()

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

virtual

Get the number of iterations.

GetStopCondition()

virtual const StopConditionGradientDescentOptimizerEnum& itk::GradientDescentOptimizer::GetStopCondition ( ) const

virtual

Get Stop condition.

GetStopConditionDescription()

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

overridevirtual

Get Stop condition.

Reimplemented from itk::Optimizer.

GetValue()

virtual const double& itk::GradientDescentOptimizer::GetValue ( ) const

virtual

Get the current value.

MaximizeOn()

virtual void itk::GradientDescentOptimizer::MaximizeOn ( )

virtual

Methods to configure the cost function.

MinimizeOff()

void itk::GradientDescentOptimizer::MinimizeOff ( )

inline

Methods to configure the cost function.

Definition at line 120 of file itkGradientDescentOptimizer.h.

MinimizeOn()

void itk::GradientDescentOptimizer::MinimizeOn ( )

inline

Methods to configure the cost function.

Definition at line 115 of file itkGradientDescentOptimizer.h.

New()

static Pointer itk::GradientDescentOptimizer::New ( )

static

Method for creation through the object factory.

PrintSelf()

void itk::GradientDescentOptimizer::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::Object.

ResumeOptimization()

void itk::GradientDescentOptimizer::ResumeOptimization

(

)

Resume previously stopped optimization with current parameters

See also

StopOptimization.

SetLearningRate()

virtual void itk::GradientDescentOptimizer::SetLearningRate ( double  _arg )

virtual

Set the learning rate.

SetMaximize()

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

virtual

Methods to configure the cost function.

SetMinimize()

void itk::GradientDescentOptimizer::SetMinimize ( bool  v )

inline

Methods to configure the cost function.

Definition at line 110 of file itkGradientDescentOptimizer.h.

SetNumberOfIterations()

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

virtual

Set the number of iterations.

StartOptimization()

void itk::GradientDescentOptimizer::StartOptimization ( )

overridevirtual

Start optimization.

Reimplemented from itk::Optimizer.

StopOptimization()

void itk::GradientDescentOptimizer::StopOptimization

(

)

Stop optimization.

See also

ResumeOptimization

Member Data Documentation

m_CurrentIteration

SizeValueType itk::GradientDescentOptimizer::m_CurrentIteration { 0 }

private

Definition at line 191 of file itkGradientDescentOptimizer.h.

m_Gradient

DerivativeType itk::GradientDescentOptimizer::m_Gradient {}

protected

Definition at line 178 of file itkGradientDescentOptimizer.h.

m_LearningRate

double itk::GradientDescentOptimizer::m_LearningRate { 1.0 }

protected

Definition at line 182 of file itkGradientDescentOptimizer.h.

m_Maximize

bool itk::GradientDescentOptimizer::m_Maximize { false }

protected

Definition at line 180 of file itkGradientDescentOptimizer.h.

m_NumberOfIterations

SizeValueType itk::GradientDescentOptimizer::m_NumberOfIterations { 100 }

private

Definition at line 190 of file itkGradientDescentOptimizer.h.

m_Stop

bool itk::GradientDescentOptimizer::m_Stop { false }

private

Definition at line 185 of file itkGradientDescentOptimizer.h.

m_StopCondition

StopConditionGradientDescentOptimizerEnum itk::GradientDescentOptimizer::m_StopCondition

private

Initial value:

{
    StopConditionGradientDescentOptimizerEnum::MaximumNumberOfIterations
  }

Definition at line 187 of file itkGradientDescentOptimizer.h.

m_StopConditionDescription

std::ostringstream itk::GradientDescentOptimizer::m_StopConditionDescription {}

private

Definition at line 192 of file itkGradientDescentOptimizer.h.

m_Value

double itk::GradientDescentOptimizer::m_Value { 0.0 }

private

Definition at line 186 of file itkGradientDescentOptimizer.h.

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

• itkGradientDescentOptimizer.h