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itk::GenericConjugateGradientOptimizer Class Reference
Components » Optimizers

#include <itkGenericConjugateGradientOptimizer.h>

Detailed Description

A set of conjugate gradient algorithms.

The steplength is determined at each iteration by means of a line search routine. The itk::MoreThuenteLineSearchOptimizer works well.

Definition at line 40 of file itkGenericConjugateGradientOptimizer.h.

+ Inheritance diagram for itk::GenericConjugateGradientOptimizer:

Public Types

typedef std::map< BetaDefinitionType, ComputeBetaFunctionType > BetaDefinitionMapType
 
typedef std::string BetaDefinitionType
 
typedef double(Self::* ComputeBetaFunctionType) (const DerivativeType &, const DerivativeType &, const ParametersType &)
 
typedef SmartPointer< const Self > ConstPointer
 
typedef Superclass::CostFunctionType CostFunctionType
 
typedef Superclass::DerivativeType DerivativeType
 
typedef LineSearchOptimizerType::Pointer LineSearchOptimizerPointer
 
typedef LineSearchOptimizer LineSearchOptimizerType
 
typedef Superclass::MeasureType MeasureType
 
typedef Superclass::ParametersType ParametersType
 
typedef SmartPointer< Self > Pointer
 
typedef Superclass::ScaledCostFunctionType ScaledCostFunctionType
 
typedef Superclass::ScalesType ScalesType
 
typedef GenericConjugateGradientOptimizer Self
 
enum  StopConditionType {
  MetricError , LineSearchError , MaximumNumberOfIterations , GradientMagnitudeTolerance ,
  ValueTolerance , InfiniteBeta , Unknown
}
 
typedef ScaledSingleValuedNonLinearOptimizer Superclass
 
- Public Types inherited from itk::ScaledSingleValuedNonLinearOptimizer
typedef SmartPointer< const Self > ConstPointer
 
typedef Superclass::CostFunctionType CostFunctionType
 
typedef Superclass::DerivativeType DerivativeType
 
typedef Superclass::MeasureType MeasureType
 
typedef Superclass::ParametersType ParametersType
 
typedef SmartPointer< Self > Pointer
 
typedef ScaledCostFunctionType::Pointer ScaledCostFunctionPointer
 
typedef ScaledSingleValuedCostFunction ScaledCostFunctionType
 
typedef NonLinearOptimizer::ScalesType ScalesType
 
typedef ScaledSingleValuedNonLinearOptimizer Self
 
typedef SingleValuedNonLinearOptimizer Superclass
 

Public Member Functions

virtual const BetaDefinitionType & GetBetaDefinition ()
 
virtual const char * GetClassName () const
 
virtual const DerivativeType & GetCurrentGradient ()
 
virtual unsigned long GetCurrentIteration () const
 
virtual double GetCurrentStepLength () const
 
virtual MeasureType GetCurrentValue () const
 
virtual double GetGradientMagnitudeTolerance () const
 
virtual bool GetInLineSearch () const
 
virtual unsigned long GetMaximumNumberOfIterations () const
 
virtual unsigned long GetMaxNrOfItWithoutImprovement () const
 
virtual const StopConditionType & GetStopCondition ()
 
virtual double GetValueTolerance () const
 
 itkGetModifiableObjectMacro (LineSearchOptimizer, LineSearchOptimizerType)
 
virtual void ResumeOptimization (void)
 
virtual void SetBetaDefinition (const BetaDefinitionType &arg)
 
virtual void SetGradientMagnitudeTolerance (double _arg)
 
virtual void SetLineSearchOptimizer (LineSearchOptimizerType *_arg)
 
virtual void SetMaximumNumberOfIterations (unsigned long _arg)
 
virtual void SetMaxNrOfItWithoutImprovement (unsigned long arg)
 
virtual void SetValueTolerance (double _arg)
 
void StartOptimization (void) override
 
virtual void StopOptimization (void)
 
- Public Member Functions inherited from itk::ScaledSingleValuedNonLinearOptimizer
virtual const char * GetClassName () const
 
const ParametersType & GetCurrentPosition (void) const override
 
virtual bool GetMaximize () const
 
virtual const ScaledCostFunctionType * GetScaledCostFunction ()
 
virtual const ParametersType & GetScaledCurrentPosition ()
 
bool GetUseScales (void) const
 
virtual void InitializeScales (void)
 
virtual void MaximizeOff ()
 
virtual void MaximizeOn ()
 
void SetCostFunction (CostFunctionType *costFunction) override
 
virtual void SetMaximize (bool _arg)
 
virtual void SetUseScales (bool arg)
 

Static Public Member Functions

static Pointer New ()
 
- Static Public Member Functions inherited from itk::ScaledSingleValuedNonLinearOptimizer
static Pointer New ()
 

Protected Member Functions

virtual void AddBetaDefinition (const BetaDefinitionType &name, ComputeBetaFunctionType function)
 
virtual double ComputeBeta (const DerivativeType &previousGradient, const DerivativeType &gradient, const ParametersType &previousSearchDir)
 
double ComputeBetaDY (const DerivativeType &previousGradient, const DerivativeType &gradient, const ParametersType &previousSearchDir)
 
double ComputeBetaDYHS (const DerivativeType &previousGradient, const DerivativeType &gradient, const ParametersType &previousSearchDir)
 
double ComputeBetaFR (const DerivativeType &previousGradient, const DerivativeType &gradient, const ParametersType &previousSearchDir)
 
double ComputeBetaHS (const DerivativeType &previousGradient, const DerivativeType &gradient, const ParametersType &previousSearchDir)
 
double ComputeBetaPR (const DerivativeType &previousGradient, const DerivativeType &gradient, const ParametersType &previousSearchDir)
 
double ComputeBetaSD (const DerivativeType &previousGradient, const DerivativeType &gradient, const ParametersType &previousSearchDir)
 
virtual void ComputeSearchDirection (const DerivativeType &previousGradient, const DerivativeType &gradient, ParametersType &searchDir)
 
 GenericConjugateGradientOptimizer ()
 
virtual void LineSearch (const ParametersType searchDir, double &step, ParametersType &x, MeasureType &f, DerivativeType &g)
 
void PrintSelf (std::ostream &os, Indent indent) const override
 
virtual void SetInLineSearch (bool _arg)
 
virtual bool TestConvergence (bool firstLineSearchDone)
 
 ~GenericConjugateGradientOptimizer () override
 
- Protected Member Functions inherited from itk::ScaledSingleValuedNonLinearOptimizer
virtual void GetScaledDerivative (const ParametersType &parameters, DerivativeType &derivative) const
 
virtual MeasureType GetScaledValue (const ParametersType &parameters) const
 
virtual void GetScaledValueAndDerivative (const ParametersType &parameters, MeasureType &value, DerivativeType &derivative) const
 
void PrintSelf (std::ostream &os, Indent indent) const override
 
 ScaledSingleValuedNonLinearOptimizer ()
 
void SetCurrentPosition (const ParametersType &param) override
 
virtual void SetScaledCurrentPosition (const ParametersType &parameters)
 
 ~ScaledSingleValuedNonLinearOptimizer () override
 

Protected Attributes

BetaDefinitionType m_BetaDefinition
 
BetaDefinitionMapType m_BetaDefinitionMap
 
DerivativeType m_CurrentGradient
 
unsigned long m_CurrentIteration
 
double m_CurrentStepLength
 
MeasureType m_CurrentValue
 
bool m_InLineSearch
 
bool m_PreviousGradientAndSearchDirValid
 
bool m_Stop
 
StopConditionType m_StopCondition
 
bool m_UseDefaultMaxNrOfItWithoutImprovement
 
- Protected Attributes inherited from itk::ScaledSingleValuedNonLinearOptimizer
ScaledCostFunctionPointer m_ScaledCostFunction
 
ParametersType m_ScaledCurrentPosition
 

Private Member Functions

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

Private Attributes

double m_GradientMagnitudeTolerance
 
LineSearchOptimizerPointer m_LineSearchOptimizer
 
unsigned long m_MaximumNumberOfIterations
 
unsigned long m_MaxNrOfItWithoutImprovement
 
double m_ValueTolerance
 

Member Typedef Documentation

◆ BetaDefinitionMapType

typedef std::map< BetaDefinitionType, ComputeBetaFunctionType > itk::GenericConjugateGradientOptimizer::BetaDefinitionMapType

Definition at line 72 of file itkGenericConjugateGradientOptimizer.h.

◆ BetaDefinitionType

typedef std::string itk::GenericConjugateGradientOptimizer::BetaDefinitionType

Definition at line 70 of file itkGenericConjugateGradientOptimizer.h.

◆ ComputeBetaFunctionType

typedef double(Self::* itk::GenericConjugateGradientOptimizer::ComputeBetaFunctionType) (const DerivativeType &, const DerivativeType &, const ParametersType &)

Typedef for a function that computes $\beta$, given the previousGradient, the current gradient, and the previous search direction

Definition at line 66 of file itkGenericConjugateGradientOptimizer.h.

◆ ConstPointer

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

Definition at line 48 of file itkGenericConjugateGradientOptimizer.h.

◆ CostFunctionType

typedef Superclass::CostFunctionType itk::GenericConjugateGradientOptimizer::CostFunctionType

Definition at line 56 of file itkGenericConjugateGradientOptimizer.h.

◆ DerivativeType

typedef Superclass::DerivativeType itk::GenericConjugateGradientOptimizer::DerivativeType

Definition at line 55 of file itkGenericConjugateGradientOptimizer.h.

◆ LineSearchOptimizerPointer

typedef LineSearchOptimizerType::Pointer itk::GenericConjugateGradientOptimizer::LineSearchOptimizerPointer

Definition at line 62 of file itkGenericConjugateGradientOptimizer.h.

◆ LineSearchOptimizerType

typedef LineSearchOptimizer itk::GenericConjugateGradientOptimizer::LineSearchOptimizerType

Definition at line 61 of file itkGenericConjugateGradientOptimizer.h.

◆ MeasureType

typedef Superclass::MeasureType itk::GenericConjugateGradientOptimizer::MeasureType

Definition at line 58 of file itkGenericConjugateGradientOptimizer.h.

◆ ParametersType

typedef Superclass::ParametersType itk::GenericConjugateGradientOptimizer::ParametersType

Definition at line 54 of file itkGenericConjugateGradientOptimizer.h.

◆ Pointer

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

Definition at line 47 of file itkGenericConjugateGradientOptimizer.h.

◆ ScaledCostFunctionType

typedef Superclass::ScaledCostFunctionType itk::GenericConjugateGradientOptimizer::ScaledCostFunctionType

Definition at line 57 of file itkGenericConjugateGradientOptimizer.h.

◆ ScalesType

typedef Superclass::ScalesType itk::GenericConjugateGradientOptimizer::ScalesType

Definition at line 59 of file itkGenericConjugateGradientOptimizer.h.

◆ Self

typedef GenericConjugateGradientOptimizer itk::GenericConjugateGradientOptimizer::Self

Definition at line 45 of file itkGenericConjugateGradientOptimizer.h.

◆ Superclass

typedef ScaledSingleValuedNonLinearOptimizer itk::GenericConjugateGradientOptimizer::Superclass

Definition at line 46 of file itkGenericConjugateGradientOptimizer.h.

Member Enumeration Documentation

◆ StopConditionType

enum itk::GenericConjugateGradientOptimizer::StopConditionType
Enumerator
MetricError 
LineSearchError 
MaximumNumberOfIterations 
GradientMagnitudeTolerance 
ValueTolerance 
InfiniteBeta 
Unknown 

Definition at line 74 of file itkGenericConjugateGradientOptimizer.h.

Constructor & Destructor Documentation

◆ GenericConjugateGradientOptimizer() [1/2]

itk::GenericConjugateGradientOptimizer::GenericConjugateGradientOptimizer ( )
protected

◆ ~GenericConjugateGradientOptimizer()

itk::GenericConjugateGradientOptimizer::~GenericConjugateGradientOptimizer ( )
inlineoverrideprotected

Definition at line 141 of file itkGenericConjugateGradientOptimizer.h.

◆ GenericConjugateGradientOptimizer() [2/2]

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

Member Function Documentation

◆ AddBetaDefinition()

virtual void itk::GenericConjugateGradientOptimizer::AddBetaDefinition ( const BetaDefinitionType &  name,
ComputeBetaFunctionType  function 
)
protectedvirtual

Function to add a new beta definition. The first argument should be a name via which a user can select this $\beta$ definition. The second argument is a pointer to a method that computes $\beta$. Called in the constructor of this class, and possibly by subclasses.

◆ ComputeBeta()

virtual double itk::GenericConjugateGradientOptimizer::ComputeBeta ( const DerivativeType &  previousGradient,
const DerivativeType &  gradient,
const ParametersType &  previousSearchDir 
)
protectedvirtual

Compute $\beta$ according to the user set $\beta$-definition

◆ ComputeBetaDY()

double itk::GenericConjugateGradientOptimizer::ComputeBetaDY ( const DerivativeType &  previousGradient,
const DerivativeType &  gradient,
const ParametersType &  previousSearchDir 
)
protected

"DaiYuan"

◆ ComputeBetaDYHS()

double itk::GenericConjugateGradientOptimizer::ComputeBetaDYHS ( const DerivativeType &  previousGradient,
const DerivativeType &  gradient,
const ParametersType &  previousSearchDir 
)
protected

"DaiYuanHestenesStiefel"

◆ ComputeBetaFR()

double itk::GenericConjugateGradientOptimizer::ComputeBetaFR ( const DerivativeType &  previousGradient,
const DerivativeType &  gradient,
const ParametersType &  previousSearchDir 
)
protected

"FletcherReeves"

◆ ComputeBetaHS()

double itk::GenericConjugateGradientOptimizer::ComputeBetaHS ( const DerivativeType &  previousGradient,
const DerivativeType &  gradient,
const ParametersType &  previousSearchDir 
)
protected

"HestenesStiefel"

◆ ComputeBetaPR()

double itk::GenericConjugateGradientOptimizer::ComputeBetaPR ( const DerivativeType &  previousGradient,
const DerivativeType &  gradient,
const ParametersType &  previousSearchDir 
)
protected

"PolakRibiere"

◆ ComputeBetaSD()

double itk::GenericConjugateGradientOptimizer::ComputeBetaSD ( const DerivativeType &  previousGradient,
const DerivativeType &  gradient,
const ParametersType &  previousSearchDir 
)
protected

Different definitions of $\beta$ "SteepestDescent: beta=0

◆ ComputeSearchDirection()

virtual void itk::GenericConjugateGradientOptimizer::ComputeSearchDirection ( const DerivativeType &  previousGradient,
const DerivativeType &  gradient,
ParametersType &  searchDir 
)
protectedvirtual

Compute the search direction:

\[ d_{k} = - g_{k} + \beta_{k} d_{k-1} \]

In the first iteration the search direction is computed as:

\[ d_{0} = - g_{0} \]

On calling, searchDir should equal $d_{k-1}$. On return searchDir equals $d_{k}$.

◆ GetBetaDefinition()

virtual const BetaDefinitionType & itk::GenericConjugateGradientOptimizer::GetBetaDefinition ( )
virtual

◆ GetClassName()

virtual const char * itk::GenericConjugateGradientOptimizer::GetClassName ( ) const
virtual

Reimplemented from itk::ScaledSingleValuedNonLinearOptimizer.

Reimplemented in elastix::ConjugateGradient< TElastix >.

◆ GetCurrentGradient()

virtual const DerivativeType & itk::GenericConjugateGradientOptimizer::GetCurrentGradient ( )
virtual

◆ GetCurrentIteration()

virtual unsigned long itk::GenericConjugateGradientOptimizer::GetCurrentIteration ( ) const
virtual

Get information about optimization process:

◆ GetCurrentStepLength()

virtual double itk::GenericConjugateGradientOptimizer::GetCurrentStepLength ( ) const
virtual

◆ GetCurrentValue()

virtual MeasureType itk::GenericConjugateGradientOptimizer::GetCurrentValue ( ) const
virtual

◆ GetGradientMagnitudeTolerance()

virtual double itk::GenericConjugateGradientOptimizer::GetGradientMagnitudeTolerance ( ) const
virtual

Setting: the mininum gradient magnitude. By default 1e-5.

The optimizer stops when: $ \|CurrentGradient\| < GradientMagnitudeTolerance * \max(1, \|CurrentPosition\| ) $

◆ GetInLineSearch()

virtual bool itk::GenericConjugateGradientOptimizer::GetInLineSearch ( ) const
virtual

◆ GetMaximumNumberOfIterations()

virtual unsigned long itk::GenericConjugateGradientOptimizer::GetMaximumNumberOfIterations ( ) const
virtual

Setting: the maximum number of iterations

◆ GetMaxNrOfItWithoutImprovement()

virtual unsigned long itk::GenericConjugateGradientOptimizer::GetMaxNrOfItWithoutImprovement ( ) const
virtual

◆ GetStopCondition()

virtual const StopConditionType & itk::GenericConjugateGradientOptimizer::GetStopCondition ( )
virtual

◆ GetValueTolerance()

virtual double itk::GenericConjugateGradientOptimizer::GetValueTolerance ( ) const
virtual

Setting: a stopping criterion, the value tolerance. By default 1e-5.

The optimizer stops when

\[ 2.0 * | f_k - f_{k-1} | \le ValueTolerance * ( |f_k| + |f_{k-1}| + 1e-20 ) \]

is satisfied MaxNrOfItWithoutImprovement times in a row.

◆ itkGetModifiableObjectMacro()

itk::GenericConjugateGradientOptimizer::itkGetModifiableObjectMacro ( LineSearchOptimizer  ,
LineSearchOptimizerType   
)

◆ LineSearch()

virtual void itk::GenericConjugateGradientOptimizer::LineSearch ( const ParametersType  searchDir,
double &  step,
ParametersType &  x,
MeasureType &  f,
DerivativeType &  g 
)
protectedvirtual

Perform a line search along the search direction. On calling, $x, f$, and $g$ should contain the current position, the cost function value at this position, and the derivative. On return the step, $x$ (new position), $f$ (value at $x$), and $g$ (derivative at $x$) are updated.

Reimplemented in elastix::ConjugateGradient< TElastix >.

◆ New()

static Pointer itk::GenericConjugateGradientOptimizer::New ( )
static

◆ operator=()

void itk::GenericConjugateGradientOptimizer::operator= ( const Self &  )
private

◆ PrintSelf()

void itk::GenericConjugateGradientOptimizer::PrintSelf ( std::ostream &  os,
Indent  indent 
) const
overrideprotected

◆ ResumeOptimization()

virtual void itk::GenericConjugateGradientOptimizer::ResumeOptimization ( void  )
virtual

◆ SetBetaDefinition()

virtual void itk::GenericConjugateGradientOptimizer::SetBetaDefinition ( const BetaDefinitionType &  arg)
virtual

Setting: the definition of $\beta$, by default "DaiYuanHestenesStiefel"

◆ SetGradientMagnitudeTolerance()

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

◆ SetInLineSearch()

virtual void itk::GenericConjugateGradientOptimizer::SetInLineSearch ( bool  _arg)
protectedvirtual

◆ SetLineSearchOptimizer()

virtual void itk::GenericConjugateGradientOptimizer::SetLineSearchOptimizer ( LineSearchOptimizerType *  _arg)
virtual

Setting: the line search optimizer

◆ SetMaximumNumberOfIterations()

virtual void itk::GenericConjugateGradientOptimizer::SetMaximumNumberOfIterations ( unsigned long  _arg)
virtual

◆ SetMaxNrOfItWithoutImprovement()

virtual void itk::GenericConjugateGradientOptimizer::SetMaxNrOfItWithoutImprovement ( unsigned long  arg)
virtual

Setting: the maximum number of iterations in a row that satisfy the value tolerance criterion. By default (if never set) equal to the number of parameters.

◆ SetValueTolerance()

virtual void itk::GenericConjugateGradientOptimizer::SetValueTolerance ( double  _arg)
virtual

◆ StartOptimization()

void itk::GenericConjugateGradientOptimizer::StartOptimization ( void  )
override

◆ StopOptimization()

virtual void itk::GenericConjugateGradientOptimizer::StopOptimization ( void  )
virtual

◆ TestConvergence()

virtual bool itk::GenericConjugateGradientOptimizer::TestConvergence ( bool  firstLineSearchDone)
protectedvirtual

Check if convergence has occured; The firstLineSearchDone bool allows the implementation of TestConvergence to decide to skip a few convergence checks when no line search has performed yet (so, before the actual optimisation begins)

Reimplemented in elastix::ConjugateGradient< TElastix >.

Field Documentation

◆ m_BetaDefinition

BetaDefinitionType itk::GenericConjugateGradientOptimizer::m_BetaDefinition
protected

The name of the BetaDefinition

Definition at line 167 of file itkGenericConjugateGradientOptimizer.h.

◆ m_BetaDefinitionMap

BetaDefinitionMapType itk::GenericConjugateGradientOptimizer::m_BetaDefinitionMap
protected

A mapping that links the names of the BetaDefinitions to functions that compute $\beta$.

Definition at line 171 of file itkGenericConjugateGradientOptimizer.h.

◆ m_CurrentGradient

DerivativeType itk::GenericConjugateGradientOptimizer::m_CurrentGradient
protected

Definition at line 145 of file itkGenericConjugateGradientOptimizer.h.

◆ m_CurrentIteration

unsigned long itk::GenericConjugateGradientOptimizer::m_CurrentIteration
protected

Definition at line 147 of file itkGenericConjugateGradientOptimizer.h.

◆ m_CurrentStepLength

double itk::GenericConjugateGradientOptimizer::m_CurrentStepLength
protected

Definition at line 150 of file itkGenericConjugateGradientOptimizer.h.

◆ m_CurrentValue

MeasureType itk::GenericConjugateGradientOptimizer::m_CurrentValue
protected

Definition at line 146 of file itkGenericConjugateGradientOptimizer.h.

◆ m_GradientMagnitudeTolerance

double itk::GenericConjugateGradientOptimizer::m_GradientMagnitudeTolerance
private

Definition at line 265 of file itkGenericConjugateGradientOptimizer.h.

◆ m_InLineSearch

bool itk::GenericConjugateGradientOptimizer::m_InLineSearch
protected

Is true when the LineSearchOptimizer has been started.

Definition at line 157 of file itkGenericConjugateGradientOptimizer.h.

◆ m_LineSearchOptimizer

LineSearchOptimizerPointer itk::GenericConjugateGradientOptimizer::m_LineSearchOptimizer
private

Definition at line 268 of file itkGenericConjugateGradientOptimizer.h.

◆ m_MaximumNumberOfIterations

unsigned long itk::GenericConjugateGradientOptimizer::m_MaximumNumberOfIterations
private

Definition at line 263 of file itkGenericConjugateGradientOptimizer.h.

◆ m_MaxNrOfItWithoutImprovement

unsigned long itk::GenericConjugateGradientOptimizer::m_MaxNrOfItWithoutImprovement
private

Definition at line 266 of file itkGenericConjugateGradientOptimizer.h.

◆ m_PreviousGradientAndSearchDirValid

bool itk::GenericConjugateGradientOptimizer::m_PreviousGradientAndSearchDirValid
protected

Flag that says if the previous gradient and search direction are known. Typically 'true' at the start of optimization, or when a stopped optimisation is resumed (in the latter case the previous gradient and search direction may of course still be valid, but to be safe it is assumed that they are not).

Definition at line 164 of file itkGenericConjugateGradientOptimizer.h.

◆ m_Stop

bool itk::GenericConjugateGradientOptimizer::m_Stop
protected

Definition at line 149 of file itkGenericConjugateGradientOptimizer.h.

◆ m_StopCondition

StopConditionType itk::GenericConjugateGradientOptimizer::m_StopCondition
protected

Definition at line 148 of file itkGenericConjugateGradientOptimizer.h.

◆ m_UseDefaultMaxNrOfItWithoutImprovement

bool itk::GenericConjugateGradientOptimizer::m_UseDefaultMaxNrOfItWithoutImprovement
protected

Flag that is true as long as the method SetMaxNrOfItWithoutImprovement is never called

Definition at line 154 of file itkGenericConjugateGradientOptimizer.h.

◆ m_ValueTolerance

double itk::GenericConjugateGradientOptimizer::m_ValueTolerance
private

Definition at line 264 of file itkGenericConjugateGradientOptimizer.h.


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