ITK  4.1.0
Insight Segmentation and Registration Toolkit
Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Protected Attributes | Private Member Functions
itk::RegularStepGradientDescentBaseOptimizer Class Reference

#include <itkRegularStepGradientDescentBaseOptimizer.h>

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

List of all members.

Public Types

typedef SmartPointer< const SelfConstPointer
typedef SmartPointer< SelfPointer
typedef
RegularStepGradientDescentBaseOptimizer 
Self
enum  StopConditionType {
  GradientMagnitudeTolerance = 1,
  StepTooSmall = 2,
  ImageNotAvailable = 3,
  CostFunctionError = 4,
  MaximumNumberOfIterations = 5,
  Unknown = 6
}
typedef
SingleValuedNonLinearOptimizer 
Superclass

Public Member Functions

virtual ::itk::LightObject::Pointer CreateAnother (void) const
virtual const char * GetNameOfClass () const
virtual const std::string GetStopConditionDescription () const
void ResumeOptimization (void)
void StartOptimization (void)
void StopOptimization (void)
virtual void SetMaximize (bool _arg)
virtual const bool & GetMaximize ()
virtual void MaximizeOn ()
virtual void MaximizeOff ()
bool GetMinimize () const
void SetMinimize (bool v)
void MinimizeOn (void)
void MinimizeOff (void)
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 ()
virtual const double & GetMaximumStepLength ()
virtual const double & GetMinimumStepLength ()
virtual const double & GetRelaxationFactor ()
virtual const SizeValueTypeGetNumberOfIterations ()
virtual const double & GetGradientMagnitudeTolerance ()
virtual unsigned int GetCurrentIteration () const
virtual const StopConditionTypeGetStopCondition ()
virtual const MeasureTypeGetValue ()
virtual const DerivativeTypeGetGradient ()

Static Public Member Functions

static Pointer New ()

Protected Member Functions

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

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
StopConditionType m_StopCondition
std::ostringstream m_StopConditionDescription
MeasureType m_Value

Private Member Functions

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

Detailed Description

Implement a gradient descent optimizer.

Definition at line 32 of file itkRegularStepGradientDescentBaseOptimizer.h.


Member Typedef Documentation


Member Enumeration Documentation

Codes of stopping conditions.

Enumerator:
GradientMagnitudeTolerance 
StepTooSmall 
ImageNotAvailable 
CostFunctionError 
MaximumNumberOfIterations 
Unknown 

Definition at line 50 of file itkRegularStepGradientDescentBaseOptimizer.h.


Constructor & Destructor Documentation


Member Function Documentation

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

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.

virtual::itk::LightObject::Pointer itk::RegularStepGradientDescentBaseOptimizer::CreateAnother ( void  ) const [virtual]

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::SingleValuedNonLinearOptimizer.

Reimplemented in itk::VersorTransformOptimizer, itk::VersorRigid3DTransformOptimizer, and itk::RegularStepGradientDescentOptimizer.

Set/Get parameters to control the optimization process.

Set/Get parameters to control the optimization process.

Set/Get parameters to control the optimization process.

Set/Get parameters to control the optimization process.

Specify whether to minimize or maximize the cost function.

Set/Get parameters to control the optimization process.

Specify whether to minimize or maximize the cost function.

Definition at line 63 of file itkRegularStepGradientDescentBaseOptimizer.h.

Set/Get parameters to control the optimization process.

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

Run-time type information (and related methods).

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Reimplemented in itk::VersorTransformOptimizer, itk::VersorRigid3DTransformOptimizer, and itk::RegularStepGradientDescentOptimizer.

Set/Get parameters to control the optimization process.

Set/Get parameters to control the optimization process.

Set/Get parameters to control the optimization process.

Get the reason for termination

Reimplemented from itk::Optimizer.

Set/Get parameters to control the optimization process.

Specify whether to minimize or maximize the cost function.

Specify whether to minimize or maximize the cost function.

Specify whether to minimize or maximize the cost function.

Definition at line 69 of file itkRegularStepGradientDescentBaseOptimizer.h.

Specify whether to minimize or maximize the cost function.

Definition at line 67 of file itkRegularStepGradientDescentBaseOptimizer.h.

Method for creation through the object factory.

Reimplemented from itk::SingleValuedNonLinearOptimizer.

Reimplemented in itk::VersorTransformOptimizer, itk::VersorRigid3DTransformOptimizer, and itk::RegularStepGradientDescentOptimizer.

void itk::RegularStepGradientDescentBaseOptimizer::operator= ( const Self ) [private]
void itk::RegularStepGradientDescentBaseOptimizer::PrintSelf ( std::ostream &  os,
Indent  indent 
) const [protected, virtual]

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.

Resume previously stopped optimization with current parameters.

See also:
StopOptimization

Set/Get parameters to control the optimization process.

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

Specify whether to minimize or maximize the cost function.

Set/Get parameters to control the optimization process.

Specify whether to minimize or maximize the cost function.

Definition at line 65 of file itkRegularStepGradientDescentBaseOptimizer.h.

Set/Get parameters to control the optimization process.

Set/Get parameters to control the optimization process.

Set/Get parameters to control the optimization process.

Start optimization.

Reimplemented from itk::Optimizer.

virtual void itk::RegularStepGradientDescentBaseOptimizer::StepAlongGradient ( double  ,
const DerivativeType  
) [inline, protected, virtual]

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 overrided by optimization methods in non-vector spaces

See also:
AdvanceOneStep

Definition at line 120 of file itkRegularStepGradientDescentBaseOptimizer.h.

References itk::ExceptionObject::SetDescription(), and itk::ExceptionObject::SetLocation().

Stop optimization.

See also:
ResumeOptimization

Member Data Documentation


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