#include <itkGradientDescentOptimizer.h>
Inheritance diagram for itk::GradientDescentOptimizer:
Public Types | |
typedef GradientDescentOptimizer | Self |
typedef SingleValuedNonLinearOptimizer | Superclass |
typedef SmartPointer< Self > | Pointer |
typedef SmartPointer< const Self > | ConstPointer |
enum | StopConditionType { MaximumNumberOfIterations, MetricError } |
Public Member Functions | |
virtual const char * | GetClassName () const |
virtual void | AdvanceOneStep (void) |
void | StartOptimization (void) |
void | ResumeOptimization (void) |
void | StopOptimization (void) |
virtual void | SetLearningRate (double _arg) |
virtual double | GetLearningRate () const |
virtual void | SetNumberOfIterations (unsigned long _arg) |
virtual unsigned long | GetNumberOfIterations () const |
virtual unsigned int | GetCurrentIteration () const |
virtual double | GetValue () const |
virtual StopConditionType | GetStopCondition () const |
virtual const DerivativeType & | GetGradient () |
virtual bool | GetMaximize () const |
virtual void | SetMaximize (bool _arg) |
virtual void | MaximizeOn () |
virtual void | MaximizeOff () |
bool | GetMinimize () const |
void | SetMinimize (bool v) |
void | MinimizeOn () |
void | MinimizeOff () |
Static Public Member Functions | |
Pointer | New () |
Protected Member Functions | |
GradientDescentOptimizer () | |
virtual | ~GradientDescentOptimizer () |
void | PrintSelf (std::ostream &os, Indent indent) const |
Protected Attributes | |
DerivativeType | m_Gradient |
bool | m_Maximize |
double | m_LearningRate |
GradientDescentOptimizer implements a simple gradient descent optimizer. At each iteration the current position is updated according to
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 of the df / dp but setting a scaling vector using method SetScale().
Definition at line 48 of file itkGradientDescentOptimizer.h.
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Reimplemented from itk::SingleValuedNonLinearOptimizer.
Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer. Definition at line 56 of file itkGradientDescentOptimizer.h. |
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Reimplemented from itk::SingleValuedNonLinearOptimizer.
Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer. Definition at line 55 of file itkGradientDescentOptimizer.h. |
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Standard class typedefs. Reimplemented from itk::SingleValuedNonLinearOptimizer.
Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer. Definition at line 53 of file itkGradientDescentOptimizer.h. |
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Reimplemented from itk::SingleValuedNonLinearOptimizer.
Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer. Definition at line 54 of file itkGradientDescentOptimizer.h. |
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Codes of stopping conditions Definition at line 66 of file itkGradientDescentOptimizer.h. |
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Definition at line 126 of file itkGradientDescentOptimizer.h. |
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Advance one step following the gradient direction. Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer.
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Run-time type information (and related methods). Reimplemented from itk::SingleValuedNonLinearOptimizer.
Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer.
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Get the current iteration number. |
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Get Stop condition. |
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Get the learning rate. |
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Methods to configure the cost function. |
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Methods to configure the cost function. Definition at line 75 of file itkGradientDescentOptimizer.h. |
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Get the number of iterations. |
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Get Stop condition. |
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Get the current value. |
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Methods to configure the cost function. |
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Methods to configure the cost function. |
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Methods to configure the cost function. Definition at line 81 of file itkGradientDescentOptimizer.h. |
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Methods to configure the cost function. Definition at line 79 of file itkGradientDescentOptimizer.h. |
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Method for creation through the object factory. Reimplemented from itk::SingleValuedNonLinearOptimizer.
Reimplemented in itk::QuaternionRigidTransformGradientDescentOptimizer.
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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.
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Resume previously stopped optimization with current parameters
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Set the learning rate. |
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Methods to configure the cost function. |
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Methods to configure the cost function. Definition at line 77 of file itkGradientDescentOptimizer.h. |
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Set the number of iterations. |
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Start optimization. Reimplemented from itk::Optimizer.
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Stop optimization.
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Definition at line 131 of file itkGradientDescentOptimizer.h. |
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Definition at line 133 of file itkGradientDescentOptimizer.h. |
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Definition at line 132 of file itkGradientDescentOptimizer.h. |