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/*=========================================================================
*
* Copyright NumFOCUS
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
#ifndef itkRegularStepGradientDescentBaseOptimizer_h
#define itkRegularStepGradientDescentBaseOptimizer_h
#include "itkIntTypes.h"
#include "itkSingleValuedNonLinearOptimizer.h"
#include "ITKOptimizersExport.h"
namespace itk
{
/** \class RegularStepGradientDescentBaseOptimizerEnums
*\brief Contains all enum classes for RegularStepGradientDescentBaseOptimizer class.
* \ingroup ITKOptimizers
*/
class RegularStepGradientDescentBaseOptimizerEnums
{
public:
/** \class StopCondition
*
* \ingroup ITKOptimizers
* Codes of stopping conditions. */
enum class StopCondition : uint8_t
{
GradientMagnitudeTolerance = 1,
StepTooSmall = 2,
ImageNotAvailable = 3,
CostFunctionError = 4,
MaximumNumberOfIterations = 5,
Unknown = 6
};
};
// Define how to print enumeration
extern ITKOptimizers_EXPORT std::ostream &
operator<<(std::ostream & out, const RegularStepGradientDescentBaseOptimizerEnums::StopCondition value);
/** \class RegularStepGradientDescentBaseOptimizer
* \brief Implement a gradient descent optimizer
*
* \ingroup Numerics Optimizers
* \ingroup ITKOptimizers
*/
class ITKOptimizers_EXPORT RegularStepGradientDescentBaseOptimizer : public SingleValuedNonLinearOptimizer
{
public:
ITK_DISALLOW_COPY_AND_MOVE(RegularStepGradientDescentBaseOptimizer);
/** Standard "Self" type alias. */
using Self = RegularStepGradientDescentBaseOptimizer;
using Superclass = SingleValuedNonLinearOptimizer;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(RegularStepGradientDescentBaseOptimizer);
using StopConditionEnum = RegularStepGradientDescentBaseOptimizerEnums::StopCondition;
#if !defined(ITK_LEGACY_REMOVE)
// We need to expose the enum values at the class level
// for backwards compatibility
static constexpr StopConditionEnum GradientMagnitudeTolerance = StopConditionEnum::GradientMagnitudeTolerance;
static constexpr StopConditionEnum StepTooSmall = StopConditionEnum::StepTooSmall;
static constexpr StopConditionEnum ImageNotAvailable = StopConditionEnum::ImageNotAvailable;
static constexpr StopConditionEnum CostFunctionError = StopConditionEnum::CostFunctionError;
static constexpr StopConditionEnum MaximumNumberOfIterations = StopConditionEnum::MaximumNumberOfIterations;
static constexpr StopConditionEnum Unknown = StopConditionEnum::Unknown;
#endif
/** Specify whether to minimize or maximize the cost function. */
itkSetMacro(Maximize, bool);
itkGetConstReferenceMacro(Maximize, bool);
itkBooleanMacro(Maximize);
bool
GetMinimize() const
{
return !m_Maximize;
}
void
SetMinimize(bool v)
{
this->SetMaximize(!v);
}
void
MinimizeOn()
{
SetMaximize(false);
}
void
MinimizeOff()
{
SetMaximize(true);
}
/** Start optimization. */
void
StartOptimization() override;
/** Resume previously stopped optimization with current parameters.
* \sa StopOptimization */
void
ResumeOptimization();
/** Stop optimization.
* \sa ResumeOptimization */
void
StopOptimization();
/** Set/Get parameters to control the optimization process. */
itkSetMacro(MaximumStepLength, double);
itkSetMacro(MinimumStepLength, double);
itkSetMacro(RelaxationFactor, double);
itkSetMacro(NumberOfIterations, SizeValueType);
itkSetMacro(GradientMagnitudeTolerance, double);
itkGetConstReferenceMacro(CurrentStepLength, double);
itkGetConstReferenceMacro(MaximumStepLength, double);
itkGetConstReferenceMacro(MinimumStepLength, double);
itkGetConstReferenceMacro(RelaxationFactor, double);
itkGetConstReferenceMacro(NumberOfIterations, SizeValueType);
itkGetConstReferenceMacro(GradientMagnitudeTolerance, double);
itkGetConstMacro(CurrentIteration, unsigned int);
itkGetConstReferenceMacro(StopCondition, StopConditionEnum);
itkGetConstReferenceMacro(Value, MeasureType);
itkGetConstReferenceMacro(Gradient, DerivativeType);
/** Get the reason for termination */
const std::string
GetStopConditionDescription() const override;
protected:
RegularStepGradientDescentBaseOptimizer();
~RegularStepGradientDescentBaseOptimizer() override = default;
void
PrintSelf(std::ostream & os, Indent indent) const override;
/** 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 void
AdvanceOneStep();
/** 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
* \sa AdvanceOneStep */
virtual void
StepAlongGradient(double, const DerivativeType &)
{
ExceptionObject ex;
ex.SetLocation(__FILE__);
ex.SetDescription("This method MUST be overloaded in derived classes");
throw ex;
}
private:
protected:
DerivativeType m_Gradient{};
DerivativeType m_PreviousGradient{};
bool m_Stop{ false };
bool m_Maximize{};
MeasureType m_Value{};
double m_GradientMagnitudeTolerance{};
double m_MaximumStepLength{};
double m_MinimumStepLength{};
double m_CurrentStepLength{};
double m_RelaxationFactor{};
StopConditionEnum m_StopCondition{};
SizeValueType m_NumberOfIterations{};
SizeValueType m_CurrentIteration{};
std::ostringstream m_StopConditionDescription{};
};
} // end namespace itk
#endif
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