itkGradientDescentOptimizerv4.h

Go to the documentation of this file.

/*=========================================================================
 *
 *  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 itkGradientDescentOptimizerv4_h
#define itkGradientDescentOptimizerv4_h
 
#include "itkGradientDescentOptimizerBasev4.h"
 
namespace itk
{
template <typename TInternalComputationValueType>
class ITK_TEMPLATE_EXPORT GradientDescentOptimizerv4Template
  : public GradientDescentOptimizerBasev4Template<TInternalComputationValueType>
{
public:
  ITK_DISALLOW_COPY_AND_MOVE(GradientDescentOptimizerv4Template);
  using Self = GradientDescentOptimizerv4Template;
  using Superclass = GradientDescentOptimizerBasev4Template<TInternalComputationValueType>;
  using Pointer = SmartPointer<Self>;
  using ConstPointer = SmartPointer<const Self>;
 
  itkOverrideGetNameOfClassMacro(GradientDescentOptimizerv4Template);
 
  itkNewMacro(Self);
 
 
  using InternalComputationValueType = TInternalComputationValueType;
 
  using typename Superclass::DerivativeType;
 
  using typename Superclass::MeasureType;
  using typename Superclass::IndexRangeType;
  using typename Superclass::ScalesType;
  using typename Superclass::ParametersType;
 
  itkSetMacro(LearningRate, TInternalComputationValueType);
  itkGetConstReferenceMacro(LearningRate, TInternalComputationValueType);
  itkSetMacro(MaximumStepSizeInPhysicalUnits, TInternalComputationValueType);
  itkGetConstReferenceMacro(MaximumStepSizeInPhysicalUnits, TInternalComputationValueType);
  itkSetMacro(DoEstimateLearningRateAtEachIteration, bool);
  itkGetConstReferenceMacro(DoEstimateLearningRateAtEachIteration, bool);
  itkBooleanMacro(DoEstimateLearningRateAtEachIteration);
  itkSetMacro(DoEstimateLearningRateOnce, bool);
  itkGetConstReferenceMacro(DoEstimateLearningRateOnce, bool);
  itkBooleanMacro(DoEstimateLearningRateOnce);
  itkSetMacro(MinimumConvergenceValue, TInternalComputationValueType);
 
  itkSetMacro(ConvergenceWindowSize, SizeValueType);
 
  itkGetConstReferenceMacro(ConvergenceValue, TInternalComputationValueType);
 
  itkSetMacro(ReturnBestParametersAndValue, bool);
  itkGetConstReferenceMacro(ReturnBestParametersAndValue, bool);
  itkBooleanMacro(ReturnBestParametersAndValue);
  void
  StartOptimization(bool doOnlyInitialization = false) override;
 
  void
  StopOptimization() override;
 
  void
  ResumeOptimization() override;
 
  virtual void
  EstimateLearningRate();
 
protected:
  virtual void
  AdvanceOneStep();
 
  void
  ModifyGradientByScalesOverSubRange(const IndexRangeType & subrange) override;
 
  void
  ModifyGradientByLearningRateOverSubRange(const IndexRangeType & subrange) override;
 
  GradientDescentOptimizerv4Template();
 
  ~GradientDescentOptimizerv4Template() override = default;
 
  void
  PrintSelf(std::ostream & os, Indent indent) const override;
 
 
  TInternalComputationValueType m_LearningRate{};
  TInternalComputationValueType m_MinimumConvergenceValue{};
  TInternalComputationValueType m_ConvergenceValue{};
 
  MeasureType    m_CurrentBestValue{};
  ParametersType m_BestParameters{};
 
  bool m_ReturnBestParametersAndValue{ false };
 
  DerivativeType m_PreviousGradient{};
 
private:
};
 
using GradientDescentOptimizerv4 = GradientDescentOptimizerv4Template<double>;
 
} // end namespace itk
 
#ifndef ITK_MANUAL_INSTANTIATION
#  include "itkGradientDescentOptimizerv4.hxx"
#endif
 
#endif