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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 itkConjugateGradientLineSearchOptimizerv4_h
#define itkConjugateGradientLineSearchOptimizerv4_h
#include "itkGradientDescentLineSearchOptimizerv4.h"
#include "itkOptimizerParameterScalesEstimator.h"
#include "itkWindowConvergenceMonitoringFunction.h"
namespace itk
{
/**
* \class ConjugateGradientLineSearchOptimizerv4Template
* \brief Conjugate gradient descent optimizer with a golden section line search for nonlinear optimization.
*
* ConjugateGradientLineSearchOptimizer implements a conjugate gradient descent optimizer
* that is followed by a line search to find the best value for the learning rate.
* At each iteration the current position is updated according to
*
* \f[
* p_{n+1} = p_n
* + \mbox{learningRateByGoldenSectionLineSearch}
* \, d
* \f]
*
* where d is defined as the Polak-Ribiere conjugate gradient.
*
* Options are identical to the superclass's.
*
* \ingroup ITKOptimizersv4
*/
template <typename TInternalComputationValueType>
class ITK_TEMPLATE_EXPORT ConjugateGradientLineSearchOptimizerv4Template
: public GradientDescentLineSearchOptimizerv4Template<TInternalComputationValueType>
{
public:
ITK_DISALLOW_COPY_AND_MOVE(ConjugateGradientLineSearchOptimizerv4Template);
/** Standard class type aliases. */
using Self = ConjugateGradientLineSearchOptimizerv4Template;
using Superclass = GradientDescentLineSearchOptimizerv4Template<TInternalComputationValueType>;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(ConjugateGradientLineSearchOptimizerv4Template);
/** New macro for creation of through a Smart Pointer */
itkNewMacro(Self);
/** It should be possible to derive the internal computation type from the class object. */
using InternalComputationValueType = TInternalComputationValueType;
/** Derivative type */
using typename Superclass::DerivativeType;
/** Metric type over which this class is templated */
using typename Superclass::MeasureType;
/** Type for the convergence checker */
using ConvergenceMonitoringType = itk::Function::WindowConvergenceMonitoringFunction<TInternalComputationValueType>;
void
StartOptimization(bool doOnlyInitialization = false) override;
protected:
/** Advance one Step following the gradient direction.
* Includes transform update. */
void
AdvanceOneStep() override;
/** Default constructor */
ConjugateGradientLineSearchOptimizerv4Template() = default;
/** Destructor */
~ConjugateGradientLineSearchOptimizerv4Template() override = default;
void
PrintSelf(std::ostream & os, Indent indent) const override;
private:
DerivativeType m_LastGradient{};
DerivativeType m_ConjugateGradient{};
};
/** This helps to meet backward compatibility */
using ConjugateGradientLineSearchOptimizerv4 = ConjugateGradientLineSearchOptimizerv4Template<double>;
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
# include "itkConjugateGradientLineSearchOptimizerv4.hxx"
#endif
#endif
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