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/*=========================================================================
*
* Copyright UMC Utrecht and contributors
*
* 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
*
* http://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 elxSimultaneousPerturbation_h
#define elxSimultaneousPerturbation_h
#include "elxIncludes.h" // include first to avoid MSVS warning
#include "itkSPSAOptimizer.h"
namespace elastix
{
/**
* \class SimultaneousPerturbation
* \brief An optimizer based on the itk::SPSAOptimizer.
*
* The ITK doxygen help gives more information about this optimizer.
*
* This optimizer supports the NewSamplesEveryIteration parameter.
*
* The parameters used in this class are:
* \parameter Optimizer: Select this optimizer as follows:\n
* <tt>(Optimizer "SimultaneousPerturbation")</tt>
* \parameter MaximumNumberOfIterations: The maximum number of iterations in each resolution. \n
* example: <tt>(MaximumNumberOfIterations 100 100 50)</tt> \n
* Default value: 500.
* \parameter NumberOfPerturbations: The number of perturbation used to
* construct a gradient estimate \f$g_k\f$. \n
* \f$q =\f$ NumberOfPerturbations \n
* \f$g_k = 1/q \sum_{j = 1..q} g^(j)_k\f$ \n
* This parameter can be defined for each resolution. \n
* example: <tt>(NumberOfPerturbations 1 1 2)</tt> \n
* Default value: 1.
* \parameter SP_a: The gain \f$a(k)\f$ at each iteration \f$k\f$ is defined by \n
* \f$a(k) = SP\_a / (SP\_A + k + 1)^{SP\_alpha}\f$. \n
* SP_a can be defined for each resolution. \n
* example: <tt>(SP_a 3200.0 3200.0 1600.0)</tt> \n
* The default value is 400.0. Tuning this variable for you specific problem is recommended.
* \parameter SP_A: The gain \f$a(k)\f$ at each iteration \f$k\f$ is defined by \n
* \f$a(k) = SP\_a / (SP\_A + k + 1)^{SP\_alpha}\f$. \n
* SP_A can be defined for each resolution. \n
* example: <tt>(SP_A 50.0 50.0 100.0)</tt> \n
* The default/recommended value is 50.0.
* \parameter SP_alpha: The gain \f$a(k)\f$ at each iteration \f$k\f$ is defined by \n
* \f$a(k) = SP\_a / (SP\_A + k + 1)^{SP\_alpha}\f$. \n
* SP_alpha can be defined for each resolution. \n
* example: <tt>(SP_alpha 0.602 0.602 0.602)</tt> \n
* The default/recommended value is 0.602.
* \parameter SP_c: The perturbation step size \f$c(k)\f$ at each iteration \f$k\f$ is defined by \n
* \f$c(k) = SP\_c / ( k + 1)^{SP\_gamma}\f$. \n
* SP_c can be defined for each resolution. \n
* example: <tt>(SP_c 2.0 1.0 1.0)</tt> \n
* The default value is 1.0.
* \parameter SP_gamma: The perturbation step size \f$c(k)\f$ at each iteration \f$k\f$ is defined by \n
* \f$c(k) = SP\_c / ( k + 1)^{SP\_gamma}\f$. \n
* SP_gamma can be defined for each resolution. \n
* example: <tt>(SP_gamma 0.101 0.101 0.101)</tt> \n
* The default/recommended value is 0.101.
* \parameter ShowMetricValues: Defines whether to compute/show the metric value in each iteration. \n
* This flag can NOT be defined for each resolution. \n
* example: <tt>(ShowMetricValues "true" )</tt> \n
* Default value: "false". Note that turning this flag on increases computation time.
*
*
* \ingroup Optimizers
*/
template <class TElastix>
class ITK_TEMPLATE_EXPORT SimultaneousPerturbation
: public itk::SPSAOptimizer
, public OptimizerBase<TElastix>
{
public:
ITK_DISALLOW_COPY_AND_MOVE(SimultaneousPerturbation);
/** Standard ITK.*/
using Self = SimultaneousPerturbation;
using Superclass1 = SPSAOptimizer;
using Superclass2 = OptimizerBase<TElastix>;
using Pointer = itk::SmartPointer<Self>;
using ConstPointer = itk::SmartPointer<const Self>;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Run-time type information (and related methods). */
itkTypeMacro(SimultaneousPerturbation, SPSAOptimizer);
/** Name of this class.
* Use this name in the parameter file to select this specific optimizer. \n
* example: <tt>(Optimizer "SimultaneousPerturbation")</tt>\n
*/
elxClassNameMacro("SimultaneousPerturbation");
/** Typedef's inherited from Superclass1.*/
using Superclass1::CostFunctionType;
using Superclass1::CostFunctionPointer;
/** Typedef's inherited from Elastix.*/
using typename Superclass2::ElastixType;
using typename Superclass2::RegistrationType;
using ITKBaseType = typename Superclass2::ITKBaseType;
/** Typedef for the ParametersType. */
using typename Superclass1::ParametersType;
/** Methods that take care of setting parameters and printing progress information.*/
void
BeforeRegistration() override;
void
BeforeEachResolution() override;
void
AfterEachResolution() override;
void
AfterEachIteration() override;
void
AfterRegistration() override;
/** Override the SetInitialPosition.
* Override the implementation in itkOptimizer.h, to
* ensure that the scales array and the parameters
* array have the same size. */
void
SetInitialPosition(const ParametersType & param) override;
protected:
SimultaneousPerturbation();
~SimultaneousPerturbation() override = default;
bool m_ShowMetricValues;
private:
elxOverrideGetSelfMacro;
};
} // end namespace elastix
#ifndef ITK_MANUAL_INSTANTIATION
# include "elxSimultaneousPerturbation.hxx"
#endif
#endif // end #ifndef elxSimultaneousPerturbation_h
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