/usr/include/OTB-6.4/otbMRFOptimizerMetropolis.h is in libotb-dev 6.4.0+dfsg-1.
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* Copyright (C) 2005-2017 Centre National d'Etudes Spatiales (CNES)
*
* This file is part of Orfeo Toolbox
*
* https://www.orfeo-toolbox.org/
*
* 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
*
* 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 otbMRFOptimizerMetropolis_h
#define otbMRFOptimizerMetropolis_h
#include "otbMRFOptimizer.h"
#include "otbMath.h"
#include "itkNumericTraits.h"
#include "itkMersenneTwisterRandomVariateGenerator.h"
namespace otb
{
/**
* \class MRFOptimizerMetropolis
* \brief This is the optimizer class implementing the Metropolis algorithm
*
* This is one optimizer to be used in the MRF framework. This optimizer
* follows the metropolis algorithm to accept of reject the value proposed by the sampler.
*
* The MRFOptimizerMetropolis has one parameter corresponding to the temperature T used
* to accept or reject proposed values. The proposed value is accepted with a probability:
*
* \f[ e^{\frac{-\Delta E}{T}} \f]
*
*
* This class is meant to be used in the MRF framework with the otb::MarkovRandomFieldFilter
*
* \ingroup Markov
*
* \ingroup OTBMarkov
*/
class ITK_EXPORT MRFOptimizerMetropolis : public MRFOptimizer
{
public:
typedef MRFOptimizerMetropolis Self;
typedef MRFOptimizer Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
typedef Superclass::ParametersType ParametersType;
typedef itk::Statistics::MersenneTwisterRandomVariateGenerator RandomGeneratorType;
itkNewMacro(Self);
itkTypeMacro(MRFOptimizerMetropolis, MRFOptimizer);
/** Set parameter to a one array filled with paramVal.*/
void SetSingleParameter(double parameterVal)
{
this->m_Parameters.SetSize(1);
this->m_Parameters.Fill(parameterVal);
this->Modified();
}
inline bool Compute(double deltaEnergy) ITK_OVERRIDE
{
if (deltaEnergy < 0)
{
return true;
}
if (deltaEnergy == 0)
{
return false;
}
else
{
double proba = vcl_exp(-(deltaEnergy) / this->m_Parameters[0]);
if ((m_Generator->GetIntegerVariate() % 10000) < proba * 10000)
{
return true;
}
}
return false;
}
/** Methods to cancel random effects.*/
void InitializeSeed(int seed)
{
m_Generator->SetSeed(seed);
}
void InitializeSeed()
{
m_Generator->SetSeed();
}
protected:
MRFOptimizerMetropolis()
{
this->m_NumberOfParameters = 1;
this->m_Parameters.SetSize(1);
this->m_Parameters[0] = 1.0;
m_Generator = RandomGeneratorType::GetInstance();
m_Generator->SetSeed();
}
~MRFOptimizerMetropolis() ITK_OVERRIDE {}
RandomGeneratorType::Pointer m_Generator;
};
}
#endif
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