/*
 * Copyright (C) 2005-2019 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 otbMRFSamplerRandom_h
#define otbMRFSamplerRandom_h

#include "otbMRFSampler.h"
#include "itkMersenneTwisterRandomVariateGenerator.h"
#include "itkNumericTraits.h"

namespace otb
{
/**
   * \class MRFSamplerRandom
   * \brief This is the base class for sampler methods used in the MRF framework.
   *
   * This is one sampler to be used int he MRF framework. This sampler select the
   * value randomly according to a uniform probability.
   *
   *
   * This class is meant to be used in the MRF framework with the otb::MarkovRandomFieldFilter
   *
   * \ingroup Markov
 *
 * \ingroup OTBMarkov
 */

template <class TInput1, class TInput2>
class ITK_EXPORT MRFSamplerRandom : public MRFSampler<TInput1, TInput2>
{
public:
  typedef MRFSamplerRandom Self;
  typedef otb::MRFSampler<TInput1, TInput2> Superclass;
  typedef itk::SmartPointer<Self>       Pointer;
  typedef itk::SmartPointer<const Self> ConstPointer;

  typedef typename Superclass::InputImageNeighborhoodIterator    InputImageNeighborhoodIterator;
  typedef typename Superclass::LabelledImageNeighborhoodIterator LabelledImageNeighborhoodIterator;
  typedef typename Superclass::LabelledImagePixelType            LabelledImagePixelType;
  typedef typename Superclass::InputImagePixelType               InputImagePixelType;
  typedef typename Superclass::EnergyFidelityType                EnergyFidelityType;
  typedef typename Superclass::EnergyRegularizationType          EnergyRegularizationType;
  typedef typename Superclass::EnergyFidelityPointer             EnergyFidelityPointer;
  typedef typename Superclass::EnergyRegularizationPointer       EnergyRegularizationPointer;

  typedef itk::Statistics::MersenneTwisterRandomVariateGenerator RandomGeneratorType;

  itkNewMacro(Self);

  itkTypeMacro(MRFSamplerRandom, MRFSampler);

  inline int Compute(const InputImageNeighborhoodIterator& itData, const LabelledImageNeighborhoodIterator& itRegul) override
  {
    this->m_EnergyBefore = this->m_EnergyFidelity->GetValue(itData, itRegul.GetCenterPixel());
    this->m_EnergyBefore += this->m_Lambda * this->m_EnergyRegularization->GetValue(itRegul, itRegul.GetCenterPixel());

    this->m_Value       = static_cast<LabelledImagePixelType>(m_Generator->GetIntegerVariate() % this->m_NumberOfClasses);
    this->m_EnergyAfter = this->m_EnergyFidelity->GetValue(itData, this->m_Value);
    this->m_EnergyAfter += this->m_Lambda * this->m_EnergyRegularization->GetValue(itRegul, this->m_Value);
    this->m_DeltaEnergy = this->m_EnergyAfter - this->m_EnergyBefore;

    return 0;
  }

  /** Methods to cancel random effects.*/
  void InitializeSeed(int seed)
  {
    m_Generator->SetSeed(seed);
  }
  void InitializeSeed()
  {
    m_Generator->SetSeed();
  }

protected:
  // The constructor and destructor.
  MRFSamplerRandom()
  {
    m_Generator = RandomGeneratorType::GetInstance();
    m_Generator->SetSeed();
  }
  ~MRFSamplerRandom() override
  {
  }

private:
  RandomGeneratorType::Pointer m_Generator;
};
}

#endif