/*=========================================================================
 *
 *  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 itkCurvesLevelSetFunction_hxx
#define itkCurvesLevelSetFunction_hxx

#include "itkMath.h"
#include "itkImageRegionIterator.h"
#include "itkGradientRecursiveGaussianImageFilter.h"
#include "itkGradientImageFilter.h"
#include "itkCastImageFilter.h"
#include "itkImageAlgorithm.h"

namespace itk
{
template <typename TImageType, typename TFeatureImageType>
void
CurvesLevelSetFunction<TImageType, TFeatureImageType>::Initialize(const RadiusType & r)
{
  Superclass::Initialize(r);

  this->SetAdvectionWeight(NumericTraits<ScalarValueType>::OneValue());
  this->SetPropagationWeight(NumericTraits<ScalarValueType>::OneValue());
  this->SetCurvatureWeight(NumericTraits<ScalarValueType>::OneValue());
}

template <typename TImageType, typename TFeatureImageType>
void
CurvesLevelSetFunction<TImageType, TFeatureImageType>::CalculateSpeedImage()
{
  /* copy the feature image into the speed image */
  ImageAlgorithm::Copy(this->GetFeatureImage(),
                       this->GetSpeedImage(),
                       this->GetFeatureImage()->GetRequestedRegion(),
                       this->GetFeatureImage()->GetRequestedRegion());
}

template <typename TImageType, typename TFeatureImageType>
void
CurvesLevelSetFunction<TImageType, TFeatureImageType>::CalculateAdvectionImage()
{
  /* compute the gradient of the feature image. */

  typename VectorImageType::Pointer gradientImage;

  if (Math::NotAlmostEquals(m_DerivativeSigma, 0.0f))
  {
    using DerivativeFilterType = GradientRecursiveGaussianImageFilter<FeatureImageType, VectorImageType>;

    auto derivative = DerivativeFilterType::New();
    derivative->SetInput(this->GetFeatureImage());
    derivative->SetSigma(m_DerivativeSigma);
    derivative->Update();

    gradientImage = derivative->GetOutput();
  }
  else
  {
    using DerivativeFilterType = GradientImageFilter<FeatureImageType>;

    auto derivative = DerivativeFilterType::New();
    derivative->SetInput(this->GetFeatureImage());
    derivative->UseImageSpacingOn();
    derivative->Update();

    using DerivativeOutputImageType = typename DerivativeFilterType::OutputImageType;
    using GradientCasterType = CastImageFilter<DerivativeOutputImageType, VectorImageType>;

    auto caster = GradientCasterType::New();
    caster->SetInput(derivative->GetOutput());
    caster->Update();

    gradientImage = caster->GetOutput();
  }

  /* copy negative gradient into the advection image. */
  ImageRegionIterator<VectorImageType> dit(gradientImage, this->GetFeatureImage()->GetRequestedRegion());
  ImageRegionIterator<VectorImageType> ait(this->GetAdvectionImage(), this->GetFeatureImage()->GetRequestedRegion());

  for (dit.GoToBegin(), ait.GoToBegin(); !dit.IsAtEnd(); ++dit, ++ait)
  {
    typename VectorImageType::PixelType v = dit.Get();
    for (unsigned int j = 0; j < ImageDimension; ++j)
    {
      v[j] *= -1.0L;
    }
    ait.Set(v);
  }
}
} // end namespace itk

#endif