/*=========================================================================
 *
 *  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 itkThresholdSegmentationLevelSetFunction_hxx
#define itkThresholdSegmentationLevelSetFunction_hxx

#include "itkImageRegionIterator.h"
#include "itkGradientAnisotropicDiffusionImageFilter.h"
#include "itkLaplacianImageFilter.h"

namespace itk
{
template <typename TImageType, typename TFeatureImageType>
void
ThresholdSegmentationLevelSetFunction<TImageType, TFeatureImageType>::CalculateSpeedImage()
{
  typename GradientAnisotropicDiffusionImageFilter<TFeatureImageType, TFeatureImageType>::Pointer diffusion =
    GradientAnisotropicDiffusionImageFilter<TFeatureImageType, TFeatureImageType>::New();
  typename LaplacianImageFilter<TFeatureImageType, TFeatureImageType>::Pointer laplacian =
    LaplacianImageFilter<TFeatureImageType, TFeatureImageType>::New();

  ImageRegionIterator<FeatureImageType>      lit;
  ImageRegionConstIterator<FeatureImageType> fit(this->GetFeatureImage(),
                                                 this->GetFeatureImage()->GetRequestedRegion());
  ImageRegionIterator<ImageType>             sit(this->GetSpeedImage(), this->GetFeatureImage()->GetRequestedRegion());

  if (m_EdgeWeight != 0.0)
  {
    diffusion->SetInput(this->GetFeatureImage());
    diffusion->SetConductanceParameter(m_SmoothingConductance);
    diffusion->SetTimeStep(m_SmoothingTimeStep);
    diffusion->SetNumberOfIterations(m_SmoothingIterations);

    laplacian->SetInput(diffusion->GetOutput());
    laplacian->Update();

    lit = ImageRegionIterator<FeatureImageType>(laplacian->GetOutput(), this->GetFeatureImage()->GetRequestedRegion());
    lit.GoToBegin();
  }

  // Copy the meta information (spacing and origin) from the feature image
  this->GetSpeedImage()->CopyInformation(this->GetFeatureImage());

  // Calculate the speed image
  auto            upper_threshold = static_cast<ScalarValueType>(m_UpperThreshold);
  auto            lower_threshold = static_cast<ScalarValueType>(m_LowerThreshold);
  ScalarValueType mid = ((upper_threshold - lower_threshold) / 2.0) + lower_threshold;
  ScalarValueType threshold;
  for (fit.GoToBegin(), sit.GoToBegin(); !fit.IsAtEnd(); ++sit, ++fit)
  {
    if (static_cast<ScalarValueType>(fit.Get()) < mid)
    {
      threshold = fit.Get() - lower_threshold;
    }
    else
    {
      threshold = upper_threshold - fit.Get();
    }

    if (m_EdgeWeight != 0.0)
    {
      sit.Set(static_cast<ScalarValueType>(threshold + m_EdgeWeight * lit.Get()));
      ++lit;
    }
    else
    {
      sit.Set(static_cast<ScalarValueType>(threshold));
    }
  }
}
} // end namespace itk

#endif