/*=========================================================================
 *
 *  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 itkContourDirectedMeanDistanceImageFilter_hxx
#define itkContourDirectedMeanDistanceImageFilter_hxx


#include "itkConstNeighborhoodIterator.h"
#include "itkNeighborhoodInnerProduct.h"
#include "itkNeighborhoodAlgorithm.h"
#include "itkOffset.h"
#include "itkImageRegionIterator.h"
#include "itkSignedMaurerDistanceMapImageFilter.h"
#include "itkProgressReporter.h"
#include "itkMacro.h"
#include "itkMath.h"

namespace itk
{
template <typename TInputImage1, typename TInputImage2>
ContourDirectedMeanDistanceImageFilter<TInputImage1, TInputImage2>::ContourDirectedMeanDistanceImageFilter()
  : m_DistanceMap(nullptr)
  , m_MeanDistance(1)
  , m_Count(1)
  , m_ContourDirectedMeanDistance(RealType{})
{
  // this filter requires two input images
  this->SetNumberOfRequiredInputs(2);
  this->DynamicMultiThreadingOff();
}

template <typename TInputImage1, typename TInputImage2>
void
ContourDirectedMeanDistanceImageFilter<TInputImage1, TInputImage2>::SetInput1(const InputImage1Type * image)
{
  this->SetInput(image);
}

template <typename TInputImage1, typename TInputImage2>
void
ContourDirectedMeanDistanceImageFilter<TInputImage1, TInputImage2>::SetInput2(const TInputImage2 * image)
{
  this->SetNthInput(1, const_cast<TInputImage2 *>(image));
}

template <typename TInputImage1, typename TInputImage2>
auto
ContourDirectedMeanDistanceImageFilter<TInputImage1, TInputImage2>::GetInput1() -> const InputImage1Type *
{
  return this->GetInput();
}

template <typename TInputImage1, typename TInputImage2>
auto
ContourDirectedMeanDistanceImageFilter<TInputImage1, TInputImage2>::GetInput2() -> const InputImage2Type *
{
  return itkDynamicCastInDebugMode<const TInputImage2 *>(this->ProcessObject::GetInput(1));
}

template <typename TInputImage1, typename TInputImage2>
void
ContourDirectedMeanDistanceImageFilter<TInputImage1, TInputImage2>::GenerateInputRequestedRegion()
{
  Superclass::GenerateInputRequestedRegion();

  // this filter requires:
  // - the largest possible region of the first image
  // - the corresponding region of the second image
  if (this->GetInput1())
  {
    const InputImage1Pointer image1 = const_cast<InputImage1Type *>(this->GetInput1());
    image1->SetRequestedRegionToLargestPossibleRegion();

    if (this->GetInput2())
    {
      const InputImage2Pointer image2 = const_cast<InputImage2Type *>(this->GetInput2());
      image2->SetRequestedRegion(this->GetInput1()->GetRequestedRegion());
    }
  }
}

template <typename TInputImage1, typename TInputImage2>
void
ContourDirectedMeanDistanceImageFilter<TInputImage1, TInputImage2>::EnlargeOutputRequestedRegion(DataObject * data)
{
  Superclass::EnlargeOutputRequestedRegion(data);
  data->SetRequestedRegionToLargestPossibleRegion();
}

template <typename TInputImage1, typename TInputImage2>
void
ContourDirectedMeanDistanceImageFilter<TInputImage1, TInputImage2>::AllocateOutputs()
{
  // Pass the first input through as the output
  const InputImage1Pointer image = const_cast<TInputImage1 *>(this->GetInput1());

  this->GraftOutput(image);
}

template <typename TInputImage1, typename TInputImage2>
void
ContourDirectedMeanDistanceImageFilter<TInputImage1, TInputImage2>::BeforeThreadedGenerateData()
{
  const ThreadIdType numberOfWorkUnits = this->GetNumberOfWorkUnits();

  // Resize the thread temporaries
  m_MeanDistance.SetSize(numberOfWorkUnits);
  m_Count.SetSize(numberOfWorkUnits);

  // Initialize the temporaries
  m_MeanDistance.Fill(RealType{});
  m_Count.Fill(0);

  // Compute Signed distance from non-zero pixels in the second image
  using FilterType = SignedMaurerDistanceMapImageFilter<InputImage2Type, DistanceMapType>;

  auto filter = FilterType::New();

  filter->SetInput(this->GetInput2());
  filter->SetSquaredDistance(false);
  filter->SetUseImageSpacing(m_UseImageSpacing);
  filter->Update();

  m_DistanceMap = filter->GetOutput();
}

template <typename TInputImage1, typename TInputImage2>
void
ContourDirectedMeanDistanceImageFilter<TInputImage1, TInputImage2>::AfterThreadedGenerateData()
{
  const ThreadIdType numberOfWorkUnits = this->GetNumberOfWorkUnits();

  // Find mean over all threads
  IdentifierType count = 0;
  RealType       sum{};

  for (ThreadIdType i = 0; i < numberOfWorkUnits; ++i)
  {
    sum += m_MeanDistance[i];
    count += m_Count[i];
  }
  if (count != 0)
  {
    m_ContourDirectedMeanDistance = sum / static_cast<RealType>(count);
  }
  else
  {
    m_ContourDirectedMeanDistance = RealType{};
  }
}

template <typename TInputImage1, typename TInputImage2>
void
ContourDirectedMeanDistanceImageFilter<TInputImage1, TInputImage2>::ThreadedGenerateData(
  const RegionType & outputRegionForThread,
  ThreadIdType       threadId)
{
  ZeroFluxNeumannBoundaryCondition<InputImage1Type> nbc;

  ConstNeighborhoodIterator<InputImage1Type> bit;

  const InputImage1ConstPointer input = this->GetInput();

  // Find the data-set boundary "faces"
  constexpr auto radius = SizeType::Filled(1);

  using FaceListType = typename NeighborhoodAlgorithm::ImageBoundaryFacesCalculator<InputImage1Type>::FaceListType;

  NeighborhoodAlgorithm::ImageBoundaryFacesCalculator<InputImage1Type> bC;
  const FaceListType faceList = bC(input, outputRegionForThread, radius);

  // Support progress methods/callbacks
  ProgressReporter progress(this, threadId, outputRegionForThread.GetNumberOfPixels());

  // Process each of the boundary faces.  These are N-d regions which border
  // the edge of the buffer.
  for (const auto & face : faceList)
  {
    ImageRegionConstIterator<DistanceMapType> it2(m_DistanceMap, face);
    bit = ConstNeighborhoodIterator<InputImage1Type>(radius, input, face);
    const unsigned int neighborhoodSize = bit.Size();

    bit.OverrideBoundaryCondition(&nbc);
    bit.GoToBegin();

    while (!bit.IsAtEnd())
    {
      // First test
      // If current pixel is not on, let's continue
      if (Math::NotExactlyEquals(bit.GetCenterPixel(), InputImage1PixelType{}))
      {
        bool bIsOnContour = false;

        for (unsigned int i = 0; i < neighborhoodSize; ++i)
        {
          // Second test if at least one neighbour pixel is off
          // the center pixel belongs to contour
          if (Math::ExactlyEquals(bit.GetPixel(i), InputImage1PixelType{}))
          {
            bIsOnContour = true;
            break;
          }
        }

        // Set pixel center pixel value whether it is or not on contour
        if (bIsOnContour)
        {
          const RealType value = it2.Get();
          m_MeanDistance[threadId] += itk::Math::Absolute(value);
          m_Count[threadId]++;
        }
      }
      ++bit;
      ++it2;
      progress.CompletedPixel();
    }
  }
}

template <typename TInputImage1, typename TInputImage2>
void
ContourDirectedMeanDistanceImageFilter<TInputImage1, TInputImage2>::PrintSelf(std::ostream & os, Indent indent) const
{
  Superclass::PrintSelf(os, indent);

  itkPrintSelfBooleanMacro(UseImageSpacing);
  os << indent << "ContourDirectedMeanDistance: " << m_ContourDirectedMeanDistance << std::endl;
}
} // end namespace itk
#endif
