/*=========================================================================
 *
 *  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 itkDifferenceOfGaussiansGradientImageFilter_hxx
#define itkDifferenceOfGaussiansGradientImageFilter_hxx

#include <cmath>
#include "itkProgressReporter.h"
#include "itkImageRegionIterator.h"

namespace itk
{
template <typename TInputImage, typename TDataType>
DifferenceOfGaussiansGradientImageFilter<TInputImage, TDataType>::DifferenceOfGaussiansGradientImageFilter()
{
  itkDebugMacro("DifferenceOfGaussiansGradientImageFilter::DifferenceOfGaussiansGradientImageFilter() called");

  m_Width = 2;
}

template <typename TInputImage, typename TDataType>
void
DifferenceOfGaussiansGradientImageFilter<TInputImage, TDataType>::GenerateData()
{
  itkDebugMacro("DifferenceOfGaussiansGradientImageFilter::GenerateData() called");

  // Get the input and output pointers
  typename Superclass::InputImagePointer  inputPtr = const_cast<TInputImage *>(this->GetInput(0));
  typename Superclass::OutputImagePointer outputPtr = this->GetOutput(0);

  // Make sure we're getting everything
  inputPtr->SetRequestedRegionToLargestPossibleRegion();

  // How big is the input image?
  typename TInputImage::SizeType size = inputPtr->GetLargestPossibleRegion().GetSize();

  // Create a region object native to the output image type
  OutputImageRegionType outputRegion;

  // Resize the output region
  outputRegion.SetSize(size);

  // Set the largest legal region size (i.e. the size of the whole image)
  // to what we just defined
  outputPtr->SetBufferedRegion(outputRegion);
  outputPtr->Allocate();

  // Create a progress reporter
  ProgressReporter progress(this, 0, outputPtr->GetRequestedRegion().GetNumberOfPixels());

  // Create an iterator that will walk the output region
  using OutputIterator = ImageRegionIterator<TOutputImage>;

  OutputIterator outIt(outputPtr, outputPtr->GetRequestedRegion());

  // Define a few indices that will be used to translate from an input pixel
  // to an output pixel
  typename TOutputImage::IndexType outputIndex;
  typename TOutputImage::IndexType upperIndex;
  typename TOutputImage::IndexType lowerIndex;

  // walk the output image, and sample the input image
  for (; !outIt.IsAtEnd(); ++outIt)
  {
    // determine the index of the output pixel
    outputIndex = outIt.GetIndex();

    // is the current index an acceptable distance from the edges
    // of the image?
    bool isValidGrad = true;

    for (unsigned int i = 0; i < NDimensions; ++i)
    {
      const auto width = static_cast<int>(m_Width);
      const int  sizeDifference = static_cast<int>(size.m_InternalArray[i]) - width;

      if (!((outputIndex[i] < sizeDifference) && (outputIndex[i] >= width)))
      {
        isValidGrad = false;
      }
    }

    if (isValidGrad)
    {
      // We're in a safe position, so calculate the gradient for
      // each dimension
      for (unsigned int i = 0; i < NDimensions; ++i)
      {
        // Build the indices for each pixel
        for (unsigned int j = 0; j < NDimensions; ++j)
        {
          if (j == i)
          {
            upperIndex[j] = outputIndex[j] + static_cast<IndexValueType>(m_Width);
            lowerIndex[j] = outputIndex[j] - static_cast<IndexValueType>(m_Width);
          }
          else
          {
            upperIndex[j] = outputIndex[j];
            lowerIndex[j] = outputIndex[j];
          }
        }
        // Remember, output type is a covariant vector of TDataType
        outputPtr->GetPixel(outputIndex)[i] = inputPtr->GetPixel(upperIndex) - inputPtr->GetPixel(lowerIndex);
      }
    }
    else // We're not in a safe position, gradient is zero
    {
      for (unsigned int i = 0; i < NDimensions; ++i)
      {
        outputPtr->GetPixel(outputIndex)[i] = 0.0;
      }
    }
    progress.CompletedPixel();
  }

  itkDebugMacro("DifferenceOfGaussiansGradientImageFilter::GenerateData() finished");
}

template <typename TInputImage, typename TDataType>
void
DifferenceOfGaussiansGradientImageFilter<TInputImage, TDataType>::PrintSelf(std::ostream & os, Indent indent) const
{
  Superclass::PrintSelf(os, indent);

  os << indent << "Width is " << m_Width << std::endl;
}
} // namespace itk

#endif
