/*=========================================================================
 *
 *  Copyright Insight Software Consortium
 *
 *  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.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 itkScalarAnisotropicDiffusionFunction_hxx
#define itkScalarAnisotropicDiffusionFunction_hxx

#include "itkConstNeighborhoodIterator.h"
#include "itkNeighborhoodInnerProduct.h"
#include "itkNeighborhoodAlgorithm.h"
#include "itkDerivativeOperator.h"
#include "itkScalarAnisotropicDiffusionFunction.h"

namespace itk
{
template< typename TImage >
void
ScalarAnisotropicDiffusionFunction< TImage >
::CalculateAverageGradientMagnitudeSquared(TImage *ip)
{
  using RNI_type = ConstNeighborhoodIterator<TImage>;
  using SNI_type = ConstNeighborhoodIterator<TImage>;
  using BFC_type = NeighborhoodAlgorithm::ImageBoundaryFacesCalculator<TImage>;
  using AccumulateType = typename NumericTraits<PixelType>::AccumulateType;

  unsigned int                               i;
  ZeroFluxNeumannBoundaryCondition< TImage > bc;
  AccumulateType                             accumulator;
  PixelRealType                              val;
  SizeValueType                              counter;
  BFC_type                                   bfc;
  typename BFC_type::FaceListType faceList;
  typename RNI_type::RadiusType radius;
  typename BFC_type::FaceListType::iterator fit;

  RNI_type iterator_list[ImageDimension];
  SNI_type face_iterator_list[ImageDimension];
  DerivativeOperator< PixelType,
                      ImageDimension > operator_list[ImageDimension];

  SizeValueType Stride[ImageDimension];
  SizeValueType Center[ImageDimension];

  // Set up the derivative operators, one for each dimension
  for ( i = 0; i < ImageDimension; ++i )
    {
    operator_list[i].SetOrder(1);
    operator_list[i].SetDirection(i);
    operator_list[i].CreateDirectional();
    radius[i] = operator_list[i].GetRadius()[i];
    }

  // Get the various region "faces" that are on the data set boundary.
  faceList = bfc(ip, ip->GetRequestedRegion(), radius);
  fit      = faceList.begin();

  // Now do the actual processing
  accumulator = NumericTraits< AccumulateType >::ZeroValue();
  counter     = NumericTraits< SizeValueType >::ZeroValue();

  // First process the non-boundary region

  // Instead of maintaining a single N-d neighborhood of pointers,
  // we maintain a list of 1-d neighborhoods along each axial direction.
  // This is more efficient for higher dimensions.
  for ( i = 0; i < ImageDimension; ++i )
    {
    iterator_list[i] = RNI_type(operator_list[i].GetRadius(), ip, *fit);
    iterator_list[i].GoToBegin();
    Center[i] = iterator_list[i].Size() / 2;
    Stride[i] = iterator_list[i].GetStride(i);
    }
  while ( !iterator_list[0].IsAtEnd() )
    {
    counter++;
    for ( i = 0; i < ImageDimension; ++i )
      {
      val = iterator_list[i].GetPixel(Center[i] + Stride[i])
            - iterator_list[i].GetPixel(Center[i] - Stride[i]);
      PixelRealType tempval = val / -2.0f;
      val = tempval * this->m_ScaleCoefficients[i];
      accumulator += val * val;
      ++iterator_list[i];
      }
    }

  // Go on to the next region(s).  These are on the boundary faces.
  ++fit;
  while ( fit != faceList.end() )
    {
    for ( i = 0; i < ImageDimension; ++i )
      {
      face_iterator_list[i] = SNI_type(operator_list[i].GetRadius(), ip,
                                       *fit);
      face_iterator_list[i].OverrideBoundaryCondition(&bc);
      face_iterator_list[i].GoToBegin();
      Center[i] = face_iterator_list[i].Size() / 2;
      Stride[i] = face_iterator_list[i].GetStride(i);
      }

    while ( !face_iterator_list[0].IsAtEnd() )
      {
      counter++;
      for ( i = 0; i < ImageDimension; ++i )
        {
        val = face_iterator_list[i].GetPixel(Center[i] + Stride[i])
              - face_iterator_list[i].GetPixel(Center[i] - Stride[i]);
        PixelRealType tempval = val / -2.0f;
        val = tempval * this->m_ScaleCoefficients[i];
        accumulator += val * val;
        ++face_iterator_list[i];
        }
      }
    ++fit;
    }

  this->SetAverageGradientMagnitudeSquared( (double)( accumulator / counter ) );
}
} // end namespace itk

#endif
