/*=========================================================================
 *
 *  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 itkGradientNDAnisotropicDiffusionFunction_hxx
#define itkGradientNDAnisotropicDiffusionFunction_hxx

#include "itkNumericTraits.h"
#include "itkGradientNDAnisotropicDiffusionFunction.h"

namespace itk
{
template< typename TImage >
double GradientNDAnisotropicDiffusionFunction< TImage >
::m_MIN_NORM = 1.0e-10;

template< typename TImage >
GradientNDAnisotropicDiffusionFunction< TImage >
::GradientNDAnisotropicDiffusionFunction() :
  m_K(0.0)
{
  unsigned int i, j;
  RadiusType   r;

  for ( i = 0; i < ImageDimension; ++i )
    {
    r[i] = 1;
    }
  this->SetRadius(r);

  // Dummy neighborhood used to set up the slices.
  Neighborhood< PixelType, ImageDimension > it;
  it.SetRadius(r);

  // Slice the neighborhood
  m_Center =  it.Size() / 2;

  for ( i = 0; i < ImageDimension; ++i )
    {
    m_Stride[i] = it.GetStride(i);
    }

  for ( i = 0; i < ImageDimension; ++i )
    {
    x_slice[i]  = std::slice(m_Center - m_Stride[i], 3, m_Stride[i]);
    }

  for ( i = 0; i < ImageDimension; ++i )
    {
    for ( j = 0; j < ImageDimension; ++j )
      {
      // For taking derivatives in the i direction that are offset one
      // pixel in the j direction.
      xa_slice[i][j] =
        std::slice( ( m_Center + m_Stride[j] ) - m_Stride[i], 3, m_Stride[i] );
      xd_slice[i][j] =
        std::slice( ( m_Center - m_Stride[j] ) - m_Stride[i], 3, m_Stride[i] );
      }
    }

  // Allocate the derivative operator.
  dx_op.SetDirection(0);  // Not relevant, will be applied in a slice-based
                          // fashion.
  dx_op.SetOrder(1);
  dx_op.CreateDirectional();
}

template< typename TImage >
typename GradientNDAnisotropicDiffusionFunction< TImage >::PixelType
GradientNDAnisotropicDiffusionFunction< TImage >
::ComputeUpdate(const NeighborhoodType & it, void *,
                const FloatOffsetType &)
{
  unsigned int i, j;

  double accum;
  double accum_d;
  double Cx;
  double Cxd;

  // PixelType is scalar in this context
  PixelRealType delta;
  PixelRealType dx_forward;
  PixelRealType dx_backward;
  PixelRealType dx[ImageDimension];
  PixelRealType dx_aug;
  PixelRealType dx_dim;

  delta = NumericTraits< PixelRealType >::ZeroValue();

  // Calculate the centralized derivatives for each dimension.
  for ( i = 0; i < ImageDimension; i++ )
    {
    dx[i]  =  ( it.GetPixel(m_Center + m_Stride[i]) - it.GetPixel(m_Center - m_Stride[i]) ) / 2.0f;
    dx[i] *= this->m_ScaleCoefficients[i];
    }

  for ( i = 0; i < ImageDimension; i++ )
    {
    // "Half" directional derivatives
    dx_forward = it.GetPixel(m_Center + m_Stride[i])
                 - it.GetPixel(m_Center);
    dx_forward *= this->m_ScaleCoefficients[i];
    dx_backward =  it.GetPixel(m_Center)
                  - it.GetPixel(m_Center - m_Stride[i]);
    dx_backward *= this->m_ScaleCoefficients[i];

    // Calculate the conductance terms.  Conductance varies with each
    // dimension because the gradient magnitude approximation is different
    // along each  dimension.
    accum   = 0.0;
    accum_d = 0.0;
    for ( j = 0; j < ImageDimension; j++ )
      {
      if ( j != i )
        {
        dx_aug = ( it.GetPixel(m_Center + m_Stride[i] + m_Stride[j])
                   - it.GetPixel(m_Center + m_Stride[i] - m_Stride[j]) ) / 2.0f;
        dx_aug *= this->m_ScaleCoefficients[j];
        dx_dim = ( it.GetPixel(m_Center - m_Stride[i] + m_Stride[j])
                   - it.GetPixel(m_Center - m_Stride[i] - m_Stride[j]) ) / 2.0f;
        dx_dim *= this->m_ScaleCoefficients[j];
        accum += 0.25f * itk::Math::sqr(dx[j] + dx_aug);
        accum_d += 0.25f * itk::Math::sqr(dx[j] + dx_dim);
        }
      }

    if ( m_K == 0.0 )
      {
      Cx = 0.0;
      Cxd = 0.0;
      }
    else
      {
      Cx = std::exp( ( itk::Math::sqr(dx_forward) + accum )  / m_K );
      Cxd = std::exp( ( itk::Math::sqr(dx_backward) + accum_d ) / m_K );
      }

    // Conductance modified first order derivatives.
    dx_forward  = dx_forward * Cx;
    dx_backward = dx_backward * Cxd;

    // Conductance modified second order derivative.
    delta += dx_forward - dx_backward;
    }

  return static_cast< PixelType >( delta );
}
} // end namespace itk

#endif