/*=========================================================================
 *
 *  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 itkImplicitManifoldNormalVectorFilter_hxx
#define itkImplicitManifoldNormalVectorFilter_hxx

#include "itkImplicitManifoldNormalVectorFilter.h"
#include "itkNumericTraits.h"

namespace itk
{
template< typename TInputImage, typename TSparseOutputImage >
ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >
::ImplicitManifoldNormalVectorFilter()
{
  this->SetPrecomputeFlag(true);
  m_NormalFunction = nullptr;

  // set defaults for parameters
  m_IsoLevelLow  = NumericTraits< NodeValueType >::ZeroValue();
  m_IsoLevelHigh = NumericTraits< NodeValueType >::ZeroValue();
  m_MaxIteration = 25;
  m_MinVectorNorm = static_cast< NodeValueType >( 1.0e-6 );
  m_UnsharpMaskingFlag = false;
  m_UnsharpMaskingWeight = NumericTraits< NodeValueType >::ZeroValue();

  // compute constants used in computations
  unsigned int j;
  for ( j = 0; j < ImageDimension; j++ )
    {
    m_Indicator[j] = 1 << j;
    m_ManifoldRadius[j] = 1;
    }
  m_NumVertex = 1 << ImageDimension;
  m_DimConst  = static_cast< NodeValueType >( 1.0 / m_NumVertex );
  m_DimConst2 = static_cast< NodeValueType >( 4.0 * m_DimConst );
}

template< typename TInputImage, typename TSparseOutputImage >
void
ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >
::PrintSelf(std::ostream & os, Indent indent) const
{
  Superclass::PrintSelf(os, indent);
  os << indent << "IsoLevelLow: " << m_IsoLevelLow << std::endl;
  os << indent << "IsoLevelHigh: " << m_IsoLevelHigh << std::endl;
  os << indent << "MaxIteration: " << m_MaxIteration << std::endl;
  os << indent << "MinVectorNorm: " << m_MinVectorNorm << std::endl;
  os << indent << "UnsharpMaskingFlag: " << m_UnsharpMaskingFlag << std::endl;
  os << indent << "UnsharpMaskingWeight: " << m_UnsharpMaskingWeight << std::endl;
  os << indent << "DimConst: " << m_DimConst << std::endl;
  os << indent << "DimConst2: " << m_DimConst2 << std::endl;
  os << indent << "NumVertex: " << m_NumVertex << std::endl;
}

template< typename TInputImage, typename TSparseOutputImage >
void
ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >
::SetNormalFunction(NormalFunctionType *nf)
{
  m_NormalFunction = nf;
  Superclass::SetSparseFunction (nf);
}

template< typename TInputImage, typename TSparseOutputImage >
void
ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >
::Initialize()
{
  SetNormalBand();

  // call FDSparseImageFilter's Initialize to
  // prepare lists for multithreading
  Superclass::Initialize();
}

template< typename TInputImage, typename TSparseOutputImage >
void
ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >
::SetNormalBand()
{
  typename InputImageType::ConstPointer ManifoldImage = this->GetInput();
  typename SparseOutputImageType::Pointer output = this->GetOutput();

  InputImageIteratorType it( m_ManifoldRadius, ManifoldImage,
                             ManifoldImage->GetRequestedRegion() );

  IndexType     index;
  NodeValueType value;

  it.GoToBegin();
  while ( !it.IsAtEnd() )
    {
    value = it.GetCenterPixel();
    index = it.GetIndex();
    if ( ( value >= m_IsoLevelLow ) && ( value <= m_IsoLevelHigh ) )
      {
      this->InitializeNormalBandNode(output->AddNode(index), it);
      }
    else
      {
      output->SetPixel(index, nullptr);
      }
    ++it;
    }
}

template< typename TInputImage, typename TSparseOutputImage >
void
ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >
::InitializeNormalBandNode(NormalBandNodeType *node,
                           const InputImageIteratorType & it)
{
  unsigned int     i, j, k;
  unsigned int     counter;
  unsigned long    position, center;
  unsigned long    stride[ImageDimension];
  NormalVectorType normalvector;
  NodeValueType    derivative;

  for ( i = 0; i < ImageDimension; i++ )
    {
    stride[i] = it.GetStride(i);
    }
  center =  it.Size() / 2;

  // Normal vector computation -- use positive quadrant of neighborhood
  for ( j = 0; j < ImageDimension; j++ ) // derivative axis
    {
    normalvector[j] = NumericTraits< NodeValueType >::ZeroValue();
    for ( counter = 0; counter < m_NumVertex; counter++ )
      {
      position = center;
      for ( k = 0; k < ImageDimension; k++ )
        {
        if ( counter & m_Indicator[k] )
          {
          position += stride[k];
          }
        }
      if ( counter & m_Indicator[j] )
        {
        normalvector[j] += it.GetPixel (position);
        }
      else
        {
        normalvector[j] -= it.GetPixel (position);
        }
      }
    } // end derivative axis
  node->m_Data = normalvector / ( m_MinVectorNorm + normalvector.GetNorm() );
  node->m_InputData = node->m_Data;

  // Manifold normal vector computation
  for ( i = 0; i < ImageDimension; i++ ) // offset axis (flux position)
    {
    for ( j = 0; j < ImageDimension; j++ ) // derivative axis
      {
      derivative = NumericTraits< NodeValueType >::ZeroValue();
      if ( i != j )
        {
        for ( counter = 0; counter < m_NumVertex; counter++ )
          {
          if ( !( counter & m_Indicator[i] ) ) // is the offset axis bit off?
            {
            position = center;
            for ( k = 0; k < ImageDimension; k++ )
              {
              if ( counter & m_Indicator[k] )
                {
                position += stride[k];
                }
              }
            if ( counter & m_Indicator[j] )  // is the derivative axis bit on?
              {
              derivative += it.GetPixel (position);
              }
            else
              {
              derivative -= it.GetPixel (position);
              }
            } // if
          }   // counter loop
        derivative *= m_DimConst2;
        } // if i!=j
      else
        {
        for ( counter = 0; counter < m_NumVertex; counter++ )
          {
          position = center;
          for ( k = 0; k < ImageDimension; k++ )
            {
            if ( ( k != i ) && ( counter & m_Indicator[k] ) )
              {
              position += stride[k];
              }
            }
          if ( counter & m_Indicator[i] )
            {
            derivative += it.GetPixel (position + stride[i]);
            }
          else
            {
            derivative -= it.GetPixel (position - stride[i]);
            }
          }
        derivative *= m_DimConst;
        }
      node->m_ManifoldNormal[i][j] = derivative;
      } // end derivative axis
    node->m_ManifoldNormal[i] /=
      ( m_MinVectorNorm + node->m_ManifoldNormal[i].GetNorm() );
    } // end offset axis (flux position)
}

template< typename TInputImage, typename TSparseOutputImage >
void
ImplicitManifoldNormalVectorFilter< TInputImage, TSparseOutputImage >
::PostProcessOutput()
{
  if ( m_UnsharpMaskingFlag == true )
    {
    typename NodeListType::Pointer nodelist = this->GetOutput()->GetNodeList();
    typename NodeListType::Iterator it = nodelist->Begin();
    typename NodeListType::ConstIterator last = nodelist->End();
    NormalVectorType nv;

    while ( it != last )
      {
      nv = it->m_InputData * ( 1.0 + m_UnsharpMaskingWeight )
           - it->m_Data * m_UnsharpMaskingWeight;
      it->m_Data = nv / ( m_MinVectorNorm + nv.GetNorm() );
      ++it;
      }
    }
}
} // end namespace itk

#endif
