/*=========================================================================
 *
 *  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 __itkGPUAnisotropicDiffusionImageFilter_hxx
#define __itkGPUAnisotropicDiffusionImageFilter_hxx

#include "itkGPUAnisotropicDiffusionFunction.h"
#include "itkGPUAnisotropicDiffusionImageFilter.h"

namespace itk
{

/** Prepare for the iteration process. */
template< typename TInputImage, typename TOutputImage, typename TParentImageFilter >
void
GPUAnisotropicDiffusionImageFilter< TInputImage, TOutputImage, TParentImageFilter >
::InitializeIteration()
{
  GPUAnisotropicDiffusionFunction< UpdateBufferType > *f =
    dynamic_cast< GPUAnisotropicDiffusionFunction< UpdateBufferType > * >
      ( this->GetDifferenceFunction().GetPointer() );
  if ( !f )
    {
    throw ExceptionObject(__FILE__, __LINE__, "GPU anisotropic diffusion function is not set.", ITK_LOCATION);

    }

  f->SetConductanceParameter( this->GetConductanceParameter() );
  f->SetTimeStep( this->GetTimeStep() );

  // Check the timestep for stability
  double minSpacing;
  if ( this->GetUseImageSpacing() )
    {
    minSpacing = this->GetInput()->GetSpacing()[0];
    for ( unsigned int i = 1; i < ImageDimension; i++ )
      {
      if ( this->GetInput()->GetSpacing()[i] < minSpacing )
        {
        minSpacing = this->GetInput()->GetSpacing()[i];
        }
      }
    }
  else
    {
    minSpacing = 1.0;
    }
  if ( this->GetTimeStep() >  ( minSpacing / std::pow(2.0, static_cast< double >( ImageDimension ) + 1) ) )
    {
    //    f->SetTimeStep(1.0 / std::pow(2.0,
    // static_cast<double>(ImageDimension)));
    itkWarningMacro( << "Anisotropic diffusion unstable time step: "
                     << this->GetTimeStep() << std::endl
                     << "Stable time step for this image must be smaller than "
                     << minSpacing / std::pow( 2.0, static_cast< double >( ImageDimension + 1 ) ) );
    }

  if ( this->m_GradientMagnitudeIsFixed == false )
    {
    if ( ( this->GetElapsedIterations() % this->GetConductanceScalingUpdateInterval() ) == 0 )
      {
      /** GPU version of average squared gradient magniture calculation */
      f->GPUCalculateAverageGradientMagnitudeSquared( this->GetOutput() );
      }
    }
  else
    {
    f->SetAverageGradientMagnitudeSquared( this->GetFixedAverageGradientMagnitude()
                                           *
                                           this->GetFixedAverageGradientMagnitude() );
    }
  f->InitializeIteration();

  if ( this->GetNumberOfIterations() != 0 )
    {
    this->UpdateProgress( ( (float)( this->GetElapsedIterations() ) )
                          / ( (float)( this->GetNumberOfIterations() ) ) );
    }
  else
    {
    this->UpdateProgress(0);
    }
}

template< typename TInputImage, typename TOutputImage, typename TParentImageFilter >
void
GPUAnisotropicDiffusionImageFilter< TInputImage, TOutputImage, TParentImageFilter >
::PrintSelf(std::ostream & os, Indent indent) const
{
  GPUSuperclass::PrintSelf( os, indent.GetNextIndent() );
}

} // end namespace itk

#endif
