/*=========================================================================
 *
 *  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 itkNormalizeToConstantImageFilter_hxx
#define itkNormalizeToConstantImageFilter_hxx


#include "itkDivideImageFilter.h"
#include "itkNumericTraits.h"
#include "itkProgressAccumulator.h"
#include "itkStatisticsImageFilter.h"

namespace itk
{

template <typename TInputImage, typename TOutputImage>
NormalizeToConstantImageFilter<TInputImage, TOutputImage>::NormalizeToConstantImageFilter()
  : m_Constant(NumericTraits<RealType>::OneValue())
{}

template <typename TInputImage, typename TOutputImage>
void
NormalizeToConstantImageFilter<TInputImage, TOutputImage>::GenerateInputRequestedRegion()
{
  // Call the superclass' implementation of this method.
  Superclass::GenerateInputRequestedRegion();

  auto * input0 = const_cast<InputImageType *>(this->GetInput(0));
  if (!input0)
  {
    return;
  }

  input0->SetRequestedRegion(input0->GetLargestPossibleRegion());
}


template <typename TInputImage, typename TOutputImage>
void
NormalizeToConstantImageFilter<TInputImage, TOutputImage>::GenerateData()
{
  this->AllocateOutputs();
  const InputImageType * input0 = this->GetInput(0);
  OutputImageType *      output0 = this->GetOutput(0);

  // Create a process accumulator for tracking the progress of this minipipeline
  auto progress = ProgressAccumulator::New();
  progress->SetMiniPipelineFilter(this);

  using StatType = typename itk::StatisticsImageFilter<InputImageType>;
  auto stat = StatType::New();
  stat->SetInput(input0);
  progress->RegisterInternalFilter(stat, 0.5f);
  stat->SetNumberOfWorkUnits(this->GetNumberOfWorkUnits());
  stat->Update();

  using DivType = typename itk::DivideImageFilter<InputImageType, OutputImageType, OutputImageType>;
  auto div = DivType::New();
  div->SetInput(input0);
  div->SetConstant2(static_cast<RealType>(stat->GetSum()) / m_Constant);
  div->SetNumberOfWorkUnits(this->GetNumberOfWorkUnits());

  progress->RegisterInternalFilter(div, 0.5f);

  div->GraftOutput(output0);
  div->Update();
  this->GraftOutput(div->GetOutput());
}


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

  os << indent << "Constant: " << m_Constant << std::endl;
}

} // end namespace itk
#endif
