/*=========================================================================
 *
 *  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 itkKappaSigmaThresholdImageFilter_hxx
#define itkKappaSigmaThresholdImageFilter_hxx

#include "itkBinaryThresholdImageFilter.h"
#include "itkProgressAccumulator.h"

namespace itk
{
template <typename TInputImage, typename TMaskImage, typename TOutputImage>
KappaSigmaThresholdImageFilter<TInputImage, TMaskImage, TOutputImage>::KappaSigmaThresholdImageFilter()
  : m_MaskValue(NumericTraits<MaskPixelType>::max())
  , m_Threshold(InputPixelType{})
  , m_InsideValue(NumericTraits<OutputPixelType>::max())
  , m_OutsideValue(OutputPixelType{})
{}

template <typename TInputImage, typename TMaskImage, typename TOutputImage>
void
KappaSigmaThresholdImageFilter<TInputImage, TMaskImage, TOutputImage>::GenerateData()
{
  auto progress = ProgressAccumulator::New();
  progress->SetMiniPipelineFilter(this);

  // Compute the Threshold for the input image
  auto thresholdImageCalculator = CalculatorType::New();
  thresholdImageCalculator->SetImage(this->GetInput());
  thresholdImageCalculator->SetMask(this->GetMaskImage());
  thresholdImageCalculator->SetMaskValue(m_MaskValue);
  thresholdImageCalculator->SetSigmaFactor(m_SigmaFactor);
  thresholdImageCalculator->SetNumberOfIterations(m_NumberOfIterations);
  thresholdImageCalculator->Compute();

  m_Threshold = thresholdImageCalculator->GetOutput();

  typename BinaryThresholdImageFilter<TInputImage, TOutputImage>::Pointer threshold =
    BinaryThresholdImageFilter<TInputImage, TOutputImage>::New();

  progress->RegisterInternalFilter(threshold, .5f);
  threshold->GraftOutput(this->GetOutput());
  threshold->SetInput(this->GetInput());
  threshold->SetLowerThreshold(m_Threshold);
  threshold->SetInsideValue(m_InsideValue);
  threshold->SetOutsideValue(m_OutsideValue);
  threshold->Update();

  this->GraftOutput(threshold->GetOutput());
}

template <typename TInputImage, typename TMaskImage, typename TOutputImage>
void
KappaSigmaThresholdImageFilter<TInputImage, TMaskImage, TOutputImage>::GenerateInputRequestedRegion()
{
  const_cast<TInputImage *>(this->GetInput())->SetRequestedRegionToLargestPossibleRegion();
}

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

  os << indent << "Threshold: " << static_cast<typename NumericTraits<InputPixelType>::PrintType>(m_Threshold)
     << std::endl;
  os << indent << "MaskValue: " << static_cast<typename NumericTraits<MaskPixelType>::PrintType>(m_MaskValue)
     << std::endl;
  os << indent << "SigmaFactor: " << m_SigmaFactor << std::endl;
  os << indent << "NumberOfIterations: " << this->m_NumberOfIterations << std::endl;
  os << indent
     << "Inside value: " << static_cast<typename NumericTraits<OutputPixelType>::PrintType>(this->m_InsideValue)
     << std::endl;
  os << indent
     << "Outside value: " << static_cast<typename NumericTraits<OutputPixelType>::PrintType>(this->m_OutsideValue)
     << std::endl;
}
} // end namespace itk
#endif
