/*=========================================================================
 *
 *  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 itkMomentsThresholdCalculator_hxx
#define itkMomentsThresholdCalculator_hxx

#include "itkProgressReporter.h"
#include "itkMath.h"

namespace itk
{

template <typename THistogram, typename TOutput>
void
MomentsThresholdCalculator<THistogram, TOutput>::GenerateData()
{
  const HistogramType * histogram = this->GetInput();

  if (histogram->GetTotalFrequency() == 0)
  {
    itkExceptionMacro("Histogram is empty");
  }
  ProgressReporter progress(this, 0, histogram->GetSize(0));
  if (histogram->GetSize(0) == 1)
  {
    this->GetOutput()->Set(static_cast<OutputType>(histogram->GetMeasurement(0, 0)));
  }

  unsigned int size = histogram->GetSize(0);

  double                                     total = histogram->GetTotalFrequency();
  double                                     m0 = 1.0, m1 = 0.0, m2 = 0.0, m3 = 0.0, sum = 0.0, p0 = 0.0;
  double                                     cd, c0, c1, z0, z1; // auxiliary variables
  typename HistogramType::InstanceIdentifier threshold = 0;

  std::vector<double> histo(size);
  for (unsigned int i = 0; i < size; ++i)
  {
    histo[i] = static_cast<double>(histogram->GetFrequency(i, 0) / total); // normalised histogram
  }

  // Calculate the first, second, and third order moments
  for (unsigned int i = 0; i < size; ++i)
  {
    double m = histogram->GetMeasurement(i, 0);
    m1 += m * histo[i];
    m2 += m * m * histo[i];
    m3 += m * m * m * histo[i];
    progress.CompletedPixel();
  }
  //
  // First 4 moments of the gray-level image should match the first 4 moments
  // of the target binary image. This leads to 4 equalities whose solutions
  // are given in the Appendix of Ref. 1
  //
  cd = m0 * m2 - m1 * m1;
  c0 = (-m2 * m2 + m1 * m3) / cd;
  c1 = (m0 * -m3 + m2 * m1) / cd;
  z0 = 0.5 * (-c1 - std::sqrt(c1 * c1 - 4.0 * c0));
  z1 = 0.5 * (-c1 + std::sqrt(c1 * c1 - 4.0 * c0));
  p0 = (z1 - m1) / (z1 - z0); // Fraction of the object pixels in the target binary image

  // The threshold is the gray-level closest to the p0-tile of the normalized
  // histogram
  sum = 0;
  for (unsigned int i = 0; i < size; ++i)
  {
    sum += histo[i];
    if (sum > p0)
    {
      threshold = i;
      break;
    }
  }

  this->GetOutput()->Set(static_cast<OutputType>(histogram->GetMeasurement(threshold, 0)));
}

} // end namespace itk

#endif