/*=========================================================================
 *
 *  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.
 *
 *=========================================================================*/

#include "itkTranslationTransform.h"
#include "itkLinearInterpolateImageFunction.h"
#include "itkMeanReciprocalSquareDifferencePointSetToImageMetric.h"
#include "itkGaussianImageSource.h"
#include "itkPointSet.h"

#include <iostream>
#include "itkStdStreamStateSave.h"
#include "itkTestingMacros.h"

/**
 *  This test uses two 2D-Gaussians (standard deviation RegionSize/2)
 *  One is shifted by 5 pixels from the other.
 *
 *  This test computes the MeanReciprocalSquares value and derivatives
 *  for various shift values in (-10,10).
 *
 */

int
itkMeanReciprocalSquareDifferencePointSetToImageMetricTest(int, char *[])
{

  // Save the format stream variables for std::cout
  // They will be restored when coutState goes out of scope
  itk::StdStreamStateSave coutState(std::cout);

  //------------------------------------------------------------
  // Create two simple images
  //------------------------------------------------------------

  constexpr unsigned int ImageDimension = 2;

  using PixelType = double;

  using CoordinateRepresentationType = double;

  // Allocate Images
  using MovingImageType = itk::Image<PixelType, ImageDimension>;
  using FixedImageType = itk::Image<PixelType, ImageDimension>;

  // Declare Gaussian Sources
  using MovingImageSourceType = itk::GaussianImageSource<MovingImageType>;
  using FixedImageSourceType = itk::GaussianImageSource<FixedImageType>;

  // Note: the following declarations are classical arrays
  FixedImageType::SizeValueType  fixedImageSize[] = { 100, 100 };
  MovingImageType::SizeValueType movingImageSize[] = { 100, 100 };

  FixedImageType::SpacingValueType  fixedImageSpacing[] = { 1.0f, 1.0f };
  MovingImageType::SpacingValueType movingImageSpacing[] = { 1.0f, 1.0f };

  FixedImageType::PointValueType  fixedImageOrigin[] = { 0.0f, 0.0f };
  MovingImageType::PointValueType movingImageOrigin[] = { 0.0f, 0.0f };

  auto movingImageSource = MovingImageSourceType::New();
  auto fixedImageSource = FixedImageSourceType::New();

  fixedImageSource->SetSize(fixedImageSize);
  fixedImageSource->SetOrigin(fixedImageOrigin);
  fixedImageSource->SetSpacing(fixedImageSpacing);
  fixedImageSource->SetNormalized(false);
  fixedImageSource->SetScale(250.0f);

  movingImageSource->SetSize(movingImageSize);
  movingImageSource->SetOrigin(movingImageOrigin);
  movingImageSource->SetSpacing(movingImageSpacing);
  movingImageSource->SetNormalized(false);
  movingImageSource->SetScale(250.0f);

  movingImageSource->Update(); // Force the filter to run
  fixedImageSource->Update();  // Force the filter to run

  MovingImageType::Pointer movingImage = movingImageSource->GetOutput();
  FixedImageType::Pointer  fixedImage = fixedImageSource->GetOutput();

  //-----------------------------------------------------------
  // Create the point set and load it with data by sampling
  // the fixed image
  //-----------------------------------------------------------
  using FixedPointSetType = itk::PointSet<float, 2>;
  auto fixedPointSet = FixedPointSetType::New();

  constexpr unsigned int numberOfPoints = 100;

  fixedPointSet->SetPointData(FixedPointSetType::PointDataContainer::New());

  fixedPointSet->GetPoints()->Reserve(numberOfPoints);
  fixedPointSet->GetPointData()->Reserve(numberOfPoints);

  itk::ImageRegionIterator<FixedImageType> it(fixedImage, fixedImage->GetBufferedRegion());

  const unsigned int skip = fixedImage->GetBufferedRegion().GetNumberOfPixels() / numberOfPoints;

  unsigned int counter = 0;

  FixedPointSetType::PointIdentifier pointId = 0;
  FixedPointSetType::PointType       point;

  it.GoToBegin();
  while (!it.IsAtEnd())
  {
    if (counter == 0)
    {
      fixedImage->TransformIndexToPhysicalPoint(it.GetIndex(), point);
      std::cout << "******************* " << pointId << ':' << point << std::endl;
      fixedPointSet->SetPoint(pointId, point);
      fixedPointSet->SetPointData(pointId, it.Get());
      ++pointId;
      if (pointId == numberOfPoints)
      {
        break;
      }
      counter = skip;
    }
    --counter;
    ++it;
  }

  // print the points accessed via iterator
  FixedPointSetType::PointsContainer::ConstIterator pointItr = fixedPointSet->GetPoints()->Begin();
  FixedPointSetType::PointsContainer::ConstIterator pointEnd = fixedPointSet->GetPoints()->End();
  while (pointItr != pointEnd)
  {
    std::cout << pointItr.Value() << std::endl;
    ++pointItr;
  }

  //-----------------------------------------------------------
  // Set up  the Metric
  //-----------------------------------------------------------
  using MetricType = itk::MeanReciprocalSquareDifferencePointSetToImageMetric<FixedPointSetType, MovingImageType>;

  using TransformBaseType = MetricType::TransformType;
  using ParametersType = TransformBaseType::ParametersType;

  auto metric = MetricType::New();

  ITK_EXERCISE_BASIC_OBJECT_METHODS(metric, MeanReciprocalSquareDifferencePointSetToImageMetric, PointSetToImageMetric);


  double lambda = 1.0;
  metric->SetLambda(lambda);
  ITK_TEST_SET_GET_VALUE(lambda, metric->GetLambda());

  //-----------------------------------------------------------
  // Plug the Images into the metric
  //-----------------------------------------------------------
  metric->SetFixedPointSet(fixedPointSet);
  metric->SetMovingImage(movingImage);

  //-----------------------------------------------------------
  // Set up a Transform
  //-----------------------------------------------------------

  using TransformType = itk::TranslationTransform<CoordinateRepresentationType, ImageDimension>;

  auto transform = TransformType::New();

  metric->SetTransform(transform);


  //------------------------------------------------------------
  // Set up an Interpolator
  //------------------------------------------------------------
  using InterpolatorType = itk::LinearInterpolateImageFunction<MovingImageType, double>;

  auto interpolator = InterpolatorType::New();

  interpolator->SetInputImage(movingImage);

  metric->SetInterpolator(interpolator);


  std::cout << metric << std::endl;


  //------------------------------------------------------------
  // This call is mandatory before start querying the Metric
  // This method do all the necessary connections between the
  // internal components: Interpolator, Transform and Images
  //------------------------------------------------------------
  try
  {
    metric->Initialize();
  }
  catch (const itk::ExceptionObject & e)
  {
    std::cout << "Metric initialization failed" << std::endl;
    std::cout << "Reason " << e.GetDescription() << std::endl;
    return EXIT_FAILURE;
  }


  //------------------------------------------------------------
  // Set up transform parameters
  //------------------------------------------------------------
  ParametersType parameters(transform->GetNumberOfParameters());

  // initialize the offset/vector part
  for (unsigned int k = 0; k < ImageDimension; ++k)
  {
    parameters[k] = 0.0f;
  }


  //---------------------------------------------------------
  // Print out metric values
  // for parameters[1] = {-10,10}  (arbitrary choice...)
  //---------------------------------------------------------

  MetricType::MeasureType    measure;
  MetricType::DerivativeType derivative;

  std::cout << "param[1]   Metric    d(Metric)/d(param[1] " << std::endl;

  for (double trans = -10; trans <= 5; trans += 0.2)
  {
    parameters[1] = trans;
    metric->GetValueAndDerivative(parameters, measure, derivative);

    std::cout.width(5);
    std::cout.precision(5);
    std::cout << trans;
    std::cout.width(15);
    std::cout.precision(5);
    std::cout << measure;
    std::cout.width(15);
    std::cout.precision(5);
    std::cout << derivative[1];
    std::cout << std::endl;

    // exercise the other functions
    metric->GetValue(parameters);
    metric->GetDerivative(parameters, derivative);
  }

  //-------------------------------------------------------
  // exercise misc member functions
  //-------------------------------------------------------
  std::cout << "Check case when Target is nullptr" << std::endl;
  metric->SetFixedPointSet(nullptr);
  try
  {
    std::cout << "Value = " << metric->GetValue(parameters);
    std::cout << "If you are reading this message the Metric " << std::endl;
    std::cout << "is NOT managing exceptions correctly    " << std::endl;
    return EXIT_FAILURE;
  }
  catch (const itk::ExceptionObject & e)
  {
    std::cout << "Exception received (as expected) " << std::endl;
    std::cout << "Description : " << e.GetDescription() << std::endl;
    std::cout << "Location    : " << e.GetLocation() << std::endl;
    std::cout << "Test for exception throwing... PASSED ! " << std::endl;
  }

  try
  {
    metric->GetValueAndDerivative(parameters, measure, derivative);
    std::cout << "Value = " << measure << std::endl;
    std::cout << "If you are reading this message the Metric " << std::endl;
    std::cout << "is NOT managing exceptions correctly    " << std::endl;
    return EXIT_FAILURE;
  }
  catch (const itk::ExceptionObject & e)
  {
    std::cout << "Exception received (as expected) " << std::endl;
    std::cout << "Description : " << e.GetDescription() << std::endl;
    std::cout << "Location    : " << e.GetLocation() << std::endl;
    std::cout << "Test for exception throwing... PASSED ! " << std::endl;
  }


  return EXIT_SUCCESS;
}