/*=========================================================================
 *
 *  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 "itkMath.h"
#include "itkJointHistogramMutualInformationImageToImageMetricv4.h"
#include "itkTranslationTransform.h"
#include "itkTestingMacros.h"

/* Simple test to verify that class builds and runs.
 * Results are not verified. See ImageToImageMetricv4Test
 * for verification of basic metric functionality.
 *
 * TODO Numerical verification.
 */

int
itkJointHistogramMutualInformationImageToImageMetricv4Test(int, char *[])
{

  constexpr unsigned int imageSize = 10;
  constexpr unsigned int imageDimensionality = 3;
  using ImageType = itk::Image<double, imageDimensionality>;

  ImageType::SizeType size;
  size.Fill(imageSize);
  ImageType::IndexType index;
  index.Fill(0);
  ImageType::RegionType region;
  region.SetSize(size);
  region.SetIndex(index);
  ImageType::SpacingType spacing;
  spacing.Fill(1.0);
  ImageType::PointType origin;
  origin.Fill(0);
  ImageType::DirectionType direction;
  direction.SetIdentity();

  /* Create simple test images. */
  auto fixedImage = ImageType::New();
  fixedImage->SetRegions(region);
  fixedImage->SetSpacing(spacing);
  fixedImage->SetOrigin(origin);
  fixedImage->SetDirection(direction);
  fixedImage->Allocate();

  auto movingImage = ImageType::New();
  movingImage->SetRegions(region);
  movingImage->SetSpacing(spacing);
  movingImage->SetOrigin(origin);
  movingImage->SetDirection(direction);
  movingImage->Allocate();

  /* Fill images */
  itk::ImageRegionIterator<ImageType> itFixed(fixedImage, region);
  itFixed.GoToBegin();
  unsigned int count = 1;
  while (!itFixed.IsAtEnd())
  {
    itFixed.Set(count * count);
    count++;
    ++itFixed;
  }
  itk::ImageRegionIteratorWithIndex<ImageType> itMoving(movingImage, region);
  itMoving.GoToBegin();
  count = 1;
  while (!itMoving.IsAtEnd())
  {
    itMoving.Set((count));
    count++;
    ++itMoving;
  }

  /* Transforms */
  using FixedTransformType = itk::TranslationTransform<double, imageDimensionality>;
  using MovingTransformType = itk::TranslationTransform<double, imageDimensionality>;
  auto fixedTransform = FixedTransformType::New();
  auto movingTransform = MovingTransformType::New();
  fixedTransform->SetIdentity();
  movingTransform->SetIdentity();

  /* The metric */
  using MetricType = itk::JointHistogramMutualInformationImageToImageMetricv4<ImageType, ImageType, ImageType>;
  auto metric = MetricType::New();

  ITK_EXERCISE_BASIC_OBJECT_METHODS(metric, JointHistogramMutualInformationImageToImageMetricv4, ImageToImageMetricv4);


  itk::SizeValueType numberOfHistogramBins = 6;
  metric->SetNumberOfHistogramBins(numberOfHistogramBins);
  ITK_TEST_SET_GET_VALUE(numberOfHistogramBins, metric->GetNumberOfHistogramBins());

  double varianceForJointPDFSmoothing = 1.5;
  metric->SetVarianceForJointPDFSmoothing(varianceForJointPDFSmoothing);
  ITK_TEST_SET_GET_VALUE(varianceForJointPDFSmoothing, metric->GetVarianceForJointPDFSmoothing());

  /* Assign images and transforms.
   * By not setting a virtual domain image or virtual domain settings,
   * the metric will use the fixed image for the virtual domain. */
  metric->SetFixedImage(fixedImage);
  metric->SetMovingImage(movingImage);
  metric->SetFixedTransform(fixedTransform);
  metric->SetMovingTransform(movingTransform);

  ITK_TRY_EXPECT_NO_EXCEPTION(metric->Initialize());


  // Evaluate
  MetricType::MeasureType    valueReturn1, valueReturn2;
  MetricType::DerivativeType derivativeReturn;

  ITK_TRY_EXPECT_NO_EXCEPTION(valueReturn1 = metric->GetValue());

  ITK_TRY_EXPECT_NO_EXCEPTION(metric->GetValueAndDerivative(valueReturn2, derivativeReturn));

  if (itk::Math::NotExactlyEquals(valueReturn1, valueReturn2))
  {
    std::cerr << "Value return results are not identical: " << valueReturn1 << ", " << valueReturn2 << std::endl;
  }

  std::cout << "JointPDF: " << metric->GetJointPDF() << std::endl;

  // Test that non-overlapping images will generate a warning
  // and return max value for metric value.
  MovingTransformType::ParametersType parameters(movingTransform->GetNumberOfParameters());
  parameters.Fill(static_cast<MovingTransformType::ParametersValueType>(1000));
  movingTransform->SetParameters(parameters);
  MetricType::MeasureType expectedMetricMax;
  expectedMetricMax = itk::NumericTraits<MetricType::MeasureType>::max();
  std::cout << "Testing non-overlapping images. Expect a warning:" << std::endl;
  metric->GetValueAndDerivative(valueReturn2, derivativeReturn);
  if (metric->GetNumberOfValidPoints() != 0 || itk::Math::NotAlmostEquals(valueReturn2, expectedMetricMax))
  {
    std::cerr << "Failed testing for non-overlapping images. " << std::endl
              << "  Number of valid points: " << metric->GetNumberOfValidPoints() << std::endl
              << "  Metric value: " << valueReturn2 << std::endl
              << "  Expected metric max value: " << expectedMetricMax << std::endl;
  }
  movingTransform->SetIdentity();


  std::cout << "Test finished." << std::endl;
  return EXIT_SUCCESS;
}