/*=========================================================================
 *
 *  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 "itkSimpleFilterWatcher.h"
#include "itkImageFileWriter.h"
#include "itkGaussianImageSource.h"
#include "itkTestingMacros.h"
#include "itkMath.h"

int
itkGaussianImageSourceTest(int argc, char * argv[])
{
  if (argc < 3)
  {
    std::cout << "Usage: " << itkNameOfTestExecutableMacro(argv) << " outputImage normalized" << std::endl;
    return EXIT_FAILURE;
  }

  constexpr unsigned int Dimension = 3;
  using PixelType = unsigned char;

  using ImageType = itk::Image<PixelType, Dimension>;

  // Create a Gaussian image source
  using GaussianSourceType = itk::GaussianImageSource<ImageType>;
  auto gaussianImage = GaussianSourceType::New();

  ImageType::SpacingValueType spacing[] = { 1.2f, 1.3f, 1.4f };
  ImageType::PointValueType   origin[] = { 1.0f, 4.0f, 2.0f };
  ImageType::SizeValueType    size[] = { 130, 150, 120 };
  ImageType::DirectionType    direction;
  direction.SetIdentity();

  GaussianSourceType::ArrayType mean;
  mean[0] = size[0] / 2.0f + origin[0];
  mean[1] = size[1] / 2.0f + origin[1];
  mean[2] = size[2] / 2.0f + origin[2];

  GaussianSourceType::ArrayType sigma;
  sigma[0] = 25.0f;
  sigma[1] = 35.0f;
  sigma[2] = 55.0f;

  gaussianImage->SetSize(size);
  for (unsigned int i = 0; i < Dimension; ++i)
  {
    ITK_TEST_SET_GET_VALUE(size[i], gaussianImage->GetSize()[i]);
  }

  gaussianImage->SetOrigin(origin);
  for (unsigned int i = 0; i < Dimension; ++i)
  {
    ITK_TEST_SET_GET_VALUE(origin[i], gaussianImage->GetOrigin()[i]);
  }

  gaussianImage->SetSpacing(spacing);
  for (unsigned int i = 0; i < Dimension; ++i)
  {
    ITK_TEST_SET_GET_VALUE(spacing[i], gaussianImage->GetSpacing()[i]);
  }

  gaussianImage->SetDirection(direction);
  ITK_TEST_SET_GET_VALUE(direction, gaussianImage->GetDirection());

  // Test SetReferenceImage from GenerateImageSource base class.
  auto                 referenceImage = ImageType::New();
  ImageType::IndexType startIndex;
  startIndex.Fill(0);
  ImageType::SizeType referenceSize;
  referenceSize.SetSize(size);
  ImageType::RegionType region(startIndex, referenceSize);
  referenceImage->SetRegions(region);
  referenceImage->Allocate();
  referenceImage->FillBuffer(0);

  referenceImage->SetOrigin(origin);
  referenceImage->SetSpacing(spacing);
  referenceImage->SetDirection(direction);
  gaussianImage->SetReferenceImage(referenceImage);
  bool useReferenceImage = true;
  ITK_TEST_SET_GET_BOOLEAN(gaussianImage, UseReferenceImage, useReferenceImage);
  gaussianImage->SetReferenceImage(referenceImage);
  ITK_TEST_SET_GET_VALUE(referenceImage, gaussianImage->GetReferenceImage());

  gaussianImage->SetOutputParametersFromImage(referenceImage);

  bool normalized = std::stoi(argv[2]) != 0;
  ITK_TEST_SET_GET_BOOLEAN(gaussianImage, Normalized, normalized);

  gaussianImage->SetMean(mean);
  ITK_TEST_SET_GET_VALUE(mean, gaussianImage->GetMean());

  gaussianImage->SetSigma(sigma);
  ITK_TEST_SET_GET_VALUE(sigma, gaussianImage->GetSigma());


  // Check the parameters
  GaussianSourceType::ParametersType params = gaussianImage->GetParameters();
  if (params.GetSize() != 7)
  {
    std::cerr << "Incorrect number of parameters. Expected 7, got " << params.GetSize() << '.' << std::endl;
    return EXIT_FAILURE;
  }

  if (itk::Math::NotAlmostEquals(params[0], sigma[0]) || itk::Math::NotAlmostEquals(params[1], sigma[1]) ||
      itk::Math::NotAlmostEquals(params[2], sigma[2]))
  {
    std::cerr << "Parameters have incorrect sigma value." << std::endl;
    return EXIT_FAILURE;
  }

  if (itk::Math::NotAlmostEquals(params[3], mean[0]) || itk::Math::NotAlmostEquals(params[4], mean[1]) ||
      itk::Math::NotAlmostEquals(params[5], mean[2]))
  {
    std::cerr << "Parameters have incorrect mean value." << std::endl;
    return EXIT_FAILURE;
  }

  if (itk::Math::NotAlmostEquals(params[6], gaussianImage->GetScale()))
  {
    std::cerr << "Parameters have incorrect scale value." << std::endl;
    return EXIT_FAILURE;
  }

  params[0] = 12.0;
  params[1] = 13.0;
  params[2] = 14.0;
  params[3] = 22.0;
  params[4] = 32.0;
  params[5] = 42.0;
  params[6] = 55.5;
  gaussianImage->SetParameters(params);

  if (itk::Math::NotAlmostEquals(gaussianImage->GetSigma()[0], params[0]) ||
      itk::Math::NotAlmostEquals(gaussianImage->GetSigma()[1], params[1]) ||
      itk::Math::NotAlmostEquals(gaussianImage->GetSigma()[2], params[2]))
  {
    std::cerr << "Sigma disagrees with parameters array." << std::endl;
    std::cerr << "Sigma: " << gaussianImage->GetSigma() << ", parameters: [" << params[0] << ", " << params[1] << ", "
              << params[2] << ']' << std::endl;
    return EXIT_FAILURE;
  }

  if (itk::Math::NotAlmostEquals(gaussianImage->GetMean()[0], params[3]) ||
      itk::Math::NotAlmostEquals(gaussianImage->GetMean()[1], params[4]) ||
      itk::Math::NotAlmostEquals(gaussianImage->GetMean()[2], params[5]))
  {
    std::cerr << "Mean disagrees with parameters array." << std::endl;
    std::cerr << "Mean: " << gaussianImage->GetMean() << ", parameters: [" << params[3] << ", " << params[4] << ", "
              << params[5] << ']' << std::endl;
    return EXIT_FAILURE;
  }

  if (itk::Math::NotAlmostEquals(gaussianImage->GetScale(), params[6]))
  {
    std::cerr << "Scale disagrees with parameters array." << std::endl;
    std::cerr << "Scale: " << gaussianImage->GetScale() << ", parameters: " << params[6] << std::endl;
    return EXIT_FAILURE;
  }


  itk::SimpleFilterWatcher watcher(gaussianImage, "GaussianImageSource");

  // Run the pipeline
  ITK_TRY_EXPECT_NO_EXCEPTION(gaussianImage->Update());


  // Get the output of the image source
  ImageType::Pointer outputImage = gaussianImage->GetOutput();

  // Write the result image
  using WriterType = itk::ImageFileWriter<ImageType>;

  auto writer = WriterType::New();

  writer->SetFileName(argv[1]);

  writer->SetInput(outputImage);

  ITK_TRY_EXPECT_NO_EXCEPTION(writer->Update());

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