/*=========================================================================
 *
 *  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 "itkGradientRecursiveGaussianImageFilter.h"
#include "itkSimpleFilterWatcher.h"
#include "itkTestingMacros.h"

int
itkGradientRecursiveGaussianFilterTest(int argc, char * argv[])
{
  if (argc != 3)
  {
    std::cerr << "Missing parameters." << std::endl;
    std::cerr << "Usage: " << itkNameOfTestExecutableMacro(argv);
    std::cerr << " normalizeAcrossScale useImageDirection" << std::endl;
    return EXIT_FAILURE;
  }

  // Define the dimension of the images
  constexpr unsigned int myDimension = 3;

  // Declare the types of the images
  using myImageType = itk::Image<float, myDimension>;

  // Declare the type of the index to access images
  using myIndexType = itk::Index<myDimension>;

  // Declare the type of the size
  using mySizeType = itk::Size<myDimension>;

  // Declare the type of the Region
  using myRegionType = itk::ImageRegion<myDimension>;

  // Create the image
  auto inputImage = myImageType::New();


  // Define their size, and start index
  mySizeType size;
  size[0] = 8;
  size[1] = 8;
  size[2] = 8;

  myIndexType start;
  start.Fill(0);

  myRegionType region{ start, size };

  // Initialize Image A
  inputImage->SetRegions(region);
  inputImage->Allocate();

  // Declare Iterator type for the input image
  using myIteratorType = itk::ImageRegionIteratorWithIndex<myImageType>;

  // Create one iterator for the Input Image A (this is a light object)
  myIteratorType it(inputImage, inputImage->GetRequestedRegion());

  // Initialize the content of Image A
  while (!it.IsAtEnd())
  {
    it.Set(0.0);
    ++it;
  }

  size[0] = 4;
  size[1] = 4;
  size[2] = 4;

  start[0] = 2;
  start[1] = 2;
  start[2] = 2;

  // Create one iterator for an internal region
  myRegionType   innerRegion{ start, size };
  myIteratorType itb(inputImage, innerRegion);

  // Initialize the content the internal region
  while (!itb.IsAtEnd())
  {
    itb.Set(100.0);
    ++itb;
  }

  // Declare the type for the
  using myFilterType = itk::GradientRecursiveGaussianImageFilter<myImageType>;

  using myGradientImageType = myFilterType::OutputImageType;


  // Create a  Filter
  auto filter = myFilterType::New();

  ITK_EXERCISE_BASIC_OBJECT_METHODS(filter, GradientRecursiveGaussianImageFilter, ImageToImageFilter);


  itk::SimpleFilterWatcher watcher(filter);

  auto normalizeAcrossScale = static_cast<bool>(std::stoi(argv[1]));
  filter->SetNormalizeAcrossScale(normalizeAcrossScale);
  ITK_TEST_SET_GET_VALUE(normalizeAcrossScale, filter->GetNormalizeAcrossScale());

  auto useImageDirection = static_cast<bool>(std::stoi(argv[2]));
  ITK_TEST_SET_GET_BOOLEAN(filter, UseImageDirection, useImageDirection);

  // Select the value of Sigma
  typename myFilterType::ScalarRealType sigma = 2.5;
  filter->SetSigma(sigma);
  ITK_TEST_SET_GET_VALUE(sigma, filter->GetSigma());

  // Connect the input images
  filter->SetInput(inputImage);

  // Execute the filter
  filter->Update();

  // Get the Smart Pointer to the Filter Output
  // It is important to do it AFTER the filter is Updated
  // Because the object connected to the output may be changed
  // by another during GenerateData() call
  myGradientImageType::Pointer outputImage = filter->GetOutput();

  // Declare Iterator type for the output image
  using myOutputIteratorType = itk::ImageRegionIteratorWithIndex<myGradientImageType>;

  // Create an iterator for going through the output image
  myOutputIteratorType itg(outputImage, outputImage->GetRequestedRegion());

  // Print the content of the result image
  std::cout << " Result " << std::endl;
  itg.GoToBegin();
  while (!itg.IsAtEnd())
  {
    std::cout << itg.Get();
    ++itg;
  }
  std::cout << std::endl;

  //
  // Test with a change in image direction
  //
  myImageType::DirectionType direction;
  direction.Fill(0.0);
  direction[0][0] = -1.0;
  direction[1][1] = -1.0;
  direction[2][2] = -1.0;
  inputImage->SetDirection(direction);

  // Create a  Filter
  auto filter2 = myFilterType::New();
  filter2->SetInput(inputImage);
  filter2->SetSigma(2.5);
  filter2->Update();
  myGradientImageType::Pointer outputFlippedImage = filter2->GetOutput();

  // compare the output between identity direction and flipped direction
  std::cout << " Result of flipped image " << std::endl;
  myOutputIteratorType itf(outputFlippedImage, outputFlippedImage->GetRequestedRegion());
  itf.GoToBegin();
  bool passed = true;
  while (!itf.IsAtEnd())
  {
    std::cout << itf.Get();
    myImageType::IndexType index;
    for (unsigned int d = 0; d < myDimension; ++d)
    {
      index[d] = region.GetSize()[d] - 1 - itf.GetIndex()[d];
    }
    if (itf.Value() != outputImage->GetPixel(index))
    {
      passed = false;
    }
    ++itf;
  }
  std::cout << std::endl;
  if (!passed)
  {
    std::cerr << "Flipped image gradient does not match regular image as expected." << std::endl;
    return EXIT_FAILURE;
  }

  // All objects should be automatically destroyed at this point
  return EXIT_SUCCESS;
}