/*=========================================================================
 *
 *  Copyright Insight Software Consortium
 *
 *  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
 *
 *         http://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 "itkGaussianImageSource.h"
#include "itkLinearInterpolateImageFunction.h"
#include "itkMeanSquaresHistogramImageToImageMetric.h"
#include "itkTranslationTransform.h"

/** This test uses two 2D-Gaussians (standard deviation RegionSize/2).
    This test computes the mean squared differences between the pixels in the
    two images.
*/
int itkMeanSquaresHistogramImageToImageMetricTest(int , char* [])
{
  try {
    // Create two simple images.
    const unsigned int ImageDimension = 2;
    typedef double PixelType;
    typedef double CoordinateRepresentationType;

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

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

    // 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};

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

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

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

    // Set up the metric.
    typedef itk::MeanSquaresHistogramImageToImageMetric<FixedImageType,
      MovingImageType>                        MetricType;
    typedef MetricType::TransformType         TransformBaseType;
    typedef MetricType::ScalesType            ScalesType;
    typedef TransformBaseType::ParametersType ParametersType;

    MetricType::Pointer metric = MetricType::New();

    unsigned int nBins = 256;
    MetricType::HistogramType::SizeType histSize;
    histSize.SetSize(2);
    histSize[0] = nBins;
    histSize[1] = nBins;
    metric->SetHistogramSize(histSize);

    // Plug the images into the metric.
    metric->SetFixedImage(fixedImage);
    metric->SetMovingImage(movingImage);

    // Set up a transform.
    typedef itk::TranslationTransform<CoordinateRepresentationType,
      ImageDimension> TransformType;

    TransformType::Pointer transform = TransformType::New();
    metric->SetTransform(transform.GetPointer());

    // Set up an interpolator.
    typedef itk::LinearInterpolateImageFunction<MovingImageType,
      CoordinateRepresentationType> InterpolatorType;

    InterpolatorType::Pointer interpolator = InterpolatorType::New();
    interpolator->SetInputImage(movingImage.GetPointer());
    metric->SetInterpolator(interpolator.GetPointer());

    // Define the region over which the metric will be computed.
    metric->SetFixedImageRegion(fixedImage->GetBufferedRegion());

    // Set up transform parameters.
    const unsigned int numberOfParameters = transform->GetNumberOfParameters();

    ParametersType parameters( numberOfParameters );

    for (unsigned int k = 0; k < numberOfParameters; k++)
      {
      parameters[k] = 0.0f;
      }

    // Set scales for derivative calculation.
    ScalesType scales( numberOfParameters );

    for (unsigned int k = 0; k < numberOfParameters; k++)
      {
      scales[k] = 1;
      }

    metric->SetDerivativeStepLengthScales(scales);

    // Initialize the metric.
    metric->Initialize();

    // Print out metric value and derivative.
    MetricType::MeasureType measure = metric->GetValue(parameters);
    MetricType::DerivativeType derivative;
    metric->GetDerivative(parameters, derivative);

    std::cout << "Metric value = " << measure << std::endl
              << "Derivative = " << derivative << std::endl;

    // Exercise Print() method.
    metric->Print(std::cout);

    std::cout << "Test passed." << std::endl;
  }
  catch (itk::ExceptionObject& ex)
  {
    std::cerr << "Exception caught!" << std::endl;
    std::cerr << ex << std::endl;
    return EXIT_FAILURE;
  }

  return EXIT_SUCCESS;
}
