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

//  Software Guide : BeginLatex
//
//  This example illustrates how to compute second derivatives of
//  a 3D image using the \doxygen{RecursiveGaussianImageFilter}.
//
//  It's good to be able to compute the raw derivative without any smoothing,
//  but this can be problematic in a medical imaging scenario, when images
//  will often have a certain amount of noise. It's almost always more
//  desirable to include a smoothing step first, where an image is convolved
//  with a Gaussian kernel in whichever directions the user desires a
//  derivative. The nature of the Gaussian kernel makes it easy to combine
//  these two steps into one, using an infinite impulse response (IIR) filter.
//  In this example, all the second derivatives are computed independently in
//  the same way, as if they were intended to be used for building the Hessian
//  matrix of the image (a square matrix of second-order derivatives of an
//  image, which is useful in many image processing techniques).
//
//  Software Guide : EndLatex


//  Software Guide : BeginLatex
//
//  First, we will include the relevant header files: the
//  itkRecursiveGaussianImageFilter, the image reader, writer, and duplicator.
//
//  Software Guide : EndLatex

// Software Guide : BeginCodeSnippet
#include "itkRecursiveGaussianImageFilter.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkImageDuplicator.h"
#include <string>
//  Software Guide : EndCodeSnippet

int
main(int argc, char * argv[])
{

  if (argc < 3)
  {
    std::cerr << "Usage: " << std::endl;
    std::cerr << argv[0] << " inputImage outputPrefix  [sigma] " << std::endl;
    return EXIT_FAILURE;
  }

  //  Software Guide : BeginLatex
  //
  //  Next, we declare our pixel type and output pixel type to be floats, and
  //  our image dimension to be $3$.
  //
  // Software Guide : EndLatex

  // Software Guide : BeginCodeSnippet
  using PixelType = float;
  using OutputPixelType = float;

  constexpr unsigned int Dimension = 3;
  //  Software Guide : EndCodeSnippet

  //  Software Guide : BeginLatex
  //
  //  Using these definitions, define the image types, reader and writer
  //  types, and duplicator types, which are templated over the pixel types
  //  and dimension.  Then, instantiate the reader, writer, and duplicator
  //  with the \code{New()} method.
  //
  // Software Guide : EndLatex

  // Software Guide : BeginCodeSnippet
  using ImageType = itk::Image<PixelType, Dimension>;
  using OutputImageType = itk::Image<OutputPixelType, Dimension>;

  using ReaderType = itk::ImageFileReader<ImageType>;
  using WriterType = itk::ImageFileWriter<OutputImageType>;

  using DuplicatorType = itk::ImageDuplicator<OutputImageType>;

  using FilterType = itk::RecursiveGaussianImageFilter<ImageType, ImageType>;

  auto reader = ReaderType::New();
  auto writer = WriterType::New();

  auto duplicator = DuplicatorType::New();
  // Software Guide : EndCodeSnippet

  reader->SetFileName(argv[1]);

  std::string outputPrefix = argv[2];
  std::string outputFileName;

  try
  {
    reader->Update();
  }
  catch (const itk::ExceptionObject & excp)
  {
    std::cerr << "Problem reading the input file" << std::endl;
    std::cerr << excp << std::endl;
    return EXIT_FAILURE;
  }

  //  Software Guide : BeginLatex
  //
  //  Here we create three new filters. For each derivative we take, we will
  //  want to smooth in that direction first. So after the filters are
  //  created, each is given a dimension, and set to (in this example) the
  //  same sigma. Note that here, $\sigma$ represents the standard deviation,
  //  whereas the \doxygen{DiscreteGaussianImageFilter} exposes the
  //  \code{SetVariance} method.
  //
  //  Software Guide : EndLatex

  //  Software Guide : BeginCodeSnippet
  auto ga = FilterType::New();
  auto gb = FilterType::New();
  auto gc = FilterType::New();

  ga->SetDirection(0);
  gb->SetDirection(1);
  gc->SetDirection(2);

  if (argc > 3)
  {
    const float sigma = std::stod(argv[3]);
    ga->SetSigma(sigma);
    gb->SetSigma(sigma);
    gc->SetSigma(sigma);
  }
  //  Software Guide: EndCodeSnippet

  //  Software Guide : BeginLatex
  //
  //  First we will compute the second derivative of the $z$-direction.
  //  In order to do this, we smooth in the $x$- and $y$- directions, and
  //  finally smooth and compute the derivative in the $z$-direction. Taking
  //  the zero-order derivative is equivalent to simply smoothing in that
  //  direction. This result is commonly notated $I_{zz}$.
  //
  //  Software Guide : EndLatex

  //  Software Guide : BeginCodeSnippet
  ga->SetZeroOrder();
  gb->SetZeroOrder();
  gc->SetSecondOrder();

  ImageType::Pointer inputImage = reader->GetOutput();

  ga->SetInput(inputImage);
  gb->SetInput(ga->GetOutput());
  gc->SetInput(gb->GetOutput());

  duplicator->SetInputImage(gc->GetOutput());

  gc->Update();
  duplicator->Update();

  ImageType::Pointer Izz = duplicator->GetOutput();
  //  Software Guide: EndCodeSnippet

  writer->SetInput(Izz);
  outputFileName = outputPrefix + "-Izz.mhd";
  writer->SetFileName(outputFileName.c_str());
  writer->Update();

  //  Software Guide : BeginLatex
  //
  //  Recall that \code{gc} is the filter responsible for taking the second
  //  derivative. We can now take advantage of the pipeline architecture and,
  //  without much hassle, switch the direction of \code{gc} and \code{gb},
  //  so that \code{gc} now takes the derivatives in the $y$-direction. Now we
  //  only need to call \code{Update()} on \code{gc} to re-run the entire
  //  pipeline from \code{ga} to \code{gc}, obtaining the second-order
  //  derivative in the $y$-direction, which is commonly notated $I_{yy}$.
  //
  // Software Guide : EndLatex

  //  Software Guide : BeginCodeSnippet
  gc->SetDirection(1); // gc now works along Y
  gb->SetDirection(2); // gb now works along Z

  gc->Update();
  duplicator->Update();

  ImageType::Pointer Iyy = duplicator->GetOutput();
  //  Software Guide : EndCodeSnippet

  writer->SetInput(Iyy);
  outputFileName = outputPrefix + "-Iyy.mhd";
  writer->SetFileName(outputFileName.c_str());
  writer->Update();

  //  Software Guide : BeginLatex
  //
  //  Now we switch the directions of \code{gc} with that of \code{ga} in
  //  order to take the derivatives in the $x$-direction. This will give us
  //  $I_{xx}$.
  //
  //  Software Guide : EndLatex

  //  Software Guide : BeginCodeSnippet
  gc->SetDirection(0); // gc now works along X
  ga->SetDirection(1); // ga now works along Y

  gc->Update();
  duplicator->Update();

  ImageType::Pointer Ixx = duplicator->GetOutput();
  //  Software Guide : EndCodeSnippet

  writer->SetInput(Ixx);
  outputFileName = outputPrefix + "-Ixx.mhd";
  writer->SetFileName(outputFileName.c_str());
  writer->Update();

  //  Software Guide : BeginLatex
  //
  //  Now we can reset the directions to their original values, and compute
  //  first derivatives in different directions. Since we set both \code{gb}
  //  and \code{gc} to compute first derivatives, and \code{ga} to zero-order
  //  (which is only smoothing) we will obtain $I_{yz}$.
  //
  //  Software Guide : EndLatex

  //  Software Guide : BeginCodeSnippet
  ga->SetDirection(0);
  gb->SetDirection(1);
  gc->SetDirection(2);

  ga->SetZeroOrder();
  gb->SetFirstOrder();
  gc->SetFirstOrder();

  gc->Update();
  duplicator->Update();

  ImageType::Pointer Iyz = duplicator->GetOutput();
  //  Software Guide : EndCodeSnippet

  writer->SetInput(Iyz);
  outputFileName = outputPrefix + "-Iyz.mhd";
  writer->SetFileName(outputFileName.c_str());
  writer->Update();

  //  Software Guide : BeginLatex
  //
  //  Here is how you may easily obtain $I_{xz}$.
  //
  //  Software Guide : EndLatex

  //  Software Guide : BeginCodeSnippet
  ga->SetDirection(1);
  gb->SetDirection(0);
  gc->SetDirection(2);

  ga->SetZeroOrder();
  gb->SetFirstOrder();
  gc->SetFirstOrder();

  gc->Update();
  duplicator->Update();

  ImageType::Pointer Ixz = duplicator->GetOutput();
  //  Software Guide : EndCodeSnippet

  //  Software Guide : BeginLatex
  //
  //  For the sake of completeness, here is how you may compute
  //  $I_{xz}$ and $I_{xy}$.
  //
  //  Software Guide : EndLatex

  //  Software Guide : BeginCodeSnippet
  writer->SetInput(Ixz);
  outputFileName = outputPrefix + "-Ixz.mhd";
  writer->SetFileName(outputFileName.c_str());
  writer->Update();

  ga->SetDirection(2);
  gb->SetDirection(0);
  gc->SetDirection(1);

  ga->SetZeroOrder();
  gb->SetFirstOrder();
  gc->SetFirstOrder();

  gc->Update();
  duplicator->Update();

  ImageType::Pointer Ixy = duplicator->GetOutput();

  writer->SetInput(Ixy);
  outputFileName = outputPrefix + "-Ixy.mhd";
  writer->SetFileName(outputFileName.c_str());
  writer->Update();
  // Software Guide : EndCodeSnippet

  return EXIT_SUCCESS;
}
