/*
 * Copyright (C) 2005-2020 Centre National d'Etudes Spatiales (CNES)
 *
 * This file is part of Orfeo Toolbox
 *
 *     https://www.orfeo-toolbox.org/
 *
 * 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
 *
 * 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.
 */


/* Example usage:
./AtmosphericCorrectionSequencement Input/Romania_Extract.tif \
                                    Output/AtmosphericCorrectionSequencement.tif \
                                    Input/atmosphericCorrectionSequencement_alpha_beta.txt \
                                    Input/atmosphericCorrectionSequencement_solar_illumination.txt \
                                    Input/atmosphericCorrectionSequencement_wavelength_spectral_bands_spot4_1.txt \
                                    27.3 \
                                    4 \
                                    12 \
                                    152.7 \
                                    2.5 \
                                    -77.0 \
                                    1013. \
                                    2.48134 \
                                    0.34400 \
                                    1 \
                                    0.199854 \
                                    2 \
                                    0.020
*/

// \index{otb::VegetationIndex}
// \index{otb::VegetationIndex!header}
//
//
// The following example illustrates the application of atmospheric corrections to
// an optical multispectral image similar to Pleiades.
// These corrections are made in four steps :
// \begin{itemize}
// \item digital number to radiance correction;
// \item radiance to refletance image conversion;
// \item atmospheric correction for TOA (top of atmosphere) to TOC (top of canopy)
// reflectance estimation;
// \item correction of the adjacency effects taking into account the neighborhood contribution.
// \end{itemize}
//
// The manipulation of each class used for the different steps and the
// link with the 6S radiometry library will be explained. In particular,
// the API modifications that have been made in version 4.2 will be
// detailed. There was several reasons behind these modifications :
// \begin{itemize}
// \item fix design issues in the framework that were causing trouble
// when setting the atmospheric parameters
// \item allow the computation of the radiative terms by other libraries
// than 6S (such as SMAC method).
// \item allow the users of the OpticalCalibration application to set
// and override each correction parameter.
// \end{itemize}
//
// Let's look at the minimal code required to use this
// algorithm. First, the following header defining the
// \doxygen{otb}{AtmosphericCorrectionSequencement} class must be
// included.  For the numerical to radiance image, radiance to
// refletance image, and reflectance to atmospheric correction image
// corrections and the neighborhood correction, four header files are
// required.

#include "otbImageToRadianceImageFilter.h"
#include "otbRadianceToReflectanceImageFilter.h"
#include "otbReflectanceToSurfaceReflectanceImageFilter.h"
#include "otbSurfaceAdjacencyEffectCorrectionSchemeFilter.h"

// In version 4.2, the class \code{SurfaceAdjacencyEffect6SCorrectionSchemeFilter}
// has been renamed into \doxygen{otb}{SurfaceAdjacencyEffectCorrectionSchemeFilter},
// but it still does the same thing.
//
// This chain uses the 6S radiative
// transfer code to compute radiative terms (for instance upward and
// downward transmittance). The inputs needed are separated into
// two categories :
// \begin{itemize}
// \item The atmospheric correction parameters : physical parameters of the
// atmosphere when the image was taken (for instance : atmospheric pressure,
// water vapour amount, aerosol data, ...). They are stored in the class
// \footnote{Before version 4.2, this class was storing all correction
// parameters} \doxygen{otb}{AtmosphericCorrectionParameters}.
// \item The acquisition correction parameters : sensor related information
// about the way the image was taken, usually available with the image
// metadata (for instance : solar angles, spectral
// sensitivity, ...). They are stored in the class
// \doxygen{otb}{ImageMetadataCorrectionParameters}.
// \end{itemize}
//
// The class \doxygen{otb}{RadiometryCorrectionParametersToAtmisphericRadiativeTerms}
// computes the radiative terms using these two types of parameters. It
// contains a single static method that calls the 6S library. The header
// also includes the classes to manipulate correction parameters and radiative
// terms.


#include "otbVectorImage.h"
#include "otbImageFileReader.h"
#include "otbImageFileWriter.h"
#include <string>

int main(int argc, char* argv[])
{
  if (argc != 19)
  {
    std::cerr << "Missing Parameters " << std::endl;
    std::cerr << "Usage: " << argv[0] << std::endl;
    std::cerr << " inputImage outputImage atmosphericCorrectionSequencement_alpha_beta.txt atmosphericCorrectionSequencement_solar_illumination.txt "
                 "atmosphericCorrectionSequencement_wavelength_spectral_bands_spot4_1.txt SolarZenithalAngle day month SolarAzimuthalAngle "
                 "ViewingZenithalAngle ViewingAzimuthalAngle AtmosphericPresure WaterVaporAmount OzoneAmount AerosolModel AerosolOpticalThickness "
                 "WindowRadiusForAdjacencyCorrection PixelSpacing"
              << std::endl;
    std::cerr << std::endl;
    return 1;
  }

  // Image types are now defined using pixel types and
  // dimension. The input image is defined as an \doxygen{otb}{VectorImage},
  // the output image is a \doxygen{otb}{VectorImage}. To simplify, input and
  // output image types are the same one.

  const unsigned int Dimension = 2;
  using PixelType              = double;
  using ImageType              = otb::VectorImage<PixelType, Dimension>;

  // We instantiate reader and writer types
  using ReaderType           = otb::ImageFileReader<ImageType>;
  using WriterType           = otb::ImageFileWriter<ImageType>;
  ReaderType::Pointer reader = ReaderType::New();

  // The \code{GenerateOutputInformation()} reader method is called
  // to know the number of component per pixel of the image.  It is
  // recommended to
  // place \code{GenerateOutputInformation} calls in a \code{try/catch} block in case
  // errors occur and exceptions are thrown.

  reader->SetFileName(argv[1]);
  try
  {
    reader->GenerateOutputInformation();
  }
  catch (itk::ExceptionObject& excep)
  {
    std::cerr << "Exception caught !" << std::endl;
    std::cerr << excep << std::endl;
  }
  catch (...)
  {
    std::cout << "Unknown exception !" << std::endl;
    return EXIT_FAILURE;
  }

  unsigned int nbOfComponent = reader->GetOutput()->GetNumberOfComponentsPerPixel();

  //-------------------------------
  // The \doxygen{otb}{ImageToRadianceImageFilter}
  // type is defined and instancied. This class uses a functor applied
  // to each component of each pixel ($\mathbf{X^{k}}$) whose formula is:
  //
  // \begin{equation}
  // \mathbf{L_{TOA}^{k}} = \frac{ X^{k} } { \alpha_{k} } + \beta_{k}.
  // \end{equation}
  //
  // Where :
  // \begin{itemize}
  // \item $\mathbf{L_{TOA}^{k}}$ is the incident radiance (in
  // $W.m^{-2}.sr^{-1}.\mu m^{-1}$);
  // \item $\mathbf{X^{k}}$ is the measured digital number (ie. the input image pixel component);
  // \item $\alpha_{k}$ is the absolute calibration gain for the channel k;
  // \item $\beta_{k}$ is the absolute calibration bias for the channel k.
  // \end{itemize}

  using ImageToRadianceImageFilterType = otb::ImageToRadianceImageFilter<ImageType, ImageType>;

  ImageToRadianceImageFilterType::Pointer filterImageToRadiance = ImageToRadianceImageFilterType::New();
  using VectorType                                              = ImageToRadianceImageFilterType::VectorType;
  VectorType alpha(nbOfComponent);
  VectorType beta(nbOfComponent);
  alpha.Fill(0);
  beta.Fill(0);
  std::ifstream fin;
  fin.open(argv[3]);
  double dalpha(0.), dbeta(0.);
  for (unsigned int i = 0; i < nbOfComponent; ++i)
  {
    fin >> dalpha;
    fin >> dbeta;
    alpha[i] = dalpha;
    beta[i]  = dbeta;
  }
  fin.close();

  // Here, $\alpha$ and $\beta$ are read from an ASCII file given in input,
  // stored in a vector and passed to the class.

  filterImageToRadiance->SetAlpha(alpha);
  filterImageToRadiance->SetBeta(beta);

  //-------------------------------
  // The \doxygen{otb}{RadianceToReflectanceImageFilter}
  // type is defined and instancied.
  // This class used a functor applied to each component of each pixel
  // of the radiance filter output ($\mathbf{L_{TOA}^{k}}$):
  //
  // \begin{equation}
  // \rho_{TOA}^{k} = \frac{ \pi.\mathbf{L_{TOA}^{k}} } { E_{S}^{k}.cos(\theta_{S}).d/d_{0} }.
  // \end{equation}
  //
  // Where :
  // \begin{itemize}
  // \item $\mathbf{\rho_{TOA}^{k}}$ is the reflectance measured by the sensor;
  // \item $\theta_{S}$ is the zenithal solar angle in degrees;
  // \item $E_{S}^{k}$ is the solar illumination out of the atmosphere measured at a distance
  // $d_{0}$ from the Earth;
  // \item $d/d_{0}$ is the ratio between the Earth-Sun distance at
  // the acquisition date and the mean Earth-Sun distance. The ratio can be directly
  // given to the class or computed using a 6S routine. TODO
  // In the last case (that is the one of this example), the user has to precise
  // the month and the day of the acquisition.
  // \end{itemize}

  using RadianceToReflectanceImageFilterType                                = otb::RadianceToReflectanceImageFilter<ImageType, ImageType>;
  RadianceToReflectanceImageFilterType::Pointer filterRadianceToReflectance = RadianceToReflectanceImageFilterType::New();

  using VectorType = RadianceToReflectanceImageFilterType::VectorType;

  VectorType solarIllumination(nbOfComponent);
  solarIllumination.Fill(0);

  fin.open(argv[4]);
  double dsolarIllumination(0.);
  for (unsigned int i = 0; i < nbOfComponent; ++i)
  {
    fin >> dsolarIllumination;
    solarIllumination[i] = dsolarIllumination;
  }
  fin.close();

  // The solar illumination is read from a ASCII file given in input,
  // stored in a vector
  // and given to the class.
  // Day, month and zenital solar angle are inputs and can be directly given to the class.

  filterRadianceToReflectance->SetZenithalSolarAngle(static_cast<double>(atof(argv[6])));
  filterRadianceToReflectance->SetDay(atoi(argv[7]));
  filterRadianceToReflectance->SetMonth(atoi(argv[8]));
  filterRadianceToReflectance->SetSolarIllumination(solarIllumination);

  //-------------------------------
  // At this step of the chain, radiative information are nedeed to compute
  // the contribution of the atmosphere (such as atmosphere transmittance
  // and reflectance). Those information will be computed from different
  // correction parameters stored in \doxygen{otb}{AtmosphericCorrectionParameters}
  // and \doxygen{otb}{ImageMetadataCorrectionParameters} instances.
  // These {\em containers} will be given to the static function \texttt{Compute}
  // from \doxygen{otb}{RadiometryCorrectionParametersToAtmosphericRadiativeTerms}
  // class, which will call a 6S routine that will compute the needed
  // radiometric information and store them in a
  // \doxygen{otb}{AtmosphericRadiativeTerms} class instance.
  // For this,
  // \doxygen{otb}{RadiometryCorrectionParametersToAtmosphericRadiativeTerms},
  // \doxygen{otb}{AtmosphericCorrectionParameters},
  // \doxygen{otb}{ImageMetadataCorrectionParameters} and
  // \doxygen{otb}{AtmosphericRadiativeTerms}
  // types are defined and instancied.

  using RadiometryCorrectionParametersToRadiativeTermsType = otb::RadiometryCorrectionParametersToAtmosphericRadiativeTerms;

  using AtmosphericCorrectionParametersType = otb::AtmosphericCorrectionParameters;

  using AcquisitionCorrectionParametersType = otb::ImageMetadataCorrectionParameters;

  using AtmosphericRadiativeTermsType = otb::AtmosphericRadiativeTerms;
  using AerosolModelType              = AtmosphericCorrectionParametersType::AerosolModelType;
  using FilterFunctionValuesType      = otb::FilterFunctionValues;
  using ValuesVectorType              = FilterFunctionValuesType::ValuesVectorType;

  AtmosphericCorrectionParametersType::Pointer dataAtmosphericCorrectionParameters = AtmosphericCorrectionParametersType::New();
  AcquisitionCorrectionParametersType::Pointer dataAcquisitionCorrectionParameters = AcquisitionCorrectionParametersType::New();
  AtmosphericRadiativeTermsType::Pointer       dataAtmosphericRadiativeTerms       = AtmosphericRadiativeTermsType::New();

  float minSpectralValue(0.);
  float maxSpectralValue(0.);
  float userStep(0.);
  float value(0.);

  unsigned int     nbBands(0);
  unsigned int     nbValuesPerBand(0);
  std::string      sString;
  ValuesVectorType vector;

  fin.open(argv[5]);
  fin >> nbBands;
  for (unsigned int i = 0; i < nbBands; ++i)
  {
    vector.clear();
    fin >> sString;
    fin >> minSpectralValue;
    fin >> maxSpectralValue;
    fin >> userStep;
    fin >> nbValuesPerBand;
    for (unsigned int j = 0; j < nbValuesPerBand; ++j)
    {
      fin >> value;
      vector.push_back(value);
    }
    FilterFunctionValuesType::Pointer functionValues = FilterFunctionValuesType::New();
    functionValues->SetFilterFunctionValues(vector);
    functionValues->SetMinSpectralValue(minSpectralValue);
    functionValues->SetMaxSpectralValue(maxSpectralValue);
    functionValues->SetUserStep(userStep);
    dataAcquisitionCorrectionParameters->SetWavelengthSpectralBandWithIndex(i, functionValues);
  }

  fin.close();

  // The \doxygen{otb}{ImageMetadataCorrectionParameters} class stores
  // several parameters that are generally present in the image metadata :
  // \begin{itemize}
  // \item The zenithal and azimutal solar angles that describe the solar incidence
  // configuration (in degrees);
  // \item The zenithal and azimuthal viewing angles that describe the viewing
  // direction (in degrees);
  // \item The month and the day of the acquisition;
  // \item The filter function that is the values of the filter function for one
  // spectral band, from $\lambda_{inf}$ to $\lambda_{sup}$ by step of 2.5 nm.
  // One filter function by channel is required.
  // This last parameter are read in text files, the other one are directly given to the class.
  // \end{itemize}
  //
  // When this container is not set in the ReflectanceToSurfaceReflectance
  // filter, it is automatically filled using the image metadata. The
  // following lines show that it is also possible to set the values manually.

  // Set parameters
  dataAcquisitionCorrectionParameters->SetSolarZenithalAngle(static_cast<double>(atof(argv[6])));

  dataAcquisitionCorrectionParameters->SetSolarAzimutalAngle(static_cast<double>(atof(argv[9])));

  dataAcquisitionCorrectionParameters->SetViewingZenithalAngle(static_cast<double>(atof(argv[10])));

  dataAcquisitionCorrectionParameters->SetViewingAzimutalAngle(static_cast<double>(atof(argv[11])));

  dataAcquisitionCorrectionParameters->SetMonth(atoi(argv[8]));

  dataAcquisitionCorrectionParameters->SetDay(atoi(argv[7]));

  // The \doxygen{otb}{AtmosphericCorrectionParameters} class stores
  // physical parameters of the atmosphere that are not impacted
  // by the viewing angles of the image :
  // \begin{itemize}
  // \item The atmospheric pressure;
  // \item The water vapor amount, that is, the total water vapor content over vertical
  // atmospheric column;
  // \item The ozone amount that is the Stratospheric ozone layer content;
  // \item The aerosol model that is the kind of particles (no aerosol, continental,
  // maritime, urban, desertic);
  // \item The aerosol optical thickness at 550 nm that is the is the Radiative impact
  //  of aerosol for the reference wavelength 550 nm;
  // \end{itemize}

  dataAtmosphericCorrectionParameters->SetAtmosphericPressure(static_cast<double>(atof(argv[12])));

  dataAtmosphericCorrectionParameters->SetWaterVaporAmount(static_cast<double>(atof(argv[13])));

  dataAtmosphericCorrectionParameters->SetOzoneAmount(static_cast<double>(atof(argv[14])));

  AerosolModelType aerosolModel = static_cast<AerosolModelType>(::atoi(argv[15]));

  dataAtmosphericCorrectionParameters->SetAerosolModel(aerosolModel);

  dataAtmosphericCorrectionParameters->SetAerosolOptical(static_cast<double>(atof(argv[16])));

  // Once those parameters are loaded, they are used by the 6S library
  // to compute the needed radiometric information. The
  // RadiometryCorrectionParametersToAtmosphericRadiativeTerms class
  // provides a static function to perform this step\footnote{Before version
  // 4.2, it was done with the filter
  // AtmosphericCorrectionParametersTo6SAtmosphericRadiativeTerms}.

  AtmosphericRadiativeTermsType::Pointer atmosphericRadiativeTerms =
      RadiometryCorrectionParametersToRadiativeTermsType::Compute(dataAtmosphericCorrectionParameters, dataAcquisitionCorrectionParameters);

  // The output is stored inside an instance of the
  // \doxygen{otb}{AtmosphericRadiativeTerms} class.
  // This class contains (for each channel of the image)
  // \begin{itemize}
  // \item The Intrinsic atmospheric reflectance that takes into account for the molecular scattering
  // and the aerosol scattering attenuated by water vapor absorption;
  // \item The spherical albedo of the atmosphere;
  // \item The total gaseous transmission (for all species);
  // \item The total transmittance of the atmosphere from sun to ground (downward transmittance)
  // and from ground to space sensor (upward transmittance).
  // \end{itemize}

  //-------------------------------
  // Atmospheric corrections can now start.
  // First, an instance of \doxygen{otb}{ReflectanceToSurfaceReflectanceImageFilter} is created.

  using ReflectanceToSurfaceReflectanceImageFilterType = otb::ReflectanceToSurfaceReflectanceImageFilter<ImageType, ImageType>;

  ReflectanceToSurfaceReflectanceImageFilterType::Pointer filterReflectanceToSurfaceReflectanceImageFilter =
      ReflectanceToSurfaceReflectanceImageFilterType::New();

  // The aim of the atmospheric correction is to invert the surface reflectance
  // (for each pixel of the input image) from the TOA reflectance and from simulations
  // of the atmospheric radiative functions corresponding to the geometrical conditions
  // of the observation and to the atmospheric components.
  // The process required to be applied on each pixel of the image, band by band with
  // the following formula:
  //
  // \begin{equation}
  // \rho_{S}^{unif} = \frac{ \mathbf{A} }{ 1 + Sx\mathbf{A} }
  // \end{equation}
  // Where,
  // \begin{equation}
  // \mathbf{A} = \frac{ \rho_{TOA} - \rho_{atm} }{ T(\mu_{S}).T(\mu_{V}).t_{g}^{all gas} }
  // \end{equation}
  //
  // With :
  // \begin{itemize}
  // \item $\rho_{TOA}$ is the reflectance at the top of the atmosphere;
  // \item $\rho_{S}^{unif}$ is the ground reflectance under assumption
  // of a lambertian surface and an uniform environment;
  // \item $\rho_{atm}$ is the intrinsic atmospheric reflectance;
  // \item $t_{g}^{all gas}$ is the spherical albedo of the atmosphere;
  // \item $T(\mu_{S})$ is the downward transmittance;
  // \item $T(\mu_{V})$ is the upward transmittance.
  // \end{itemize}
  // All those parameters are contained in the AtmosphericRadiativeTerms
  // container.

  filterReflectanceToSurfaceReflectanceImageFilter->SetAtmosphericRadiativeTerms(atmosphericRadiativeTerms);

  //-------------------------------
  // Next (and last step) is the neighborhood correction.
  // For this, the SurfaceAdjacencyEffectCorrectionSchemeFilter class is used.
  // The previous surface reflectance inversion is performed under the assumption of a
  // homogeneous ground environment. The following step allows correcting the adjacency
  // effect on the radiometry of pixels. The method is based on the decomposition of
  // the observed signal as the summation of the own contribution of the target pixel and
  // of the contributions of neighbored pixels moderated by their distance to the target pixel.
  // A simplified relation may be :
  // \begin{equation}
  // \rho{S} = \frac{ \rho_{S}^{unif}.T(\mu_{V}) - <\rho{S}>.t_{d}(\mu_{V}) }{ exp(-\delta/\mu_{V}) }
  // \end{equation}
  // With :
  // \begin{itemize}
  // \item $\rho_{S}^{unif}$ is the ground reflectance under assumption of an homogeneous environment;
  // \item $T(\mu_{V})$ is the upward transmittance;
  // \item $t_{d}(\mu_{S})$ is the upward diffus transmittance;
  // \item $exp(-\delta/\mu_{V})$ is the upward direct transmittance;
  // \item $\rho_{S}$ is the environment contribution to the pixel target reflectance in the total
  // observed signal.
  // \begin{equation}
  // \rho{S} = \sum{j}\sum{i}f(r(i, j))\times \rho_{S}^{unif}(i, j)
  // \end{equation}
  // where,
  // \begin{itemize}
  // \item r(i, j) is the distance between the pixel(i, j) and the central pixel of the window in $km$;
  // \item f(r) is the global environment function.
  // \begin{equation}
  // f(r) = \frac{t_{d}^{R}(\mu_{V}).f_{R}(r)+t_{d}^{A}(\mu_{V}).f_{A}(r)}{ t_{d}(\mu_{V}) }
  // \end{equation}
  // \end{itemize}
  // \end{itemize}
  // The neighborhood consideration window size is given by the window radius.
  //
  // An instance of \doxygen{otb}{SurfaceAdjacencyEffectCorrectionSchemeFilter}
  // is created. This class has an interface quite similar to
  // \doxygen{otb}{ReflectanceToSurfaceReflectance}. They both need radiative terms
  // (\doxygen{otb}{AtmosphericRadiativeTerms}), so it is possible to compute
  // them outside the filter and set them directly in the filter. The other
  // solution is to give as input the two parameters containers ("atmospheric"
  // and "acquisition" parameters), then the filter will compute the radiative
  // terms internally. If the "acquisition" correction parameters are not
  // present, the filter will try to get them from the image metadata.

  using SurfaceAdjacencyEffectCorrectionSchemeFilterType = otb::SurfaceAdjacencyEffectCorrectionSchemeFilter<ImageType, ImageType>;
  SurfaceAdjacencyEffectCorrectionSchemeFilterType::Pointer filterSurfaceAdjacencyEffectCorrectionSchemeFilter =
      SurfaceAdjacencyEffectCorrectionSchemeFilterType::New();

  // Four inputs are needed to compute the neighborhood contribution:
  // \begin{itemize}
  // \item The radiative terms (stored in the AtmosphericRadiativeTerms container);
  // \item The zenithal viewing angle;
  // \item The neighborhood window radius;
  // \item The pixel spacing in kilometers.
  // \end{itemize}
  filterSurfaceAdjacencyEffectCorrectionSchemeFilter->SetAtmosphericRadiativeTerms(atmosphericRadiativeTerms);
  filterSurfaceAdjacencyEffectCorrectionSchemeFilter->SetZenithalViewingAngle(dataAcquisitionCorrectionParameters->GetViewingZenithalAngle());
  filterSurfaceAdjacencyEffectCorrectionSchemeFilter->SetWindowRadius(atoi(argv[17]));
  filterSurfaceAdjacencyEffectCorrectionSchemeFilter->SetPixelSpacingInKilometers(static_cast<double>(atof(argv[18])));

  //-------------------------------
  WriterType::Pointer writer = WriterType::New();
  // At this step, each filter of the chain is instancied and every one has its
  // input parameters set. A name can be given to the output image, each filter
  //  can be linked to the next one and create the final processing chain.

  writer->SetFileName(argv[2]);

  filterImageToRadiance->SetInput(reader->GetOutput());
  filterRadianceToReflectance->SetInput(filterImageToRadiance->GetOutput());
  filterReflectanceToSurfaceReflectanceImageFilter->SetInput(filterRadianceToReflectance->GetOutput());
  filterSurfaceAdjacencyEffectCorrectionSchemeFilter->SetInput(filterReflectanceToSurfaceReflectanceImageFilter->GetOutput());

  writer->SetInput(filterSurfaceAdjacencyEffectCorrectionSchemeFilter->GetOutput());

  //  The invocation of the \code{Update()} method on the writer triggers the
  //  execution of the pipeline.  It is recommended to place this call in a
  //  \code{try/catch} block in case errors occur and exceptions are thrown.
  try
  {
    writer->Update();
  }
  catch (itk::ExceptionObject& excep)
  {
    std::cerr << "Exception caught !" << std::endl;
    std::cerr << excep << std::endl;
  }
  catch (...)
  {
    std::cout << "Unknown exception !" << std::endl;
    return EXIT_FAILURE;
  }

  return EXIT_SUCCESS;
}
