/* ---------------------------------------------------------------------
 *
 * Copyright (C) 2009 - 2022 by the deal.II authors
 *
 * This file is part of the deal.II library.
 *
 * The deal.II library is free software; you can use it, redistribute
 * it, and/or modify it under the terms of the GNU Lesser General
 * Public License as published by the Free Software Foundation; either
 * version 2.1 of the License, or (at your option) any later version.
 * The full text of the license can be found in the file LICENSE.md at
 * the top level directory of deal.II.
 *
 * ---------------------------------------------------------------------

 *
 * Author: Guido Kanschat, Texas A&M University, 2009
 */


// The first few files have already been covered in previous examples and will
// thus not be further commented on:
#include <deal.II/base/quadrature_lib.h>
#include <deal.II/base/function.h>
#include <deal.II/lac/vector.h>
#include <deal.II/lac/dynamic_sparsity_pattern.h>
#include <deal.II/lac/sparse_matrix.h>
#include <deal.II/grid/tria.h>
#include <deal.II/grid/grid_generator.h>
#include <deal.II/grid/grid_out.h>
#include <deal.II/grid/grid_refinement.h>
#include <deal.II/fe/fe_values.h>
#include <deal.II/dofs/dof_handler.h>
#include <deal.II/dofs/dof_tools.h>
#include <deal.II/numerics/data_out.h>
#include <deal.II/fe/mapping_q1.h>
// Here the discontinuous finite elements are defined. They are used in the same
// way as all other finite elements, though -- as you have seen in previous
// tutorial programs -- there isn't much user interaction with finite element
// classes at all: they are passed to <code>DoFHandler</code> and
// <code>FEValues</code> objects, and that is about it.
#include <deal.II/fe/fe_dgq.h>
// We are going to use the simplest possible solver, called Richardson
// iteration, that represents a simple defect correction. This, in combination
// with a block SSOR preconditioner (defined in precondition_block.h), that
// uses the special block matrix structure of system matrices arising from DG
// discretizations.
#include <deal.II/lac/solver_richardson.h>
#include <deal.II/lac/precondition_block.h>
// We are going to use gradients as refinement indicator.
#include <deal.II/numerics/derivative_approximation.h>

// Here come the new include files for using the MeshWorker framework. The first
// contains the class MeshWorker::DoFInfo, which provides local integrators with
// a mapping between local and global degrees of freedom. It stores the results
// of local integrals as well in its base class MeshWorker::LocalResults.
// In the second of these files, we find an object of type
// MeshWorker::IntegrationInfo, which is mostly a wrapper around a group of
// FEValues objects. The file <tt>meshworker/simple.h</tt> contains classes
// assembling locally integrated data into a global system containing only a
// single matrix. Finally, we will need the file that runs the loop over all
// mesh cells and faces.
#include <deal.II/meshworker/dof_info.h>
#include <deal.II/meshworker/integration_info.h>
#include <deal.II/meshworker/simple.h>
#include <deal.II/meshworker/loop.h>

// Like in all programs, we finish this section by including the needed C++
// headers and declaring we want to use objects in the dealii namespace without
// prefix.
#include <iostream>
#include <fstream>


namespace Step12
{
  using namespace dealii;

  // @sect3{Equation data}
  //
  // First, we define a class describing the inhomogeneous boundary data. Since
  // only its values are used, we implement value_list(), but leave all other
  // functions of Function undefined.
  template <int dim>
  class BoundaryValues : public Function<dim>
  {
  public:
    BoundaryValues() = default;
    virtual void value_list(const std::vector<Point<dim>> &points,
                            std::vector<double> &          values,
                            const unsigned int component = 0) const override;
  };

  // Given the flow direction, the inflow boundary of the unit square $[0,1]^2$
  // are the right and the lower boundaries. We prescribe discontinuous boundary
  // values 1 and 0 on the x-axis and value 0 on the right boundary. The values
  // of this function on the outflow boundaries will not be used within the DG
  // scheme.
  template <int dim>
  void BoundaryValues<dim>::value_list(const std::vector<Point<dim>> &points,
                                       std::vector<double> &          values,
                                       const unsigned int component) const
  {
    (void)component;
    AssertIndexRange(component, 1);
    AssertDimension(values.size(), points.size());

    for (unsigned int i = 0; i < values.size(); ++i)
      {
        if (points[i](0) < 0.5)
          values[i] = 1.;
        else
          values[i] = 0.;
      }
  }


  // Finally, a function that computes and returns the wind field
  // $\beta=\beta(\mathbf x)$. As explained in the introduction, we will use a
  // rotational field around the origin in 2d. In 3d, we simply leave the
  // $z$-component unset (i.e., at zero), whereas the function can not be used
  // in 1d in its current implementation:
  template <int dim>
  Tensor<1, dim> beta(const Point<dim> &p)
  {
    Assert(dim >= 2, ExcNotImplemented());

    Tensor<1, dim> wind_field;
    wind_field[0] = -p[1];
    wind_field[1] = p[0];
    wind_field /= wind_field.norm();

    return wind_field;
  }


  // @sect3{The AdvectionProblem class}
  //
  // After this preparations, we proceed with the main class of this program,
  // called AdvectionProblem. It is basically the main class of step-6. We do
  // not have an AffineConstraints object, because there are no hanging node
  // constraints in DG discretizations.

  // Major differences will only come up in the implementation of the assemble
  // functions, since here, we not only need to cover the flux integrals over
  // faces, we also use the MeshWorker interface to simplify the loops
  // involved.
  template <int dim>
  class AdvectionProblem
  {
  public:
    AdvectionProblem();
    void run();

  private:
    void setup_system();
    void assemble_system();
    void solve(Vector<double> &solution);
    void refine_grid();
    void output_results(const unsigned int cycle) const;

    Triangulation<dim>   triangulation;
    const MappingQ1<dim> mapping;

    // Furthermore we want to use DG elements of degree 1 (but this is only
    // specified in the constructor). If you want to use a DG method of a
    // different degree the whole program stays the same, only replace 1 in
    // the constructor by the desired polynomial degree.
    FE_DGQ<dim>     fe;
    DoFHandler<dim> dof_handler;

    // The next four members represent the linear system to be solved.
    // <code>system_matrix</code> and <code>right_hand_side</code> are generated
    // by <code>assemble_system()</code>, the <code>solution</code> is computed
    // in <code>solve()</code>. The <code>sparsity_pattern</code> is used to
    // determine the location of nonzero elements in <code>system_matrix</code>.
    SparsityPattern      sparsity_pattern;
    SparseMatrix<double> system_matrix;

    Vector<double> solution;
    Vector<double> right_hand_side;

    // Finally, we have to provide functions that assemble the cell, boundary,
    // and inner face terms. Within the MeshWorker framework, the loop over all
    // cells and much of the setup of operations will be done outside this
    // class, so all we have to provide are these three operations. They will
    // then work on intermediate objects for which first, we here define
    // alias to the info objects handed to the local integration functions
    // in order to make our life easier below.
    using DoFInfo  = MeshWorker::DoFInfo<dim>;
    using CellInfo = MeshWorker::IntegrationInfo<dim>;

    // The following three functions are then the ones that get called inside
    // the generic loop over all cells and faces. They are the ones doing the
    // actual integration.
    //
    // In our code below, these functions do not access member variables of the
    // current class, so we can mark them as <code>static</code> and simply pass
    // pointers to these functions to the MeshWorker framework. If, however,
    // these functions would want to access member variables (or needed
    // additional arguments beyond the ones specified below), we could use the
    // facilities of lambda functions to provide the
    // MeshWorker framework with objects that act as if they had the required
    // number and types of arguments, but have in fact other arguments already
    // bound.
    static void integrate_cell_term(DoFInfo &dinfo, CellInfo &info);
    static void integrate_boundary_term(DoFInfo &dinfo, CellInfo &info);
    static void integrate_face_term(DoFInfo & dinfo1,
                                    DoFInfo & dinfo2,
                                    CellInfo &info1,
                                    CellInfo &info2);
  };


  // We start with the constructor. The 1 in the constructor call of
  // <code>fe</code> is the polynomial degree.
  template <int dim>
  AdvectionProblem<dim>::AdvectionProblem()
    : mapping()
    , fe(1)
    , dof_handler(triangulation)
  {}


  template <int dim>
  void AdvectionProblem<dim>::setup_system()
  {
    // In the function that sets up the usual finite element data structures, we
    // first need to distribute the DoFs.
    dof_handler.distribute_dofs(fe);

    // We start by generating the sparsity pattern. To this end, we first fill
    // an intermediate object of type DynamicSparsityPattern with the couplings
    // appearing in the system. After building the pattern, this object is
    // copied to <code>sparsity_pattern</code> and can be discarded.

    // To build the sparsity pattern for DG discretizations, we can call the
    // function analogue to DoFTools::make_sparsity_pattern, which is called
    // DoFTools::make_flux_sparsity_pattern:
    DynamicSparsityPattern dsp(dof_handler.n_dofs());
    DoFTools::make_flux_sparsity_pattern(dof_handler, dsp);
    sparsity_pattern.copy_from(dsp);

    // Finally, we set up the structure of all components of the linear system.
    system_matrix.reinit(sparsity_pattern);
    solution.reinit(dof_handler.n_dofs());
    right_hand_side.reinit(dof_handler.n_dofs());
  }

  // @sect4{The assemble_system function}

  // Here we see the major difference to assembling by hand. Instead of writing
  // loops over cells and faces, we leave all this to the MeshWorker framework.
  // In order to do so, we just have to define local integration functions and
  // use one of the classes in namespace MeshWorker::Assembler to build the
  // global system.
  template <int dim>
  void AdvectionProblem<dim>::assemble_system()
  {
    // This is the magic object, which knows everything about the data
    // structures and local integration.  This is the object doing the work in
    // the function MeshWorker::loop(), which is implicitly called by
    // MeshWorker::integration_loop() below. After the functions to which we
    // provide pointers did the local integration, the
    // MeshWorker::Assembler::SystemSimple object distributes these into the
    // global sparse matrix and the right hand side vector.
    MeshWorker::IntegrationInfoBox<dim> info_box;

    // First, we initialize the quadrature formulae and the update flags in the
    // worker base class. For quadrature, we play safe and use a QGauss formula
    // with number of points one higher than the polynomial degree used. Since
    // the quadratures for cells, boundary and interior faces can be selected
    // independently, we have to hand over this value three times.
    const unsigned int n_gauss_points = dof_handler.get_fe().degree + 1;
    info_box.initialize_gauss_quadrature(n_gauss_points,
                                         n_gauss_points,
                                         n_gauss_points);

    // These are the types of values we need for integrating our system. They
    // are added to the flags used on cells, boundary and interior faces, as
    // well as interior neighbor faces, which is forced by the four @p true
    // values.
    info_box.initialize_update_flags();
    UpdateFlags update_flags =
      update_quadrature_points | update_values | update_gradients;
    info_box.add_update_flags(update_flags, true, true, true, true);

    // After preparing all data in <tt>info_box</tt>, we initialize the FEValues
    // objects in there.
    info_box.initialize(fe, mapping);

    // The object created so far helps us do the local integration on each cell
    // and face. Now, we need an object which receives the integrated (local)
    // data and forwards them to the assembler.
    MeshWorker::DoFInfo<dim> dof_info(dof_handler);

    // Now, we have to create the assembler object and tell it, where to put the
    // local data. These will be our system matrix and the right hand side.
    MeshWorker::Assembler::SystemSimple<SparseMatrix<double>, Vector<double>>
      assembler;
    assembler.initialize(system_matrix, right_hand_side);

    // Finally, the integration loop over all active cells (determined by the
    // first argument, which is an active iterator).
    //
    // As noted in the discussion when declaring the local integration functions
    // in the class declaration, the arguments expected by the assembling
    // integrator class are not actually function pointers. Rather, they are
    // objects that can be called like functions with a certain number of
    // arguments. Consequently, we could also pass objects with appropriate
    // operator() implementations here, or lambda functions if the local
    // integrators were, for example, non-static member functions.
    MeshWorker::loop<dim,
                     dim,
                     MeshWorker::DoFInfo<dim>,
                     MeshWorker::IntegrationInfoBox<dim>>(
      dof_handler.begin_active(),
      dof_handler.end(),
      dof_info,
      info_box,
      &AdvectionProblem<dim>::integrate_cell_term,
      &AdvectionProblem<dim>::integrate_boundary_term,
      &AdvectionProblem<dim>::integrate_face_term,
      assembler);
  }


  // @sect4{The local integrators}

  // These are the functions given to the MeshWorker::integration_loop() called
  // just above. They compute the local contributions to the system matrix and
  // right hand side on cells and faces.
  template <int dim>
  void AdvectionProblem<dim>::integrate_cell_term(DoFInfo & dinfo,
                                                  CellInfo &info)
  {
    // First, let us retrieve some of the objects used here from @p info. Note
    // that these objects can handle much more complex structures, thus the
    // access here looks more complicated than might seem necessary.
    const FEValuesBase<dim> &  fe_values    = info.fe_values();
    FullMatrix<double> &       local_matrix = dinfo.matrix(0).matrix;
    const std::vector<double> &JxW          = fe_values.get_JxW_values();

    // With these objects, we continue local integration like always. First, we
    // loop over the quadrature points and compute the advection vector in the
    // current point.
    for (unsigned int point = 0; point < fe_values.n_quadrature_points; ++point)
      {
        const Tensor<1, dim> beta_at_q_point =
          beta(fe_values.quadrature_point(point));

        // We solve a homogeneous equation, thus no right hand side shows up in
        // the cell term.  What's left is integrating the matrix entries.
        for (unsigned int i = 0; i < fe_values.dofs_per_cell; ++i)
          for (unsigned int j = 0; j < fe_values.dofs_per_cell; ++j)
            local_matrix(i, j) += -beta_at_q_point *                //
                                  fe_values.shape_grad(i, point) *  //
                                  fe_values.shape_value(j, point) * //
                                  JxW[point];
      }
  }

  // Now the same for the boundary terms. Note that now we use FEValuesBase, the
  // base class for both FEFaceValues and FESubfaceValues, in order to get
  // access to normal vectors.
  template <int dim>
  void AdvectionProblem<dim>::integrate_boundary_term(DoFInfo & dinfo,
                                                      CellInfo &info)
  {
    const FEValuesBase<dim> &fe_face_values = info.fe_values();
    FullMatrix<double> &     local_matrix   = dinfo.matrix(0).matrix;
    Vector<double> &         local_vector   = dinfo.vector(0).block(0);

    const std::vector<double> &        JxW = fe_face_values.get_JxW_values();
    const std::vector<Tensor<1, dim>> &normals =
      fe_face_values.get_normal_vectors();

    std::vector<double> g(fe_face_values.n_quadrature_points);

    static BoundaryValues<dim> boundary_function;
    boundary_function.value_list(fe_face_values.get_quadrature_points(), g);

    for (unsigned int point = 0; point < fe_face_values.n_quadrature_points;
         ++point)
      {
        const double beta_dot_n =
          beta(fe_face_values.quadrature_point(point)) * normals[point];
        if (beta_dot_n > 0)
          for (unsigned int i = 0; i < fe_face_values.dofs_per_cell; ++i)
            for (unsigned int j = 0; j < fe_face_values.dofs_per_cell; ++j)
              local_matrix(i, j) += beta_dot_n *                           //
                                    fe_face_values.shape_value(j, point) * //
                                    fe_face_values.shape_value(i, point) * //
                                    JxW[point];
        else
          for (unsigned int i = 0; i < fe_face_values.dofs_per_cell; ++i)
            local_vector(i) += -beta_dot_n *                          //
                               g[point] *                             //
                               fe_face_values.shape_value(i, point) * //
                               JxW[point];
      }
  }

  // Finally, the interior face terms. The difference here is that we receive
  // two info objects, one for each cell adjacent to the face and we assemble
  // four matrices, one for each cell and two for coupling back and forth.
  template <int dim>
  void AdvectionProblem<dim>::integrate_face_term(DoFInfo & dinfo1,
                                                  DoFInfo & dinfo2,
                                                  CellInfo &info1,
                                                  CellInfo &info2)
  {
    // For quadrature points, weights, etc., we use the FEValuesBase object of
    // the first argument.
    const FEValuesBase<dim> &fe_face_values = info1.fe_values();
    const unsigned int       dofs_per_cell  = fe_face_values.dofs_per_cell;

    // For additional shape functions, we have to ask the neighbors
    // FEValuesBase.
    const FEValuesBase<dim> &fe_face_values_neighbor = info2.fe_values();
    const unsigned int       neighbor_dofs_per_cell =
      fe_face_values_neighbor.dofs_per_cell;

    // Then we get references to the four local matrices. The letters u and v
    // refer to trial and test functions, respectively. The %numbers indicate
    // the cells provided by info1 and info2. By convention, the two matrices
    // in each info object refer to the test functions on the respective cell.
    // The first matrix contains the interior couplings of that cell, while the
    // second contains the couplings between cells.
    FullMatrix<double> &u1_v1_matrix = dinfo1.matrix(0, false).matrix;
    FullMatrix<double> &u2_v1_matrix = dinfo1.matrix(0, true).matrix;
    FullMatrix<double> &u1_v2_matrix = dinfo2.matrix(0, true).matrix;
    FullMatrix<double> &u2_v2_matrix = dinfo2.matrix(0, false).matrix;

    // Here, following the previous functions, we would have the local right
    // hand side vectors. Fortunately, the interface terms only involve the
    // solution and the right hand side does not receive any contributions.

    const std::vector<double> &        JxW = fe_face_values.get_JxW_values();
    const std::vector<Tensor<1, dim>> &normals =
      fe_face_values.get_normal_vectors();

    for (unsigned int point = 0; point < fe_face_values.n_quadrature_points;
         ++point)
      {
        const double beta_dot_n =
          beta(fe_face_values.quadrature_point(point)) * normals[point];
        if (beta_dot_n > 0)
          {
            // This term we've already seen:
            for (unsigned int i = 0; i < dofs_per_cell; ++i)
              for (unsigned int j = 0; j < dofs_per_cell; ++j)
                u1_v1_matrix(i, j) += beta_dot_n *                           //
                                      fe_face_values.shape_value(j, point) * //
                                      fe_face_values.shape_value(i, point) * //
                                      JxW[point];

            // We additionally assemble the term $(\beta\cdot n u,\hat
            // v)_{\partial \kappa_+}$,
            for (unsigned int k = 0; k < neighbor_dofs_per_cell; ++k)
              for (unsigned int j = 0; j < dofs_per_cell; ++j)
                u1_v2_matrix(k, j) +=
                  -beta_dot_n *                                   //
                  fe_face_values.shape_value(j, point) *          //
                  fe_face_values_neighbor.shape_value(k, point) * //
                  JxW[point];
          }
        else
          {
            // This one we've already seen, too:
            for (unsigned int i = 0; i < dofs_per_cell; ++i)
              for (unsigned int l = 0; l < neighbor_dofs_per_cell; ++l)
                u2_v1_matrix(i, l) +=
                  beta_dot_n *                                    //
                  fe_face_values_neighbor.shape_value(l, point) * //
                  fe_face_values.shape_value(i, point) *          //
                  JxW[point];

            // And this is another new one: $(\beta\cdot n \hat u,\hat
            // v)_{\partial \kappa_-}$:
            for (unsigned int k = 0; k < neighbor_dofs_per_cell; ++k)
              for (unsigned int l = 0; l < neighbor_dofs_per_cell; ++l)
                u2_v2_matrix(k, l) +=
                  -beta_dot_n *                                   //
                  fe_face_values_neighbor.shape_value(l, point) * //
                  fe_face_values_neighbor.shape_value(k, point) * //
                  JxW[point];
          }
      }
  }


  // @sect3{All the rest}
  //
  // For this simple problem we use the simplest possible solver, called
  // Richardson iteration, that represents a simple defect correction. This, in
  // combination with a block SSOR preconditioner, that uses the special block
  // matrix structure of system matrices arising from DG discretizations. The
  // size of these blocks are the number of DoFs per cell. Here, we use a SSOR
  // preconditioning as we have not renumbered the DoFs according to the flow
  // field. If the DoFs are renumbered in the downstream direction of the flow,
  // then a block Gauss-Seidel preconditioner (see the PreconditionBlockSOR
  // class with relaxation=1) does a much better job.
  template <int dim>
  void AdvectionProblem<dim>::solve(Vector<double> &solution)
  {
    SolverControl                    solver_control(1000, 1e-12);
    SolverRichardson<Vector<double>> solver(solver_control);

    // Here we create the preconditioner,
    PreconditionBlockSSOR<SparseMatrix<double>> preconditioner;

    // then assign the matrix to it and set the right block size:
    preconditioner.initialize(system_matrix, fe.n_dofs_per_cell());

    // After these preparations we are ready to start the linear solver.
    solver.solve(system_matrix, solution, right_hand_side, preconditioner);
  }


  // We refine the grid according to a very simple refinement criterion, namely
  // an approximation to the gradient of the solution. As here we consider the
  // DG(1) method (i.e. we use piecewise bilinear shape functions) we could
  // simply compute the gradients on each cell. But we do not want to base our
  // refinement indicator on the gradients on each cell only, but want to base
  // them also on jumps of the discontinuous solution function over faces
  // between neighboring cells. The simplest way of doing that is to compute
  // approximative gradients by difference quotients including the cell under
  // consideration and its neighbors. This is done by the
  // <code>DerivativeApproximation</code> class that computes the approximate
  // gradients in a way similar to the <code>GradientEstimation</code> described
  // in step-9 of this tutorial. In fact, the
  // <code>DerivativeApproximation</code> class was developed following the
  // <code>GradientEstimation</code> class of step-9. Relating to the discussion
  // in step-9, here we consider $h^{1+d/2}|\nabla_h u_h|$. Furthermore we note
  // that we do not consider approximate second derivatives because solutions to
  // the linear advection equation are in general not in $H^2$ but only in $H^1$
  // (or, to be more precise: in $H^1_\beta$, i.e., the space of functions whose
  // derivatives in direction $\beta$ are square integrable).
  template <int dim>
  void AdvectionProblem<dim>::refine_grid()
  {
    // The <code>DerivativeApproximation</code> class computes the gradients to
    // float precision. This is sufficient as they are approximate and serve as
    // refinement indicators only.
    Vector<float> gradient_indicator(triangulation.n_active_cells());

    // Now the approximate gradients are computed
    DerivativeApproximation::approximate_gradient(mapping,
                                                  dof_handler,
                                                  solution,
                                                  gradient_indicator);

    // and they are cell-wise scaled by the factor $h^{1+d/2}$
    unsigned int cell_no = 0;
    for (const auto &cell : dof_handler.active_cell_iterators())
      gradient_indicator(cell_no++) *=
        std::pow(cell->diameter(), 1 + 1.0 * dim / 2);

    // Finally they serve as refinement indicator.
    GridRefinement::refine_and_coarsen_fixed_number(triangulation,
                                                    gradient_indicator,
                                                    0.3,
                                                    0.1);

    triangulation.execute_coarsening_and_refinement();
  }


  // The output of this program consists of eps-files of the adaptively refined
  // grids and the numerical solutions given in gnuplot format.
  template <int dim>
  void AdvectionProblem<dim>::output_results(const unsigned int cycle) const
  {
    // First write the grid in eps format.
    {
      const std::string filename = "grid-" + std::to_string(cycle) + ".eps";
      deallog << "Writing grid to <" << filename << '>' << std::endl;
      std::ofstream eps_output(filename);

      GridOut grid_out;
      grid_out.write_eps(triangulation, eps_output);
    }

    // Then output the solution in gnuplot format.
    {
      const std::string filename = "sol-" + std::to_string(cycle) + ".gnuplot";
      deallog << "Writing solution to <" << filename << '>' << std::endl;
      std::ofstream gnuplot_output(filename);

      DataOut<dim> data_out;
      data_out.attach_dof_handler(dof_handler);
      data_out.add_data_vector(solution, "u");

      data_out.build_patches();

      data_out.write_gnuplot(gnuplot_output);
    }
  }


  // The following <code>run</code> function is similar to previous examples.
  template <int dim>
  void AdvectionProblem<dim>::run()
  {
    for (unsigned int cycle = 0; cycle < 6; ++cycle)
      {
        deallog << "Cycle " << cycle << std::endl;

        if (cycle == 0)
          {
            GridGenerator::hyper_cube(triangulation);

            triangulation.refine_global(3);
          }
        else
          refine_grid();


        deallog << "Number of active cells:       "
                << triangulation.n_active_cells() << std::endl;

        setup_system();

        deallog << "Number of degrees of freedom: " << dof_handler.n_dofs()
                << std::endl;

        assemble_system();
        solve(solution);

        output_results(cycle);
      }
  }
} // namespace Step12


// The following <code>main</code> function is similar to previous examples as
// well, and need not be commented on.
int main()
{
  try
    {
      dealii::deallog.depth_console(5);

      Step12::AdvectionProblem<2> dgmethod;
      dgmethod.run();
    }
  catch (std::exception &exc)
    {
      std::cerr << std::endl
                << std::endl
                << "----------------------------------------------------"
                << std::endl;
      std::cerr << "Exception on processing: " << std::endl
                << exc.what() << std::endl
                << "Aborting!" << std::endl
                << "----------------------------------------------------"
                << std::endl;
      return 1;
    }
  catch (...)
    {
      std::cerr << std::endl
                << std::endl
                << "----------------------------------------------------"
                << std::endl;
      std::cerr << "Unknown exception!" << std::endl
                << "Aborting!" << std::endl
                << "----------------------------------------------------"
                << std::endl;
      return 1;
    }

  return 0;
}
