示例#1
0
int main() {
    // Time measurement.
    TimePeriod cpu_time;
    cpu_time.tick();

    // Create coarse mesh, set Dirichlet BC, enumerate basis functions.
    Space* space = new Space(A, B, NELEM, DIR_BC_LEFT, DIR_BC_RIGHT, P_INIT, NEQ, NEQ);

    // Enumerate basis functions, info for user.
    int ndof = Space::get_num_dofs(space);
    info("ndof: %d", ndof);

    // Initialize the weak formulation.
    WeakForm wf;
    wf.add_matrix_form(jacobian);
    wf.add_vector_form(residual);

    // Initialize the FE problem.
    bool is_linear = false;
    DiscreteProblem *dp_coarse = new DiscreteProblem(&wf, space, is_linear);

    // Newton's loop on coarse mesh.
    // Fill vector coeff_vec using dof and coeffs arrays in elements.
    double *coeff_vec_coarse = new double[Space::get_num_dofs(space)];
    get_coeff_vector(space, coeff_vec_coarse);

    // Set up the solver, matrix, and rhs according to the solver selection.
    SparseMatrix* matrix_coarse = create_matrix(matrix_solver);
    Vector* rhs_coarse = create_vector(matrix_solver);
    Solver* solver_coarse = create_linear_solver(matrix_solver, matrix_coarse, rhs_coarse);

    int it = 1;
    while (1)
    {
        // Obtain the number of degrees of freedom.
        int ndof_coarse = Space::get_num_dofs(space);

        // Assemble the Jacobian matrix and residual vector.
        dp_coarse->assemble(coeff_vec_coarse, matrix_coarse, rhs_coarse);

        // Calculate the l2-norm of residual vector.
        double res_l2_norm = get_l2_norm(rhs_coarse);

        // Info for user.
        info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(space), res_l2_norm);

        // If l2 norm of the residual vector is within tolerance, then quit.
        // NOTE: at least one full iteration forced
        //       here because sometimes the initial
        //       residual on fine mesh is too small.
        if(res_l2_norm < NEWTON_TOL_COARSE && it > 1) break;

        // Multiply the residual vector with -1 since the matrix
        // equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
        for(int i=0; i<ndof_coarse; i++) rhs_coarse->set(i, -rhs_coarse->get(i));

        // Solve the linear system.
        if(!solver_coarse->solve())
            error ("Matrix solver failed.\n");

        // Add \deltaY^{n+1} to Y^n.
        for (int i = 0; i < ndof_coarse; i++) coeff_vec_coarse[i] += solver_coarse->get_solution()[i];

        // If the maximum number of iteration has been reached, then quit.
        if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");

        // Copy coefficients from vector y to elements.
        set_coeff_vector(coeff_vec_coarse, space);

        it++;
    }

    // Cleanup.
    delete matrix_coarse;
    delete rhs_coarse;
    delete solver_coarse;
    delete [] coeff_vec_coarse;
    delete dp_coarse;

    // DOF and CPU convergence graphs.
    SimpleGraph graph_dof_est, graph_cpu_est;
    SimpleGraph graph_dof_exact, graph_cpu_exact;

    // Test variable.
    int success_test = 1;

    // Adaptivity loop:
    int as = 1;
    bool done = false;
    do
    {
        info("---- Adaptivity step %d:", as);

        // Construct globally refined reference mesh and setup reference space.
        Space* ref_space = construct_refined_space(space);

        // Initialize the FE problem.
        bool is_linear = false;
        DiscreteProblem* dp = new DiscreteProblem(&wf, ref_space, is_linear);

        // Set up the solver, matrix, and rhs according to the solver selection.
        SparseMatrix* matrix = create_matrix(matrix_solver);
        Vector* rhs = create_vector(matrix_solver);
        Solver* solver = create_linear_solver(matrix_solver, matrix, rhs);

        // Newton's loop on the fine mesh.
        info("Solving on fine mesh:");
        // Fill vector coeff_vec using dof and coeffs arrays in elements.
        double *coeff_vec = new double[Space::get_num_dofs(ref_space)];
        get_coeff_vector(ref_space, coeff_vec);

        int it = 1;
        while (1)
        {
            // Obtain the number of degrees of freedom.
            int ndof = Space::get_num_dofs(ref_space);

            // Assemble the Jacobian matrix and residual vector.
            dp->assemble(coeff_vec, matrix, rhs);

            // Calculate the l2-norm of residual vector.
            double res_l2_norm = get_l2_norm(rhs);

            // Info for user.
            info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(ref_space), res_l2_norm);

            // If l2 norm of the residual vector is within tolerance, then quit.
            // NOTE: at least one full iteration forced
            //       here because sometimes the initial
            //       residual on fine mesh is too small.
            if(res_l2_norm < NEWTON_TOL_REF && it > 1) break;

            // Multiply the residual vector with -1 since the matrix
            // equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
            for(int i=0; i<ndof; i++) rhs->set(i, -rhs->get(i));

            // Solve the linear system.
            if(!solver->solve())
                error ("Matrix solver failed.\n");

            // Add \deltaY^{n+1} to Y^n.
            for (int i = 0; i < ndof; i++) coeff_vec[i] += solver->get_solution()[i];

            // If the maximum number of iteration has been reached, then quit.
            if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");

            // Copy coefficients from vector y to elements.
            set_coeff_vector(coeff_vec, ref_space);

            it++;
        }

        // Starting with second adaptivity step, obtain new coarse
        // mesh solution via projecting the fine mesh solution.
        if(as > 1)
        {
            info("Projecting the fine mesh solution onto the coarse mesh.");
            // Project the fine mesh solution (defined on space_ref) onto the coarse mesh (defined on space).
            OGProjection::project_global(space, ref_space, matrix_solver);
        }

        // Calculate element errors and total error estimate.
        info("Calculating error estimate.");
        double err_est_array[MAX_ELEM_NUM];
        double err_est_rel = calc_err_est(NORM, space, ref_space, err_est_array) * 100;

        // Report results.
        info("ndof_coarse: %d, ndof_fine: %d, err_est_rel: %g%%",
             Space::get_num_dofs(space), Space::get_num_dofs(ref_space), err_est_rel);

        // Time measurement.
        cpu_time.tick();

        // If exact solution available, also calculate exact error.
        if (EXACT_SOL_PROVIDED)
        {
            // Calculate element errors wrt. exact solution.
            double err_exact_rel = calc_err_exact(NORM, space, exact_sol, NEQ, A, B) * 100;

            // Info for user.
            info("Relative error (exact) = %g %%", err_exact_rel);

            // Add entry to DOF and CPU convergence graphs.
            graph_dof_exact.add_values(Space::get_num_dofs(space), err_exact_rel);
            graph_cpu_exact.add_values(cpu_time.accumulated(), err_exact_rel);
            if (as == 2)
                if (err_exact_rel > 1e-10) success_test = 0;
        }

        // Add entry to DOF and CPU convergence graphs.
        graph_dof_est.add_values(Space::get_num_dofs(space), err_est_rel);
        graph_cpu_est.add_values(cpu_time.accumulated(), err_est_rel);

        // Decide whether the relative error is sufficiently small.
        if(err_est_rel < TOL_ERR_REL) done = true;

        // Extra code for this test.
        if (as == 30)
        {
            if (err_est_rel > 1e-10) success_test = 0;
            if (space->get_n_active_elem() != 2) success_test = 0;
            Element *e = space->first_active_element();
            if (e->p != 2) success_test = 0;
            e = space->last_active_element();
            if (e->p != 2) success_test = 0;
            break;
        }

        // Returns updated coarse and fine meshes, with the last
        // coarse and fine mesh solutions on them, respectively.
        // The coefficient vectors and numbers of degrees of freedom
        // on both meshes are also updated.
        adapt(NORM, ADAPT_TYPE, THRESHOLD, err_est_array, space, ref_space);

        as++;

        // Plot meshes, results, and errors.
        adapt_plotting(space, ref_space, NORM, EXACT_SOL_PROVIDED, exact_sol);

        // Cleanup.
        delete solver;
        delete matrix;
        delete rhs;
        delete ref_space;
        delete dp;
        delete [] coeff_vec;

    }
    while (done == false);

    info("Total running time: %g s", cpu_time.accumulated());

    // Save convergence graphs.
    graph_dof_est.save("conv_dof_est.dat");
    graph_cpu_est.save("conv_cpu_est.dat");
    graph_dof_exact.save("conv_dof_exact.dat");
    graph_cpu_exact.save("conv_cpu_exact.dat");

    if (success_test)
    {
        info("Success!");
        return ERROR_SUCCESS;
    }
    else
    {
        info("Failure!");
        return ERROR_FAILURE;
    }
}
示例#2
0
文件: main.cpp 项目: alieed/hermes
int main() 
{
  // Time measurement.
  TimePeriod cpu_time;
  cpu_time.tick();

  // Create coarse mesh, set Dirichlet BC, enumerate basis functions.
  Space* space = new Space(A, B, NELEM, DIR_BC_LEFT, DIR_BC_RIGHT, P_INIT, NEQ);

  // Enumerate basis functions, info for user.
  int ndof = Space::get_num_dofs(space);
  info("ndof: %d", ndof);

  // Initialize the weak formulation.
  WeakForm wf;
  wf.add_matrix_form(jacobian);
  wf.add_vector_form(residual);

  double elem_errors[MAX_ELEM_NUM];      // This array decides what 
                                         // elements will be refined.
  ElemPtr2 ref_elem_pairs[MAX_ELEM_NUM]; // To store element pairs from the 
                                         // FTR solution. Decides how 
                                         // elements will be hp-refined. 
  for (int i=0; i < MAX_ELEM_NUM; i++) 
  {
    ref_elem_pairs[i][0] = new Element();
    ref_elem_pairs[i][1] = new Element();
  }

  // DOF and CPU convergence graphs.
  SimpleGraph graph_dof_exact, graph_cpu_exact;

  /// Adaptivity loop:
  int as = 1;
  bool done = false;
  do
  {
    info("---- Adaptivity step %d:", as); 

    // Initialize the FE problem.
    bool is_linear = false;
    DiscreteProblem *dp_coarse = new DiscreteProblem(&wf, space, is_linear);
    
    // Newton's loop on coarse mesh.
    // Fill vector coeff_vec using dof and coeffs arrays in elements.
    double *coeff_vec_coarse = new double[Space::get_num_dofs(space)];
    get_coeff_vector(space, coeff_vec_coarse);

    // Set up the solver, matrix, and rhs according to the solver selection.
    SparseMatrix* matrix_coarse = create_matrix(matrix_solver);
    Vector* rhs_coarse = create_vector(matrix_solver);
    Solver* solver_coarse = create_linear_solver(matrix_solver, matrix_coarse, rhs_coarse);

    int it = 1;
    while (1) 
    {
      // Obtain the number of degrees of freedom.
      int ndof_coarse = Space::get_num_dofs(space);

      // Assemble the Jacobian matrix and residual vector.
      dp_coarse->assemble(coeff_vec_coarse, matrix_coarse, rhs_coarse);

      // Calculate the l2-norm of residual vector.
      double res_l2_norm = get_l2_norm(rhs_coarse);

      // Info for user.
      info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(space), res_l2_norm);

      // If l2 norm of the residual vector is within tolerance, then quit.
      // NOTE: at least one full iteration forced
      //       here because sometimes the initial
      //       residual on fine mesh is too small.
      if(res_l2_norm < NEWTON_TOL_COARSE && it > 1) break;

      // Multiply the residual vector with -1 since the matrix 
      // equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
      for(int i=0; i<ndof_coarse; i++) rhs_coarse->set(i, -rhs_coarse->get(i));
 
      // Solve the linear system.
      if(!solver_coarse->solve())
      error ("Matrix solver failed.\n");

      // Add \deltaY^{n+1} to Y^n.
      for (int i = 0; i < ndof_coarse; i++) coeff_vec_coarse[i] += solver_coarse->get_solution()[i];

      // If the maximum number of iteration has been reached, then quit.
      if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
      
      // Copy coefficients from vector y to elements.
      set_coeff_vector(coeff_vec_coarse, space);
      
      it++;
    }
    
    // Cleanup.
    delete matrix_coarse;
    delete rhs_coarse;
    delete solver_coarse;
    delete [] coeff_vec_coarse;
    delete dp_coarse;

    // For every element perform its fast trial refinement (FTR),
    // calculate the norm of the difference between the FTR
    // solution and the coarse space solution, and store the
    // error in the elem_errors[] array.
    int n_elem = space->get_n_active_elem();
    for (int i=0; i < n_elem; i++) 
    {

      info("=== Starting FTR of Elem [%d].", i);

      // Replicate coarse space including solution.
      Space *space_ref_local = space->replicate();

      // Perform FTR of element 'i'
      space_ref_local->reference_refinement(i, 1);
      info("Elem [%d]: fine space created (%d DOF).", 
             i, space_ref_local->assign_dofs());

      // Initialize the FE problem. 
      bool is_linear = false;
      DiscreteProblem* dp = new DiscreteProblem(&wf, space_ref_local, is_linear);

      // Set up the solver, matrix, and rhs according to the solver selection.
      SparseMatrix* matrix = create_matrix(matrix_solver);
      Vector* rhs = create_vector(matrix_solver);
      Solver* solver = create_linear_solver(matrix_solver, matrix, rhs);

      // Newton's loop on the FTR space.
      // Fill vector coeff_vec using dof and coeffs arrays in elements.
      double *coeff_vec = new double[Space::get_num_dofs(space_ref_local)];
      get_coeff_vector(space_ref_local, coeff_vec);
      memset(coeff_vec, 0, Space::get_num_dofs(space_ref_local)*sizeof(double));

      int it = 1;
      while (1) 
      {
        // Obtain the number of degrees of freedom.
        int ndof = Space::get_num_dofs(space_ref_local);

        // Assemble the Jacobian matrix and residual vector.
        dp->assemble(coeff_vec, matrix, rhs);

        // Calculate the l2-norm of residual vector.
        double res_l2_norm = get_l2_norm(rhs);

        // Info for user.
        info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(space_ref_local), res_l2_norm);

        // If l2 norm of the residual vector is within tolerance, then quit.
        // NOTE: at least one full iteration forced
        //       here because sometimes the initial
        //       residual on fine mesh is too small.
        if(res_l2_norm < NEWTON_TOL_REF && it > 1) break;

        // Multiply the residual vector with -1 since the matrix 
        // equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
        for(int i=0; i<ndof; i++) rhs->set(i, -rhs->get(i));

        // Solve the linear system.
        if(!solver->solve())
        error ("Matrix solver failed.\n");

        // Add \deltaY^{n+1} to Y^n.
        for (int i = 0; i < ndof; i++) coeff_vec[i] += solver->get_solution()[i];

        // If the maximum number of iteration has been reached, then quit.
        if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
        
        // Copy coefficients from vector y to elements.
        set_coeff_vector(coeff_vec, space_ref_local);

        it++;
      }
      
      // Cleanup.
      delete matrix;
      delete rhs;
      delete solver;
      delete dp;
      delete [] coeff_vec;

      // Print FTR solution (enumerated). 
      //Linearizer *lxx = new Linearizer(space_ref_local);
      //char out_filename[255];
      //sprintf(out_filename, "solution_ref_%d.gp", i);
      //lxx->plot_solution(out_filename);
      //delete lxx;

      // Calculate norm of the difference between the coarse space 
      // and FTR solutions.
      // NOTE: later we want to look at the difference in some quantity 
      // of interest rather than error in global norm.
      double err_est_array[MAX_ELEM_NUM];
      elem_errors[i] = calc_err_est(NORM, space, space_ref_local, err_est_array) * 100;
      info("Elem [%d]: absolute error (est) = %g%%", i, elem_errors[i]);

      // Copy the reference element pair for element 'i'.
      // into the ref_elem_pairs[i][] array
      Iterator *I = new Iterator(space);
      Iterator *I_ref = new Iterator(space_ref_local);
      Element *e, *e_ref;
      while (1) 
      {
        e = I->next_active_element();
        e_ref = I_ref->next_active_element();
        if (e->id == i) 
        {
  	  e_ref->copy_into(ref_elem_pairs[e->id][0]);
          // coarse element 'e' was split in space.
          if (e->level != e_ref->level) 
          {
            e_ref = I_ref->next_active_element();
            e_ref->copy_into(ref_elem_pairs[e->id][1]);
          }
          break;
        }
      }

      delete I;
      delete I_ref;
      delete space_ref_local;
    }  

    // Time measurement.
    cpu_time.tick();

    // If exact solution available, also calculate exact error.
    if (EXACT_SOL_PROVIDED) 
    {
      // Calculate element errors wrt. exact solution.
      double err_exact_rel = calc_err_exact(NORM, space, exact_sol, NEQ, A, B) * 100;
     
      // Info for user.
      info("Relative error (exact) = %g %%", err_exact_rel);
     
      // Add entry to DOF and CPU convergence graphs.
      graph_dof_exact.add_values(Space::get_num_dofs(space), err_exact_rel);
      graph_cpu_exact.add_values(cpu_time.accumulated(), err_exact_rel);
    }

    // Calculate max FTR error.
    double max_ftr_error = 0;
    for (int i=0; i < space->get_n_active_elem(); i++) 
    {
      if (elem_errors[i] > max_ftr_error) max_ftr_error = elem_errors[i];
    }
    info("Max FTR error = %g%%.", max_ftr_error);

    // Decide whether the max. FTR error is sufficiently small.
    if(max_ftr_error < TOL_ERR_FTR) break;

    // debug
    //if (as >= 1) break;

    // Returns updated coarse space with the last solution on it. 
    adapt(NORM, ADAPT_TYPE, THRESHOLD, elem_errors, space, ref_elem_pairs);

    // Plot spaces, results, and errors.
    //adapt_plotting(space, ref_elem_pairs, NORM, EXACT_SOL_PROVIDED, exact_sol);

    as++;
  }
  while (done == false);

  info("Total running time: %g s", cpu_time.accumulated());

  // Save convergence graphs.
  graph_dof_exact.save("conv_dof_exact.dat");
  graph_cpu_exact.save("conv_cpu_exact.dat");

  // Test variable.
  bool success = true;
  info("ndof = %d.", Space::get_num_dofs(space));
  if (Space::get_num_dofs(space) > 35) success = false;

  if (success)
  {
    info("Success!");
    return ERROR_SUCCESS;
  }
  else
  {
    info("Failure!");
    return ERROR_FAILURE;
  }
}
示例#3
0
文件: main.cpp 项目: alieed/hermes
int main() 
{
  // Time measurement.
  TimePeriod cpu_time;
  cpu_time.tick();

  // Create coarse mesh, set Dirichlet BC, enumerate basis functions.
  Space* space = new Space(A, B, NELEM, DIR_BC_LEFT, DIR_BC_RIGHT, P_INIT, NEQ);

  // Enumerate basis functions, info for user.
  int ndof = Space::get_num_dofs(space);
  info("ndof: %d", ndof);

  // Initialize the weak formulation.
  WeakForm wf;
  wf.add_matrix_form(jacobian);
  wf.add_vector_form(residual);

  // Initialize the FE problem.
  bool is_linear = false;
  DiscreteProblem *dp_coarse = new DiscreteProblem(&wf, space, is_linear);
  if(JFNK == 0)
  {
    // Newton's loop on coarse mesh.
    // Fill vector coeff_vec using dof and coeffs arrays in elements.
    double *coeff_vec_coarse = new double[Space::get_num_dofs(space)];
    get_coeff_vector(space, coeff_vec_coarse);

    // Set up the solver, matrix, and rhs according to the solver selection.
    SparseMatrix* matrix_coarse = create_matrix(matrix_solver);
    Vector* rhs_coarse = create_vector(matrix_solver);
    Solver* solver_coarse = create_linear_solver(matrix_solver, matrix_coarse, rhs_coarse);

    int it = 1;
    while (1) 
    {
      // Obtain the number of degrees of freedom.
      int ndof_coarse = Space::get_num_dofs(space);

      // Assemble the Jacobian matrix and residual vector.
      dp_coarse->assemble(coeff_vec_coarse, matrix_coarse, rhs_coarse);

      // Calculate the l2-norm of residual vector.
      double res_l2_norm = get_l2_norm(rhs_coarse);

      // Info for user.
      info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(space), res_l2_norm);

      // If l2 norm of the residual vector is within tolerance, then quit.
      // NOTE: at least one full iteration forced
      //       here because sometimes the initial
      //       residual on fine mesh is too small.
      if(res_l2_norm < NEWTON_TOL_COARSE && it > 1) break;

      // Multiply the residual vector with -1 since the matrix 
      // equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n).
      for(int i = 0; i < ndof_coarse; i++) rhs_coarse->set(i, -rhs_coarse->get(i));

      // Solve the linear system.
      if(!solver_coarse->solve())
        error ("Matrix solver failed.\n");

      // Add \deltaY^{n+1} to Y^n.
      for (int i = 0; i < ndof_coarse; i++) coeff_vec_coarse[i] += solver_coarse->get_solution()[i];

      // If the maximum number of iteration has been reached, then quit.
      if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
      
      // Copy coefficients from vector y to elements.
      set_coeff_vector(coeff_vec_coarse, space);
      
      it++;
    }
    
    // Cleanup.
    delete matrix_coarse;
    delete rhs_coarse;
    delete solver_coarse;
    delete [] coeff_vec_coarse;
  }
  else
    jfnk_cg(dp_coarse, space, MATRIX_SOLVER_TOL, MATRIX_SOLVER_MAXITER,
            JFNK_EPSILON, NEWTON_TOL_COARSE, NEWTON_MAX_ITER, matrix_solver);

  // Cleanup.
  delete dp_coarse;

  // DOF and CPU convergence graphs.
  SimpleGraph graph_dof_est, graph_cpu_est;
  SimpleGraph graph_dof_exact, graph_cpu_exact;

  // Adaptivity loop:
  int as = 1;
  double ftr_errors[MAX_ELEM_NUM];        // This array decides what 
                                          // elements will be refined.

  bool done = false;
  do
  {
    info("---- Adaptivity step %d:", as); 

    // Construct globally refined reference mesh and setup reference space.
    Space* ref_space = construct_refined_space(space);
 
    // Initialize the FE problem. 
    bool is_linear = false;
    DiscreteProblem* dp = new DiscreteProblem(&wf, ref_space, is_linear);
      
    if(JFNK == 0)
    {
      // Set up the solver, matrix, and rhs according to the solver selection.
      SparseMatrix* matrix = create_matrix(matrix_solver);
      Vector* rhs = create_vector(matrix_solver);
      Solver* solver = create_linear_solver(matrix_solver, matrix, rhs);
      
      // Newton's loop on the fine mesh.
      info("Solving on fine mesh:");
      // Fill vector coeff_vec using dof and coeffs arrays in elements.
      double *coeff_vec = new double[Space::get_num_dofs(ref_space)];
      get_coeff_vector(ref_space, coeff_vec);

        int it = 1;
        while (1) 
        {
          // Obtain the number of degrees of freedom.
          int ndof = Space::get_num_dofs(ref_space);

          // Assemble the Jacobian matrix and residual vector.
          dp->assemble(coeff_vec, matrix, rhs);

          // Calculate the l2-norm of residual vector.
          double res_l2_norm = get_l2_norm(rhs);

          // Info for user.
          info("---- Newton iter %d, ndof %d, res. l2 norm %g", it, Space::get_num_dofs(ref_space), res_l2_norm);

          // If l2 norm of the residual vector is within tolerance, then quit.
          // NOTE: at least one full iteration forced
          //       here because sometimes the initial
          //       residual on fine mesh is too small.
          if(res_l2_norm < NEWTON_TOL_REF && it > 1) break;

          // Multiply the residual vector with -1 since the matrix 
          // equation reads J(Y^n) \deltaY^{n+1} = -F(Y^n). 
          for(int i = 0; i < ndof; i++) rhs->set(i, -rhs->get(i));

          // Solve the linear system.
          if(!solver->solve())
            error ("Matrix solver failed.\n");

          // Add \deltaY^{n+1} to Y^n.
          for (int i = 0; i < ndof; i++) coeff_vec[i] += solver->get_solution()[i];

          // If the maximum number of iteration has been reached, then quit.
          if (it >= NEWTON_MAX_ITER) error ("Newton method did not converge.");
        
          // Copy coefficients from vector y to elements.
          set_coeff_vector(coeff_vec, ref_space);

          it++;
      }
      // Cleanup.
      delete matrix;
      delete rhs;
      delete solver;
      delete [] coeff_vec;
    }
    else
      jfnk_cg(dp, ref_space, MATRIX_SOLVER_TOL, MATRIX_SOLVER_MAXITER,
              JFNK_EPSILON, NEWTON_TOL_COARSE, NEWTON_MAX_ITER, matrix_solver);
 
    // Cleanup.
    delete dp;
    
    // Starting with second adaptivity step, obtain new coarse 
    // mesh solution via projecting the fine mesh solution.
    if(as > 1)
    {
      info("Projecting the fine mesh solution onto the coarse mesh.");
      // Project the fine mesh solution (defined on space_ref) onto the coarse mesh (defined on space).
      OGProjection::project_global(space, ref_space, matrix_solver);
    }

    double max_qoi_err_est = 0;
    for (int i=0; i < space->get_n_active_elem(); i++)
    {
      if (GOAL_ORIENTED == 1) 
      {
        // Use quantity of interest.
        double qoi_est = quantity_of_interest(space, X_QOI);
        double qoi_ref_est = quantity_of_interest(ref_space, X_QOI);
        ftr_errors[i] = fabs(qoi_ref_est - qoi_est);
      }
      else 
      {
        // Use global norm
        double err_est_array[MAX_ELEM_NUM];
        ftr_errors[i] = calc_err_est(NORM, space, ref_space, err_est_array);
      }
      // Info for user.
      info("Elem [%d]: absolute error (est) = %g%%", i, ftr_errors[i]);

      // Time measurement.
      cpu_time.tick();

      // Calculating maximum of QOI FTR error for plotting purposes
      if (GOAL_ORIENTED == 1) 
      {
        if (ftr_errors[i] > max_qoi_err_est)
          max_qoi_err_est = ftr_errors[i];
      }
      else 
      {
        double qoi_est = quantity_of_interest(space, X_QOI);
        double qoi_ref_est = quantity_of_interest(ref_space, X_QOI);
        double err_est = fabs(qoi_ref_est - qoi_est);
        if (err_est > max_qoi_err_est)
          max_qoi_err_est = err_est;
      }
    }

    // Add entries to convergence graphs.
    if (EXACT_SOL_PROVIDED) 
    {
      double qoi_est = quantity_of_interest(space, X_QOI);
      double u[MAX_EQN_NUM], dudx[MAX_EQN_NUM];
      exact_sol(X_QOI, u, dudx);
      double err_qoi_exact = fabs(u[0] - qoi_est);
      // Info for user.
      info("Relative error (exact) = %g %%", err_qoi_exact);
      // Add entry to DOF and CPU convergence graphs.
      graph_dof_exact.add_values(Space::get_num_dofs(space), err_qoi_exact);
      graph_cpu_exact.add_values(cpu_time.accumulated(), err_qoi_exact);
    }
    
    // Add entry to DOF and CPU convergence graphs.
    graph_dof_est.add_values(Space::get_num_dofs(space), max_qoi_err_est);
    graph_cpu_est.add_values(cpu_time.accumulated(), max_qoi_err_est);

    // Decide whether the max. FTR error in the quantity of interest 
    // is sufficiently small.
    if(max_qoi_err_est < TOL_ERR_QOI) break;

    // Returns updated coarse and fine meshes, with the last 
    // coarse and fine mesh solutions on them, respectively. 
    // The coefficient vectors and numbers of degrees of freedom 
    // on both meshes are also updated. 
    adapt(NORM, ADAPT_TYPE, THRESHOLD, ftr_errors, space, ref_space);

    as++;

    // Plot meshes, results, and errors.
    adapt_plotting(space, ref_space, NORM, EXACT_SOL_PROVIDED, exact_sol);

    // Cleanup.
    delete ref_space;
  }
  while (done == false);

  info("Total running time: %g s", cpu_time.accumulated());

  // Save convergence graphs.
  graph_dof_est.save("conv_dof_est.dat");
  graph_cpu_est.save("conv_cpu_est.dat");
  graph_dof_exact.save("conv_dof_exact.dat");
  graph_cpu_exact.save("conv_cpu_exact.dat");

  // Test variable.
  bool success = true;
  info("ndof = %d.", Space::get_num_dofs(space));
  if (Space::get_num_dofs(space) > 150) success = false;

  if (success)
  {
    info("Success!");
    return ERROR_SUCCESS;
  }
  else
  {
    info("Failure!");
    return ERROR_FAILURE;
  }
}