int main(int argc, char **args)
{
// Time measurement.
TimePeriod cpu_time;
cpu_time.tick();
// Load the mesh.
Mesh mesh;
ExodusIIReader mloader;
mloader.load("maxwell.mesh", &mesh);
// Perform initial mesh refinement.
for (int i=0; i < INIT_REF_NUM; i++) mesh.refine_all_elements(H3D_H3D_H3D_REFT_HEX_XYZ);
// Create an Hcurl space with default shapeset.
HcurlSpace space(&mesh, bc_types, essential_bc_values, Ord3(P_INIT_X, P_INIT_Y, P_INIT_Z));
// Initialize weak formulation.
WeakForm wf;
wf.add_matrix_form(biform<double, scalar>, biform<Ord, Ord>, HERMES_SYM);
wf.add_vector_form(liform<double, scalar>, liform<Ord, Ord>);
// DOF and CPU convergence graphs.
SimpleGraph graph_dof_est, graph_cpu_est;
// 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, 1);
// Initialize discrete problem.
bool is_linear = true;
DiscreteProblem dp(&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);
// Initialize the preconditioner in the case of SOLVER_AZTECOO.
if (matrix_solver == SOLVER_AZTECOO)
{
((AztecOOSolver*) solver)->set_solver(iterative_method);
((AztecOOSolver*) solver)->set_precond(preconditioner);
// Using default iteration parameters (see solver/aztecoo.h).
}
// Assemble the reference problem.
info("Assembling on reference mesh (ndof: %d).", Space::get_num_dofs(ref_space));
dp.assemble(matrix, rhs);
// Time measurement.
cpu_time.tick();
// Solve the linear system on reference mesh. If successful, obtain the solution.
info("Solving on reference mesh.");
Solution ref_sln(ref_space->get_mesh());
if(solver->solve()) Solution::vector_to_solution(solver->get_solution(), ref_space, &ref_sln);
else error ("Matrix solver failed.\n");
// Time measurement.
cpu_time.tick();
// Project the reference solution on the coarse mesh.
Solution sln(space.get_mesh());
info("Projecting reference solution on coarse mesh.");
OGProjection::project_global(&space, &ref_sln, &sln, matrix_solver, HERMES_HCURL_NORM);
// Time measurement.
cpu_time.tick();
// Output solution and mesh with polynomial orders.
if (solution_output)
{
out_fn_vtk(&sln, "sln", as);
out_orders_vtk(&space, "order", as);
}
// Skip the visualization time.
cpu_time.tick(HERMES_SKIP);
// Calculate element errors and total error estimate.
info("Calculating error estimate.");
Adapt *adaptivity = new Adapt(&space, HERMES_HCURL_NORM);
bool solutions_for_adapt = true;
double err_est_rel = adaptivity->calc_err_est(&sln, &ref_sln, solutions_for_adapt) * 100;
// Add entry to DOF and CPU convergence graphs.
graph_dof_est.add_values(Space::get_num_dofs(&space), err_est_rel);
graph_dof_est.save("conv_dof_est.dat");
graph_cpu_est.add_values(cpu_time.accumulated(), err_est_rel);
graph_cpu_est.save("conv_cpu_est.dat");
// Clean up.
delete ref_space->get_mesh();
delete ref_space;
delete matrix;
delete rhs;
delete solver;
delete adaptivity;
// Increase the counter of performed adaptivity steps.
as++;
done = true;
} while (!done);
return 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);
// 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;
}
}
// Sets some constants, performs uniform mesh refinement
// and calculates reference solution. This needs to get
// done prior to adaptivity.
bool ModuleBasicAdapt::prepare_for_adaptivity()
{
// Perform basic sanity checks, create mesh, perform
// uniform refinements, create space, register weak forms.
bool mesh_ok = this->create_space_and_forms();
if (!mesh_ok) return false;
this->ndof_coarse = Space::get_num_dofs(this->space);
if (this->ndof_coarse <= 0) return false;
// Initialize refinement selector.
this->ref_selector = new H1ProjBasedSelector(this->cand_list, this->conv_exp, H2DRS_DEFAULT_ORDER);
this->ref_selector->set_error_weights(this->adaptivity_weight_1, this->adaptivity_weight_2,
this->adaptivity_weight_3);
// Construct globally refined reference mesh and setup reference space.
this->space_ref = (H1Space*)construct_refined_space(this->space);
this->ndof_fine = Space::get_num_dofs(this->space_ref);
// Initialize the FE problem on reference mesh.
bool is_linear = true;
DiscreteProblem dp(this->wf, this->space_ref, is_linear);
// Set up the solver, matrix, and rhs according to the solver selection.
info("Initializing matrix solver, matrix, and rhs vector.");
SparseMatrix* matrix = create_matrix(this->matrix_solver);
Vector* rhs = create_vector(this->matrix_solver);
Solver* solver = create_linear_solver(this->matrix_solver, matrix, rhs);
// Begin assembly time measurement.
TimePeriod cpu_time_assembly;
cpu_time_assembly.tick();
// Assemble the stiffness matrix and right-hand side vector.
info("Assembling matrix and vector on reference mesh.");
dp.assemble(matrix, rhs);
// End assembly time measurement.
this->assembly_time = cpu_time_assembly.accumulated();
this->assembly_time_total += this->assembly_time;
// Begin solver time measurement.
TimePeriod cpu_time_solver;
cpu_time_solver.tick();
// Solve the linear system and if successful, obtain the solution.
info("Solving on reference mesh.");
if(solver->solve()) Solution::vector_to_solution(solver->get_solution(), this->space_ref, this->sln_ref);
else {
info("Matrix solver failed.\n");
return false;
}
// End solver time measurement.
cpu_time_solver.tick();
this->solver_time = cpu_time_solver.accumulated();
this->solver_time_total += this->solver_time;
// Clean up.
info("Deleting matrix solver, matrix and rhs vector.");
delete solver;
delete matrix;
delete rhs;
return true;
}
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);
info("N_dof = %d.", Space::get_num_dofs(space));
// 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.
// Obtain the number of degrees of freedom.
int ndof = Space::get_num_dofs(space);
// Fill vector coeff_vec using dof and coeffs arrays in elements.
double *coeff_vec_coarse = new double[Space::get_num_dofs(space)];
solution_to_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(matrix_coarse, rhs_coarse);
// Calculate the l2-norm of residual vector.
double res_norm = 0;
for(int i=0; i<ndof_coarse; i++) res_norm += rhs_coarse->get(i)*rhs_coarse->get(i);
res_norm = sqrt(res_norm);
// Info for user.
info("---- Newton iter %d, residual norm: %.15f", it, res_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_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.
vector_to_solution(coeff_vec_coarse, space);
it++;
}
// Cleanup.
delete matrix_coarse;
delete rhs_coarse;
delete solver_coarse;
delete dp_coarse;
delete [] coeff_vec_coarse;
// DOF and CPU convergence graphs.
SimpleGraph graph_dof_est, graph_cpu_est;
SimpleGraph graph_dof_exact, graph_cpu_exact;
// Main adaptivity loop.
int as = 1;
while(1) {
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 fine mesh.
// Fill vector coeff_vec using dof and coeffs arrays in elements.
double *coeff_vec = new double[Space::get_num_dofs(ref_space)];
solution_to_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(matrix, rhs);
// Calculate the l2-norm of residual vector.
double res_norm = 0;
for(int i=0; i<ndof; i++) res_norm += rhs->get(i)*rhs->get(i);
res_norm = sqrt(res_norm);
// Info for user.
info("---- Newton iter %d, residual norm: %.15f", it, res_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_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.
vector_to_solution(coeff_vec, ref_space);
it++;
}
// Cleanup.
delete matrix;
delete rhs;
delete solver;
delete dp;
delete [] coeff_vec;
// Starting with second adaptivity step, obtain new coarse
// space solution via Newton's method. Initial condition is
// the last coarse mesh solution.
if (as > 1) {
//Info for user.
info("Solving on coarse mesh");
// 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)];
solution_to_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(matrix_coarse, rhs_coarse);
// Calculate the l2-norm of residual vector.
double res_norm = 0;
for(int i=0; i<ndof_coarse; i++) res_norm += rhs_coarse->get(i)*rhs_coarse->get(i);
res_norm = sqrt(res_norm);
// Info for user.
info("---- Newton iter %d, residual norm: %.15f", it, res_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_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.
vector_to_solution(coeff_vec_coarse, space);
it++;
}
// Cleanup.
delete matrix_coarse;
delete rhs_coarse;
delete solver_coarse;
delete dp_coarse;
delete [] coeff_vec_coarse;
}
// In the next step, estimate element errors based on
// the difference between the fine mesh and coarse mesh solutions.
double err_est_array[MAX_ELEM_NUM];
double err_est_rel = calc_err_est(NORM,
space, ref_space, err_est_array) * 100;
// Info for user.
info("Relative error (est) = %g %%", 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);
}
// 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) 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 ref_space;
}
// 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");
int success_test = 1;
info("N_dof = %d.", Space::get_num_dofs(space));
if (Space::get_num_dofs(space) > 40) success_test = 0;
if (success_test) {
info("Success!");
return ERROR_SUCCESS;
}
else {
info("Failure!");
return ERROR_FAILURE;
}
}
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);
// 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;
// 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);
}
// 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);
// If err_est_rel too large, adapt the mesh.
if (err_est_rel < NEWTON_TOL_REF) done = true;
else
{
info("Adapting the coarse mesh.");
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");
return 0;
}
