Hi, all,
If there is no function to compute convergence above, I need to write the
code by myself.
For Question 1, I write a code to compute the L2 norm of (solution_1 -
solution_2):
template <int dim>
double StokesProblem<dim>::norm_compute (const Vector<double> solu_1,
const Vector<double> solu_2)
{
QGauss<dim> quadrature_formula(degree+2);
FEValues<dim> fe_values (fe, quadrature_formula,
update_values |
update_quadrature_points |
update_JxW_values |
update_gradients);
const unsigned int dofs_per_cell = fe.dofs_per_cell;
const unsigned int n_q_points = quadrature_formula.size();
FullMatrix<double> local_con_rate_matrix (dofs_per_cell,
dofs_per_cell);
std::vector<types::global_dof_index> local_dof_indices (dofs_per_cell);
std::vector<double> solu_1_values(n_q_points);
std::vector<double> solu_2_values(n_q_points);
double norm_12 = 0, norm_24 = 1,norm_12_square = 0, norm_24_square = 1,
rate_124 = 0, con_rate = 0;
typename DoFHandler<dim>::active_cell_iterator
cell = dof_handler.begin_active(),
endc = dof_handler.end();
for (; cell!=endc; ++cell)
{
fe_values.reinit (celli);
fe_values.get_function_values (solu_1, solu_1_values);
fe_values.get_function_values (solu_2, solu_2_values);
for (unsigned int q=0; q<n_q_points; ++q)
{
const double delta_12 = solu_1_values[q] - solu_2_values[q];
norm_12_square += ( delta_12 * delta_12 )
* fe_values.JxW(q);
}
}
norm_12 = std::sqrt(norm_12_square);
return norm_12;
}
Is that right?
For question 2, as the 2 solution vectors have different sizes, we don't
have the same cells, so the cell loop cannot compute altogether:
typename DoFHandler<dim>::active_cell_iterator
cell_1 = dof_handler_1.begin_active(),
endc_1 = dof_handler_1.end();
typename DoFHandler<dim>::active_cell_iterator
cell_2 = dof_handler_2.begin_active();
for (; cell_1!=endc_2; ++cell_1, ++cell_2)
{....}
I wander how to solve this problem?
Thanks in advance!
Best,
Chucui
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