// classes at hand we can now implement the explicit time-stepping scheme
// that was introduced in the discussion above. The main method of the
// <code>%TimeStepping</code> class is <code>make_one_step(vector_type &U,
- // double t)</code> that takes a reference to a state vector
+ // const double t)</code> that takes a reference to a state vector
// <code>U</code> and a time point <code>t</code> (as input arguments)
// computes the updated solution, stores it in the vector
// <code>temp</code>, swaps its contents with the vector <code>U</code>,
- // and returns the chosen step-size $\tau$.
+ // and finally returns the chosen step-size $\tau$.
//
// The other important method is <code>prepare()</code> which primarily
// sets the proper partition and sparsity pattern for the temporary
void prepare();
- double make_one_step(vector_type &U, double t);
+ double make_one_step(vector_type &U, const double t);
private:
const MPI_Comm mpi_communicator;
// <code>offline_data->sparsity_pattern</code>).
template <int dim>
- double TimeStepping<dim>::make_one_step(vector_type &U, double t)
+ double TimeStepping<dim>::make_one_step(vector_type &U, const double t)
{
const auto &n_locally_owned = offline_data->n_locally_owned;
const auto &n_locally_relevant = offline_data->n_locally_relevant;