void RBEIMConstruction::initialize_parametrized_functions_in_training_set()
{
if(!serial_training_set)
{
libMesh::err << "Error: We must have serial_training_set==true in "
<< "RBEIMConstruction::initialize_parametrized_functions_in_training_set"
<< std::endl;
libmesh_error();
}
libMesh::out << "Initializing parametrized functions in training set..." << std::endl;
// initialize rb_eval's parameters
get_rb_evaluation().initialize_parameters(*this);
_parametrized_functions_in_training_set.resize( get_n_training_samples() );
for(unsigned int i=0; i<get_n_training_samples(); i++)
{
set_params_from_training_set(i);
truth_solve(-1);
_parametrized_functions_in_training_set[i] = solution->clone().release();
libMesh::out << "Completed solve for training sample " << (i+1) << " of " << get_n_training_samples() << std::endl;
}
_parametrized_functions_in_training_set_initialized = true;
libMesh::out << "Parametrized functions in training set initialized" << std::endl << std::endl;
}
Real RBEIMConstruction::compute_best_fit_error()
{
START_LOG("compute_best_fit_error()", "RBEIMConstruction");
const unsigned int RB_size = get_rb_evaluation().get_n_basis_functions();
// load up the parametrized function for the current parameters
truth_solve(-1);
switch(best_fit_type_flag)
{
// Perform an L2 projection in order to find an approximation to solution (from truth_solve above)
case(PROJECTION_BEST_FIT):
{
// compute the rhs by performing inner products
DenseVector<Number> best_fit_rhs(RB_size);
inner_product_matrix->vector_mult(*inner_product_storage_vector, *solution);
for(unsigned int i=0; i<RB_size; i++)
{
best_fit_rhs(i) = inner_product_storage_vector->dot(get_rb_evaluation().get_basis_function(i));
}
// Now compute the best fit by an LU solve
get_rb_evaluation().RB_solution.resize(RB_size);
DenseMatrix<Number> RB_inner_product_matrix_N(RB_size);
get_rb_evaluation().RB_inner_product_matrix.get_principal_submatrix(RB_size, RB_inner_product_matrix_N);
RB_inner_product_matrix_N.lu_solve(best_fit_rhs, get_rb_evaluation().RB_solution);
break;
}
// Perform EIM solve in order to find the approximation to solution
// (rb_solve provides the EIM basis function coefficients used below)
case(EIM_BEST_FIT):
{
// Turn off error estimation for this rb_solve, we use the linfty norm instead
get_rb_evaluation().evaluate_RB_error_bound = false;
get_rb_evaluation().set_parameters( get_parameters() );
get_rb_evaluation().rb_solve(RB_size);
get_rb_evaluation().evaluate_RB_error_bound = true;
break;
}
default:
libmesh_error_msg("Should not reach here");
}
// load the error into solution
for(unsigned int i=0; i<get_rb_evaluation().get_n_basis_functions(); i++)
{
solution->add(-get_rb_evaluation().RB_solution(i), get_rb_evaluation().get_basis_function(i));
}
Real best_fit_error = solution->linfty_norm();
STOP_LOG("compute_best_fit_error()", "RBEIMConstruction");
return best_fit_error;
}
