void DistributedVector<T>::conjugate()
{
for (numeric_index_type i=0; i<local_size(); i++)
{
// Replace values by complex conjugate
_values[i] = libmesh_conj(_values[i]);
}
}
void LaspackVector<T>::conjugate()
{
const numeric_index_type n = this->size();
for (numeric_index_type i=0; i<n; i++)
{
T v = (*this)(i);
this->set(i, libmesh_conj(v) );
}
}
Real RBEvaluation::eval_output_dual_norm(unsigned int n, const RBParameters& mu)
{
Number output_bound_sq = 0.;
unsigned int q=0;
for(unsigned int q_l1=0; q_l1<rb_theta_expansion->get_n_output_terms(n); q_l1++)
{
for(unsigned int q_l2=q_l1; q_l2<rb_theta_expansion->get_n_output_terms(n); q_l2++)
{
Real delta = (q_l1==q_l2) ? 1. : 2.;
output_bound_sq += delta * libmesh_real(
libmesh_conj(rb_theta_expansion->eval_output_theta(n,q_l1,mu))*
rb_theta_expansion->eval_output_theta(n,q_l2,mu) * output_dual_innerprods[n][q] );
q++;
}
}
return libmesh_real(std::sqrt( output_bound_sq ));
}
Real RBEvaluation::compute_residual_dual_norm(const unsigned int N)
{
START_LOG("compute_residual_dual_norm()", "RBEvaluation");
const RBParameters& mu = get_parameters();
// Use the stored representor inner product values
// to evaluate the residual norm
Number residual_norm_sq = 0.;
unsigned int q=0;
for(unsigned int q_f1=0; q_f1<rb_theta_expansion->get_n_F_terms(); q_f1++)
{
for(unsigned int q_f2=q_f1; q_f2<rb_theta_expansion->get_n_F_terms(); q_f2++)
{
Real delta = (q_f1==q_f2) ? 1. : 2.;
residual_norm_sq += delta * libmesh_real(
rb_theta_expansion->eval_F_theta(q_f1, mu)
* libmesh_conj(rb_theta_expansion->eval_F_theta(q_f2, mu)) * Fq_representor_innerprods[q] );
q++;
}
}
for(unsigned int q_f=0; q_f<rb_theta_expansion->get_n_F_terms(); q_f++)
{
for(unsigned int q_a=0; q_a<rb_theta_expansion->get_n_A_terms(); q_a++)
{
for(unsigned int i=0; i<N; i++)
{
Real delta = 2.;
residual_norm_sq +=
delta * libmesh_real( rb_theta_expansion->eval_F_theta(q_f, mu) *
libmesh_conj(rb_theta_expansion->eval_A_theta(q_a, mu)) *
libmesh_conj(RB_solution(i)) * Fq_Aq_representor_innerprods[q_f][q_a][i] );
}
}
}
q=0;
for(unsigned int q_a1=0; q_a1<rb_theta_expansion->get_n_A_terms(); q_a1++)
{
for(unsigned int q_a2=q_a1; q_a2<rb_theta_expansion->get_n_A_terms(); q_a2++)
{
Real delta = (q_a1==q_a2) ? 1. : 2.;
for(unsigned int i=0; i<N; i++)
{
for(unsigned int j=0; j<N; j++)
{
residual_norm_sq +=
delta * libmesh_real( libmesh_conj(rb_theta_expansion->eval_A_theta(q_a1, mu)) *
rb_theta_expansion->eval_A_theta(q_a2, mu) *
libmesh_conj(RB_solution(i)) * RB_solution(j) * Aq_Aq_representor_innerprods[q][i][j] );
}
}
q++;
}
}
if(libmesh_real(residual_norm_sq) < 0.)
{
// libMesh::out << "Warning: Square of residual norm is negative "
// << "in RBSystem::compute_residual_dual_norm()" << std::endl;
// Sometimes this is negative due to rounding error,
// but when this occurs the error is on the order of 1.e-10,
// so shouldn't affect error bound much...
residual_norm_sq = std::abs(residual_norm_sq);
}
STOP_LOG("compute_residual_dual_norm()", "RBEvaluation");
return std::sqrt( libmesh_real(residual_norm_sq) );
}