/usr/include/trilinos/Stokhos_LanczosPCEBasisImp.hpp is in libtrilinos-stokhos-dev 12.12.1-5.
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#include "Teuchos_Assert.hpp"
#include "Teuchos_BLAS.hpp"
#include "Teuchos_TimeMonitor.hpp"
template <typename ordinal_type, typename value_type>
Stokhos::LanczosPCEBasis<ordinal_type, value_type>::
LanczosPCEBasis(
ordinal_type p,
const Teuchos::RCP< const Stokhos::OrthogPolyApprox<ordinal_type, value_type> >& pce_,
const Teuchos::RCP< const Stokhos::Quadrature<ordinal_type, value_type> >& quad_,
bool normalize,
bool limit_integration_order_) :
RecurrenceBasis<ordinal_type, value_type>("Lanczos PCE", p, normalize),
pce(pce_),
quad(quad_),
limit_integration_order(limit_integration_order_),
nqp(quad->size()),
pce_weights(Teuchos::Copy,
const_cast<value_type*>(quad->getQuadWeights().getRawPtr()),
nqp),
pce_vals(nqp),
u0(nqp),
lanczos_vecs(nqp, p+1),
fromStieltjesMat(),
new_pce()
{
// Evaluate PCE at quad points
const Teuchos::Array< Teuchos::Array<value_type> >& quad_points =
quad->getQuadPoints();
const Teuchos::Array< Teuchos::Array<value_type> >& basis_values =
quad->getBasisAtQuadPoints();
for (ordinal_type i=0; i<nqp; i++) {
pce_vals[i] = pce->evaluate(quad_points[i], basis_values[i]);
u0[i] = value_type(1);
}
// Setup rest of basis
this->setup();
}
template <typename ordinal_type, typename value_type>
Stokhos::LanczosPCEBasis<ordinal_type, value_type>::
~LanczosPCEBasis()
{
}
template <typename ordinal_type, typename value_type>
void
Stokhos::LanczosPCEBasis<ordinal_type, value_type>::
getQuadPoints(ordinal_type quad_order,
Teuchos::Array<value_type>& quad_points,
Teuchos::Array<value_type>& quad_weights,
Teuchos::Array< Teuchos::Array<value_type> >& quad_values) const
{
#ifdef STOKHOS_TEUCHOS_TIME_MONITOR
TEUCHOS_FUNC_TIME_MONITOR("Stokhos::LanczosPCEBasis -- compute Gauss points");
#endif
// Call base class
ordinal_type num_points =
static_cast<ordinal_type>(std::ceil((quad_order+1)/2.0));
// We can't always reliably generate quadrature points of order > 2*p
// when using sparse grids for the underlying quadrature
if (limit_integration_order && quad_order > 2*this->p)
quad_order = 2*this->p;
Stokhos::RecurrenceBasis<ordinal_type,value_type>::getQuadPoints(quad_order,
quad_points,
quad_weights,
quad_values);
// Fill in the rest of the points with zero weight
if (quad_weights.size() < num_points) {
ordinal_type old_size = quad_weights.size();
quad_weights.resize(num_points);
quad_points.resize(num_points);
quad_values.resize(num_points);
for (ordinal_type i=old_size; i<num_points; i++) {
quad_weights[i] = value_type(0);
quad_points[i] = quad_points[0];
quad_values[i].resize(this->p+1);
this->evaluateBases(quad_points[i], quad_values[i]);
}
}
}
template <typename ordinal_type, typename value_type>
Teuchos::RCP<Stokhos::OneDOrthogPolyBasis<ordinal_type,value_type> >
Stokhos::LanczosPCEBasis<ordinal_type, value_type>::
cloneWithOrder(ordinal_type p) const
{
return Teuchos::rcp(new Stokhos::LanczosPCEBasis<ordinal_type,value_type>(
p,*this));
}
template <typename ordinal_type, typename value_type>
value_type
Stokhos::LanczosPCEBasis<ordinal_type, value_type>::
getNewCoeffs(ordinal_type i) const
{
return new_pce[i];
}
template <typename ordinal_type, typename value_type>
void
Stokhos::LanczosPCEBasis<ordinal_type, value_type>::
transformCoeffsFromLanczos(const value_type *in, value_type *out) const
{
Teuchos::BLAS<ordinal_type, value_type> blas;
ordinal_type sz = fromStieltjesMat.numRows();
blas.GEMV(Teuchos::NO_TRANS, sz, this->p+1,
value_type(1.0), fromStieltjesMat.values(), sz,
in, ordinal_type(1), value_type(0.0), out, ordinal_type(1));
}
template <typename ordinal_type, typename value_type>
bool
Stokhos::LanczosPCEBasis<ordinal_type, value_type>::
computeRecurrenceCoefficients(ordinal_type n,
Teuchos::Array<value_type>& alpha,
Teuchos::Array<value_type>& beta,
Teuchos::Array<value_type>& delta,
Teuchos::Array<value_type>& gamma) const
{
Teuchos::Array<value_type> nrm(n);
vectorspace_type vs(pce_weights);
operator_type A(pce_vals);
// Create space to store lanczos vectors -- use lanczos_vecs if
// we are requesting p+1 vectors
Teuchos::RCP<matrix_type> lv;
if (n == this->p+1)
lv = Teuchos::rcp(&lanczos_vecs, false);
else
lv = Teuchos::rcp(new matrix_type(nqp,n));
if (this->normalize)
lanczos_type::computeNormalized(n, vs, A, u0, *lv, alpha, beta, nrm);
else
lanczos_type::compute(n, vs, A, u0, *lv, alpha, beta, nrm);
for (ordinal_type i=0; i<n; i++) {
delta[i] = value_type(1.0);
}
if (this->normalize)
gamma = beta;
else
for (ordinal_type i=0; i<n; i++)
gamma[i] = value_type(1.0);
return this->normalize;
}
template <typename ordinal_type, typename value_type>
void
Stokhos::LanczosPCEBasis<ordinal_type, value_type>::
setup()
{
RecurrenceBasis<ordinal_type,value_type>::setup();
// Compute transformation matrix back to original basis
ordinal_type sz = pce->size();
fromStieltjesMat.shape(sz, this->p+1);
fromStieltjesMat.putScalar(0.0);
const Teuchos::Array< Teuchos::Array<value_type> >& basis_values =
quad->getBasisAtQuadPoints();
for (ordinal_type i=0; i<sz; i++) {
for (ordinal_type j=0; j<=this->p; j++) {
for (ordinal_type k=0; k<nqp; k++)
fromStieltjesMat(i,j) +=
pce_weights[k]*lanczos_vecs(k,j)*basis_values[k][i];
fromStieltjesMat(i,j) /= pce->basis()->norm_squared(i);
}
}
// Project original PCE into the new basis
new_pce.resize(this->p+1);
vector_type u(sz);
for (ordinal_type i=0; i<sz; i++)
u[i] = (*pce)[i]*pce->basis()->norm_squared(i);
new_pce.multiply(Teuchos::TRANS, Teuchos::NO_TRANS, 1.0, fromStieltjesMat, u,
0.0);
for (ordinal_type i=0; i<=this->p; i++)
new_pce[i] /= this->norms[i];
}
template <typename ordinal_type, typename value_type>
Stokhos::LanczosPCEBasis<ordinal_type, value_type>::
LanczosPCEBasis(ordinal_type p, const LanczosPCEBasis& basis) :
RecurrenceBasis<ordinal_type, value_type>(p, basis),
pce(basis.pce),
quad(basis.quad),
limit_integration_order(basis.limit_integration_order),
nqp(basis.nqp),
pce_weights(basis.pce_weights),
pce_vals(basis.pce_vals),
u0(basis.u0),
lanczos_vecs(nqp, p+1),
fromStieltjesMat(),
new_pce()
{
this->setup();
}
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