/usr/include/trilinos/Stokhos_GramSchmidtBasisImp.hpp is in libtrilinos-stokhos-dev 12.4.2-2.
This file is owned by root:root, with mode 0o644.
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// $Source$
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// Stokhos Package
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#include "Teuchos_BLAS.hpp"
template <typename ordinal_type, typename value_type>
Stokhos::GramSchmidtBasis<ordinal_type, value_type>::
GramSchmidtBasis(
const Teuchos::RCP<const OrthogPolyBasis<ordinal_type,value_type> >& basis_,
const Teuchos::Array< Teuchos::Array<value_type> >& points,
const Teuchos::Array<value_type>& weights_,
const value_type& sparse_tol_) :
name("Gram Schmidt Basis"),
basis(basis_),
weights(weights_),
sparse_tol(sparse_tol_),
p(basis->order()),
d(basis->dimension()),
sz(basis->size()),
norms(sz),
gs_mat(sz,sz),
basis_vals_tmp(sz)
{
// Get quadrature data
ordinal_type nqp = weights.size();
Teuchos::Array< Teuchos::Array<value_type> > values(nqp);
for (ordinal_type k=0; k<nqp; k++) {
values[k].resize(sz);
basis->evaluateBases(points[k], values[k]);
}
// Compute all inner products
Teuchos::SerialDenseMatrix<ordinal_type, value_type> inner_product(sz,sz);
inner_product.putScalar(0.0);
for (ordinal_type i=0; i<sz; i++) {
for (ordinal_type j=0; j<=i; j++) {
value_type t = 0.0;
for (ordinal_type k=0; k<nqp; k++)
t += weights[k]*values[k][i]*values[k][j];
inner_product(i,j) = t;
}
}
// Classical Gram-Schmidt algorithm:
// u_i = v_i - \sum_{j<i} (v_i,u_j)/(u_j,u_j) u_j
// u_j = \sum_{k<=i} a_{jk} v_k
// => u_i = v_i - \sum_{j<i}\sum_{k<=j} (v_i,u_j)/(u_j,u_j)*a_{jk}*v_k
for (ordinal_type i=0; i<sz; i++) {
// a_{ii} = 1.0
gs_mat(i,i) = 1.0;
for (ordinal_type j=0; j<i; j++) {
// compute t = (v_i,u_j)/(u_j,u_j)
value_type t = 0.0;
for (ordinal_type k=0; k<=j; k++)
t += gs_mat(j,k)*inner_product(i,k);
t /= norms[j];
// substract contribution to a_{ik}: t*a_{jk}
for (ordinal_type k=0; k<=j; k++)
gs_mat(i,k) -= t*gs_mat(j,k);
}
// compute (u_i,u_i) = \sum_{j,k<=i} a_{ij}*a_{ik}*(v_j,v_k)
value_type nrm = 0.0;
for (ordinal_type j=0; j<=i; j++) {
for (ordinal_type k=0; k<=j; k++)
nrm += gs_mat(i,j)*gs_mat(i,k)*inner_product(j,k);
for (ordinal_type k=j+1; k<=i; k++)
nrm += gs_mat(i,j)*gs_mat(i,k)*inner_product(k,j);
}
norms[i] = nrm;
}
basis_values.resize(nqp);
for (ordinal_type k=0; k<nqp; k++) {
basis_values[k].resize(sz);
for (ordinal_type i=0; i<sz; i++) {
value_type t = 0.0;
for (ordinal_type j=0; j<=i; j++)
t += gs_mat(i,j)*values[k][j];
basis_values[k][i] = t;
}
}
}
template <typename ordinal_type, typename value_type>
Stokhos::GramSchmidtBasis<ordinal_type, value_type>::
~GramSchmidtBasis()
{
}
template <typename ordinal_type, typename value_type>
ordinal_type
Stokhos::GramSchmidtBasis<ordinal_type, value_type>::
order() const
{
return p;
}
template <typename ordinal_type, typename value_type>
ordinal_type
Stokhos::GramSchmidtBasis<ordinal_type, value_type>::
dimension() const
{
return d;
}
template <typename ordinal_type, typename value_type>
ordinal_type
Stokhos::GramSchmidtBasis<ordinal_type, value_type>::
size() const
{
return sz;
}
template <typename ordinal_type, typename value_type>
const Teuchos::Array<value_type>&
Stokhos::GramSchmidtBasis<ordinal_type, value_type>::
norm_squared() const
{
return norms;
}
template <typename ordinal_type, typename value_type>
const value_type&
Stokhos::GramSchmidtBasis<ordinal_type, value_type>::
norm_squared(ordinal_type i) const
{
return norms[i];
}
template <typename ordinal_type, typename value_type>
Teuchos::RCP< Stokhos::Sparse3Tensor<ordinal_type, value_type> >
Stokhos::GramSchmidtBasis<ordinal_type, value_type>::
computeTripleProductTensor() const
{
Teuchos::RCP< Stokhos::Sparse3Tensor<ordinal_type, value_type> > Cijk =
Teuchos::rcp(new Sparse3Tensor<ordinal_type, value_type>);
ordinal_type nqp = weights.size();
for (ordinal_type j=0; j<sz; j++) {
for (ordinal_type i=0; i<sz; i++) {
for (ordinal_type k=0; k<sz; k++) {
value_type t = 0.0;
for (ordinal_type l=0; l<nqp; l++)
t +=
weights[l]*basis_values[l][i]*basis_values[l][j]*basis_values[l][k];
if (std::abs(t) > sparse_tol)
Cijk->add_term(i,j,k,t);
}
}
}
Cijk->fillComplete();
return Cijk;
}
template <typename ordinal_type, typename value_type>
Teuchos::RCP< Stokhos::Sparse3Tensor<ordinal_type, value_type> >
Stokhos::GramSchmidtBasis<ordinal_type, value_type>::
computeLinearTripleProductTensor() const
{
Teuchos::RCP< Stokhos::Sparse3Tensor<ordinal_type, value_type> > Cijk =
Teuchos::rcp(new Sparse3Tensor<ordinal_type, value_type>);
ordinal_type nqp = weights.size();
for (ordinal_type j=0; j<sz; j++) {
for (ordinal_type i=0; i<sz; i++) {
for (ordinal_type k=0; k<d+1; k++) {
value_type t = 0.0;
for (ordinal_type l=0; l<nqp; l++)
t +=
weights[l]*basis_values[l][i]*basis_values[l][j]*basis_values[l][k];
if (std::abs(t) > sparse_tol)
Cijk->add_term(i,j,k,t);
}
}
}
Cijk->fillComplete();
return Cijk;
}
template <typename ordinal_type, typename value_type>
value_type
Stokhos::GramSchmidtBasis<ordinal_type, value_type>::
evaluateZero(ordinal_type i) const
{
value_type z = 0.0;
for (ordinal_type j=0; j<sz; j++)
z += gs_mat(i,j)*basis->evaluateZero(j);
return z;
}
template <typename ordinal_type, typename value_type>
void
Stokhos::GramSchmidtBasis<ordinal_type, value_type>::
evaluateBases(const Teuchos::ArrayView<const value_type>& point,
Teuchos::Array<value_type>& basis_vals) const
{
basis->evaluateBases(point, basis_vals_tmp);
for (ordinal_type i=0; i<sz; i++) {
value_type t = 0.0;
for (ordinal_type j=0; j<sz; j++)
t += gs_mat(i,j)*basis_vals_tmp[j];
basis_vals[i] = t;
}
}
template <typename ordinal_type, typename value_type>
void
Stokhos::GramSchmidtBasis<ordinal_type, value_type>::
print(std::ostream& os) const
{
os << "Gram-Schmidt basis of order " << p << ", dimension " << d
<< ", and size " << sz << ". Matrix coefficients:\n";
os << gs_mat << std::endl;
os << "Basis vector norms (squared):\n\t";
for (ordinal_type i=0; i<sz; i++)
os << norms[i] << " ";
os << "\n";
os << "Underlying basis:\n";
os << *basis;
}
template <typename ordinal_type, typename value_type>
const std::string&
Stokhos::GramSchmidtBasis<ordinal_type, value_type>::
getName() const
{
return name;
}
template <typename ordinal_type, typename value_type>
void
Stokhos::GramSchmidtBasis<ordinal_type, value_type>::
transformCoeffs(const value_type *in, value_type *out) const
{
Teuchos::BLAS<ordinal_type, value_type> blas;
for (ordinal_type i=0; i<sz; i++)
out[i] = in[i];
blas.TRSM(Teuchos::LEFT_SIDE, Teuchos::LOWER_TRI, Teuchos::TRANS,
Teuchos::UNIT_DIAG, sz, 1, 1.0, gs_mat.values(), sz, out, sz);
}
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