bool comparePCEs(const PCEType& a1,
const std::string& a1_name,
const Stokhos::OrthogPolyApprox<OrdinalType,ValueType>&a2,
const std::string& a2_name,
const ValueType& rel_tol, const ValueType& abs_tol,
Teuchos::FancyOStream& out)
{
bool success = true;
out << "Comparing " << a1_name << " == " << a2_name << " ... ";
const OrdinalType n = a1.size();
// Compare sizes
if (a2.size() != n) {
out << "\nError, "<<a1_name<<".size() = "<<a1.size()<<" == "
<< a2_name<<".size() = "<<a2.size()<<" : failed!\n";
return false;
}
// Compare elements
for( OrdinalType i = 0; i < n; ++i ) {
ValueType nrm = std::sqrt(a2.basis()->norm_squared(i));
ValueType err = std::abs(a1.coeff(i) - a2[i]) / nrm;
ValueType tol =
abs_tol + rel_tol*std::max(std::abs(a1.coeff(i)),std::abs(a2[i]))/nrm;
if (err > tol) {
out
<<"\nError, relErr("<<a1_name<<"["<<i<<"],"
<<a2_name<<"["<<i<<"]) = relErr("<<a1.coeff(i)<<","<<a2[i]<<") = "
<<err<<" <= tol = "<<tol<<": failed!\n";
success = false;
}
}
if (success) {
out << "passed\n";
}
else {
out << std::endl
<< a1_name << " = " << a1 << std::endl
<< a2_name << " = " << a2 << std::endl;
}
return success;
}
ordinal_type
Stokhos::ProductLanczosPCEBasis<ordinal_type, value_type>::
isInvariant(const Stokhos::OrthogPolyApprox<ordinal_type, value_type>& pce) const
{
Teuchos::RCP<const Stokhos::OrthogPolyBasis<ordinal_type,value_type> > basis =
pce.basis();
ordinal_type dim = basis->dimension();
value_type tol = 1.0e-15;
// Check if basis is a product basis
Teuchos::RCP<const Stokhos::ProductBasis<ordinal_type,value_type> > prod_basis = Teuchos::rcp_dynamic_cast<const Stokhos::ProductBasis<ordinal_type,value_type> >(basis);
if (prod_basis == Teuchos::null)
return -2;
// Build list of dimensions pce depends on by looping over each dimension,
// computing norm of pce with just that dimension -- note we don't include
// the constant term
Teuchos::Array<ordinal_type> dependent_dims;
tmp_pce.reset(basis);
for (ordinal_type i=0; i<dim; i++) {
ordinal_type p = prod_basis->getCoordinateBases()[i]->order();
tmp_pce.init(0.0);
for (ordinal_type j=1; j<=p; j++)
tmp_pce.term(i,j) = pce.term(i,j);
value_type nrm = tmp_pce.two_norm();
if (nrm > tol) dependent_dims.push_back(i);
}
// If dependent_dims has length 1, pce a function of a single variable,
// which is an invariant subspace
if (dependent_dims.size() == 1)
return dependent_dims[0];
// If dependent_dims has length 0, pce is constant
else if (dependent_dims.size() == 0)
return -1;
// Otherwise pce depends on more than one variable
return -2;
}
Stokhos::MonoProjPCEBasis<ordinal_type, value_type>::
MonoProjPCEBasis(
ordinal_type p,
const Stokhos::OrthogPolyApprox<ordinal_type, value_type>& pce,
const Stokhos::Quadrature<ordinal_type, value_type>& quad,
const Stokhos::Sparse3Tensor<ordinal_type, value_type>& Cijk,
bool limit_integration_order_) :
RecurrenceBasis<ordinal_type, value_type>("Monomial Projection", p, true),
limit_integration_order(limit_integration_order_),
pce_sz(pce.basis()->size()),
pce_norms(pce.basis()->norm_squared()),
a(pce_sz),
b(pce_sz),
basis_vecs(pce_sz, p+1),
new_pce(p+1)
{
// If the original basis is normalized, we can use the standard QR
// factorization. For simplicity, we renormalize the PCE coefficients
// for a normalized basis
Stokhos::OrthogPolyApprox<ordinal_type, value_type> normalized_pce(pce);
for (ordinal_type i=0; i<pce_sz; i++) {
pce_norms[i] = std::sqrt(pce_norms[i]);
normalized_pce[i] *= pce_norms[i];
}
// Evaluate PCE at quad points
ordinal_type nqp = quad.size();
Teuchos::Array<value_type> pce_vals(nqp);
const Teuchos::Array<value_type>& weights = quad.getQuadWeights();
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] = normalized_pce.evaluate(quad_points[i], basis_values[i]);
}
// Form Kylov matrix up to order pce_sz
matrix_type K(pce_sz, pce_sz);
// Compute matrix
matrix_type A(pce_sz, pce_sz);
typedef Stokhos::Sparse3Tensor<ordinal_type, value_type> Cijk_type;
for (typename Cijk_type::k_iterator k_it = Cijk.k_begin();
k_it != Cijk.k_end(); ++k_it) {
ordinal_type k = index(k_it);
for (typename Cijk_type::kj_iterator j_it = Cijk.j_begin(k_it);
j_it != Cijk.j_end(k_it); ++j_it) {
ordinal_type j = index(j_it);
value_type val = 0;
for (typename Cijk_type::kji_iterator i_it = Cijk.i_begin(j_it);
i_it != Cijk.i_end(j_it); ++i_it) {
ordinal_type i = index(i_it);
value_type c = value(i_it) / (pce_norms[j]*pce_norms[k]);
val += pce[i]*c;
}
A(k,j) = val;
}
}
// Each column i is given by projection of the i-th order monomial
// onto original basis
vector_type u0 = Teuchos::getCol(Teuchos::View, K, 0);
u0(0) = 1.0;
for (ordinal_type i=1; i<pce_sz; i++)
u0(i) = 0.0;
for (ordinal_type k=1; k<pce_sz; k++) {
vector_type u = Teuchos::getCol(Teuchos::View, K, k);
vector_type up = Teuchos::getCol(Teuchos::View, K, k-1);
u.multiply(Teuchos::NO_TRANS, Teuchos::NO_TRANS, 1.0, A, up, 0.0);
}
/*
for (ordinal_type j=0; j<pce_sz; j++) {
for (ordinal_type i=0; i<pce_sz; i++) {
value_type val = 0.0;
for (ordinal_type k=0; k<nqp; k++)
val += weights[k]*std::pow(pce_vals[k],j)*basis_values[k][i];
K(i,j) = val;
}
}
*/
std::cout << K << std::endl << std::endl;
// Compute QR factorization of K
ordinal_type ws_size, info;
value_type ws_size_query;
Teuchos::Array<value_type> tau(pce_sz);
Teuchos::LAPACK<ordinal_type,value_type> lapack;
lapack.GEQRF(pce_sz, pce_sz, K.values(), K.stride(), &tau[0],
&ws_size_query, -1, &info);
TEUCHOS_TEST_FOR_EXCEPTION(info != 0, std::logic_error,
"GEQRF returned value " << info);
ws_size = static_cast<ordinal_type>(ws_size_query);
Teuchos::Array<value_type> work(ws_size);
lapack.GEQRF(pce_sz, pce_sz, K.values(), K.stride(), &tau[0],
&work[0], ws_size, &info);
TEUCHOS_TEST_FOR_EXCEPTION(info != 0, std::logic_error,
"GEQRF returned value " << info);
// Get Q
lapack.ORGQR(pce_sz, pce_sz, pce_sz, K.values(), K.stride(), &tau[0],
&ws_size_query, -1, &info);
TEUCHOS_TEST_FOR_EXCEPTION(info != 0, std::logic_error,
"ORGQR returned value " << info);
ws_size = static_cast<ordinal_type>(ws_size_query);
work.resize(ws_size);
lapack.ORGQR(pce_sz, pce_sz, pce_sz, K.values(), K.stride(), &tau[0],
&work[0], ws_size, &info);
TEUCHOS_TEST_FOR_EXCEPTION(info != 0, std::logic_error,
"ORGQR returned value " << info);
// Get basis vectors
for (ordinal_type j=0; j<p+1; j++)
for (ordinal_type i=0; i<pce_sz; i++)
basis_vecs(i,j) = K(i,j);
// Compute T = Q'*A*Q
matrix_type prod(pce_sz,pce_sz);
prod.multiply(Teuchos::TRANS, Teuchos::NO_TRANS, 1.0, K, A, 0.0);
matrix_type T(pce_sz,pce_sz);
T.multiply(Teuchos::NO_TRANS, Teuchos::NO_TRANS, 1.0, prod, K, 0.0);
//std::cout << T << std::endl;
// Recursion coefficients are diagonal and super diagonal
b[0] = 1.0;
for (ordinal_type i=0; i<pce_sz-1; i++) {
a[i] = T(i,i);
b[i+1] = T(i,i+1);
}
a[pce_sz-1] = T(pce_sz-1,pce_sz-1);
// Setup rest of basis
this->setup();
// Project original PCE into the new basis
vector_type u(pce_sz);
for (ordinal_type i=0; i<pce_sz; i++)
u[i] = normalized_pce[i];
new_pce.multiply(Teuchos::TRANS, Teuchos::NO_TRANS, 1.0, basis_vecs, u,
0.0);
for (ordinal_type i=0; i<=p; i++)
new_pce[i] /= this->norms[i];
}
