/usr/include/trilinos/Stokhos_OrthogonalizationFactory.hpp is in libtrilinos-stokhos-dev 12.4.2-2.
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// Stokhos Package
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#ifndef STOKHOS_ORTHOGONALIZATION_FACTORY_HPP
#define STOKHOS_ORTHOGONALIZATION_FACTORY_HPP
#include <string>
#include "Teuchos_Array.hpp"
#include "Teuchos_SerialDenseMatrix.hpp"
#include "Stokhos_SDMUtils.hpp"
namespace Stokhos {
/*!
* \brief Encapsulate various orthogonalization (ie QR) methods
*/
template <typename ordinal_type, typename value_type>
class OrthogonalizationFactory {
public:
//! Constructor
/*!
* \param params Parameter dictating choice of reduction method
*/
OrthogonalizationFactory() {}
//! Destructor
virtual ~OrthogonalizationFactory() {}
typedef Teuchos::SerialDenseMatrix<ordinal_type,value_type> SDM;
//! Create orthogonal basis via the method indicated by \c method
static ordinal_type
createOrthogonalBasis(const std::string& method, value_type threshold,
bool verbose, const SDM& A,
const Teuchos::Array<value_type>& w,
SDM& Q, SDM& R,
Teuchos::Array<ordinal_type>& piv) {
ordinal_type m = A.numRows();
ordinal_type n = A.numCols();
ordinal_type rank = std::min(m,n);
if (method == "SVD") { // A = U*diag(sigma)*V^T, Q = U, R = sigma*V^T
Teuchos::Array<value_type> sigma;
SDM Vt;
rank = svd_threshold(threshold, A, sigma, Q, Vt);
R.reshape(rank, Vt.numCols());
for (ordinal_type j=0; j<Vt.numCols(); j++)
for (ordinal_type i=0; i<rank; i++)
R(i,j) = sigma[i]*Vt(i,j);
piv.resize(n);
for (int i=0; i<n; i++)
piv[i] = i;
if (verbose) {
// std::cout << "diag(sigma) = [ ";
// for (ordinal_type i=0; i<rank; i++)
// std::cout << sigma[i] << " ";
// std::cout << "]" << std::endl;
std::cout << "rank = " << rank << std::endl;
}
}
else { // All QR-based methods
if (method == "Householder")
rank = CPQR_Householder_threshold(threshold, A, w, Q, R, piv);
else if (method == "Householder without Pivoting") {
QR_Householder(rank, A, w, Q, R);
piv.resize(n);
for (int i=0; i<n; i++)
piv[i] = i;
}
else if (method == "Modified Gram-Schmidt")
rank = CPQR_MGS_threshold(threshold, A, w, Q, R, piv);
else if (method == "Modified Gram-Schmidt with Reorthogonalization")
rank = CPQR_MGS_reorthog_threshold(threshold, A, w, Q, R, piv);
else if (method == "Modified Gram-Schmidt without Pivoting") {
QR_MGS(rank, A, w, Q, R);
piv.resize(n);
for (int i=0; i<n; i++)
piv[i] = i;
}
else if (method == "Modified Gram-Schmidt without Pivoting with Reorthogonalization") {
QR_MGS2(rank, A, w, Q, R);
piv.resize(n);
for (int i=0; i<n; i++)
piv[i] = i;
}
else
TEUCHOS_TEST_FOR_EXCEPTION(
true, std::logic_error,
"Invalid orthogonalization method " << method);
if (verbose) {
// std::cout << "piv = [";
// for (ordinal_type i=0; i<rank; i++)
// std::cout << piv[i] << " ";
// std::cout << "]" << std::endl;
// std::cout << "diag(R) = [ ";
// for (ordinal_type i=0; i<rank; i++)
// std::cout << R(i,i) << " ";
// std::cout << "]" << std::endl;
std::cout << "rank = " << rank << std::endl;
// Check A*P = Q*R
std::cout << "||A*P-Q*R||_infty = "
<< Stokhos::residualCPQRError(A,Q,R,piv) << std::endl;
// Check Q^T*diag(w)*Q = I
std::cout << "||I - Q^T*diag(w)**Q||_infty = "
<< weightedQROrthogonalizationError(Q,w) << std::endl;
}
}
return rank;
}
private:
// Prohibit copying
OrthogonalizationFactory(const OrthogonalizationFactory&);
// Prohibit Assignment
OrthogonalizationFactory& operator=(const OrthogonalizationFactory&);
}; // class OrthogonalizationFactory
} // Namespace Stokhos
#endif
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