/usr/include/trilinos/Tsqr_LocalVerify.hpp is in libtrilinos-tpetra-dev 12.10.1-3.
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#ifndef __TSQR_Tsqr_LocalVerify_hpp
#define __TSQR_Tsqr_LocalVerify_hpp
#include <Tsqr_Util.hpp>
#include <Teuchos_BLAS.hpp>
#include <cmath>
#include <limits>
#include <utility> // std::pair, std::make_pair
#include <vector>
////////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////
namespace TSQR {
template< class Ordinal, class Scalar >
typename Teuchos::ScalarTraits<Scalar>::magnitudeType
local_frobenius_norm (const Ordinal nrows_local,
const Ordinal ncols,
const Scalar A_local[],
const Ordinal lda_local)
{
typedef Teuchos::ScalarTraits<Scalar> STS;
typedef typename STS::magnitudeType magnitude_type;
// FIXME (mfh 22 Apr 2010) This function does no scaling of
// intermediate quantities, so it might overflow unnecessarily.
magnitude_type result (0);
for (Ordinal j = 0; j < ncols; ++j) {
const Scalar* const cur_col = &A_local[j*lda_local];
for (Ordinal i = 0; i < nrows_local; ++i) {
const magnitude_type abs_xi = STS::magnitude (cur_col[i]);
result = result + abs_xi * abs_xi;
}
}
// FIXME (mfh 14 Oct 2014) Should we use std::sqrt or even
// STS::squareroot here instead?
return sqrt (result);
}
template< class Ordinal, class Scalar >
bool
NaN_in_matrix (const Ordinal nrows,
const Ordinal ncols,
const Scalar A[],
const Ordinal lda)
{
// Testing whether a NaN is present in A only makes sense if it is
// possible for NaNs not to signal. Otherwise the NaNs would have
// signalled and we wouldn't need to be here. Of course perhaps
// one could change the signal state at runtime, but has_quiet_NaN
// refers to the possibility of quiet NaNs being able to exist at
// all.
if (std::numeric_limits<Scalar>::has_quiet_NaN)
{
for (Ordinal j = 0; j < ncols; j++)
for (Ordinal i = 0; i < nrows; i++)
{
#ifdef __CUDACC__
if (isnan (A[i + j*lda]))
#else
if (std::isnan (A[i + j*lda]))
#endif
return true;
}
return false;
}
else
return false;
}
template< class Ordinal, class Scalar >
bool
NaN_in_matrix (const Ordinal nrows,
const Ordinal ncols,
const std::vector<Scalar>& A,
const Ordinal lda)
{
const Scalar* const A_ptr = &A[0];
return NaN_in_matrix (nrows, ncols, A_ptr, lda);
}
template< class Ordinal, class Scalar >
typename Teuchos::ScalarTraits<Scalar>::magnitudeType
localOrthogonality (const Ordinal nrows,
const Ordinal ncols,
const Scalar Q[],
const Ordinal ldq)
{
typedef Teuchos::ScalarTraits<Scalar> STS;
const Scalar ZERO (0);
const Scalar ONE (1);
Teuchos::BLAS<Ordinal, Scalar> blas;
std::vector<Scalar> AbsOrthog (ncols * ncols, std::numeric_limits<Scalar>::quiet_NaN());
const Ordinal AbsOrthog_stride = ncols;
// Compute AbsOrthog := Q' * Q - I. First, compute Q' * Q:
if (STS::isComplex) {
blas.GEMM (Teuchos::CONJ_TRANS, Teuchos::NO_TRANS, ncols, ncols, nrows,
ONE, Q, ldq, Q, ldq, ZERO, &AbsOrthog[0], AbsOrthog_stride);
}
else {
blas.GEMM (Teuchos::TRANS, Teuchos::NO_TRANS, ncols, ncols, nrows,
ONE, Q, ldq, Q, ldq, ZERO, &AbsOrthog[0], AbsOrthog_stride);
}
// Now, compute (Q^T*Q) - I.
for (Ordinal j = 0; j < ncols; ++j) {
AbsOrthog[j + j*AbsOrthog_stride] = AbsOrthog[j + j*AbsOrthog_stride] - ONE;
}
// Now AbsOrthog == Q^T * Q - I. Compute and return its Frobenius norm.
return local_frobenius_norm (ncols, ncols, &AbsOrthog[0], AbsOrthog_stride);
}
template< class Ordinal, class Scalar >
typename Teuchos::ScalarTraits<Scalar>::magnitudeType
local_relative_orthogonality (const Ordinal nrows,
const Ordinal ncols,
const Scalar Q[],
const Ordinal ldq,
const typename Teuchos::ScalarTraits<Scalar>::magnitudeType A_norm_F)
{
typedef Teuchos::ScalarTraits<Scalar> STS;
typedef typename STS::magnitudeType magnitude_type;
const Scalar ZERO (0);
const Scalar ONE (1);
const bool relative = false; // whether to scale $\|I-Q^T*Q\|_F$ by $\|A\|_F$
Teuchos::BLAS<Ordinal, Scalar> blas;
std::vector<Scalar> AbsOrthog (ncols * ncols, std::numeric_limits<Scalar>::quiet_NaN());
const Ordinal AbsOrthog_stride = ncols;
// Compute AbsOrthog := Q' * Q - I. First, compute Q' * Q:
if (STS::isComplex) {
blas.GEMM (Teuchos::CONJ_TRANS, Teuchos::NO_TRANS, ncols, ncols, nrows,
ONE, Q, ldq, Q, ldq, ZERO, &AbsOrthog[0], AbsOrthog_stride);
}
else {
blas.GEMM (Teuchos::TRANS, Teuchos::NO_TRANS, ncols, ncols, nrows,
ONE, Q, ldq, Q, ldq, ZERO, &AbsOrthog[0], AbsOrthog_stride);
}
// Now, compute (Q^T*Q) - I.
for (Ordinal j = 0; j < ncols; ++j) {
AbsOrthog[j + j*AbsOrthog_stride] = AbsOrthog[j + j*AbsOrthog_stride] - ONE;
}
// Now AbsOrthog == Q^T * Q - I. Compute its Frobenius norm.
const magnitude_type AbsOrthog_norm_F =
local_frobenius_norm (ncols, ncols, &AbsOrthog[0], AbsOrthog_stride);
// Return the orthogonality measure
return relative ? (AbsOrthog_norm_F / A_norm_F) : AbsOrthog_norm_F;
}
template< class Ordinal, class Scalar >
typename Teuchos::ScalarTraits<Scalar>::magnitudeType
localResidual (const Ordinal nrows,
const Ordinal ncols,
const Scalar A[],
const Ordinal lda,
const Scalar Q[],
const Ordinal ldq,
const Scalar R[],
const Ordinal ldr)
{
using Teuchos::NO_TRANS;
typedef Teuchos::ScalarTraits<Scalar> STS;
typedef typename STS::magnitudeType magnitude_type;
std::vector<Scalar> AbsResid (nrows * ncols,
std::numeric_limits<Scalar>::quiet_NaN ());
const Ordinal AbsResid_stride = nrows;
Teuchos::BLAS<Ordinal, Scalar> blas;
const magnitude_type ONE (1);
// A_copy := A_copy - Q * R
copy_matrix (nrows, ncols, &AbsResid[0], AbsResid_stride, A, lda);
blas.GEMM (NO_TRANS, NO_TRANS, nrows, ncols, ncols, -ONE, Q, ldq, R, ldr,
ONE, &AbsResid[0], AbsResid_stride);
return local_frobenius_norm (nrows, ncols, &AbsResid[0], AbsResid_stride);
}
template< class Ordinal, class Scalar >
typename Teuchos::ScalarTraits<Scalar>::magnitudeType
local_relative_residual (const Ordinal nrows,
const Ordinal ncols,
const Scalar A[],
const Ordinal lda,
const Scalar Q[],
const Ordinal ldq,
const Scalar R[],
const Ordinal ldr,
const typename Teuchos::ScalarTraits<Scalar>::magnitudeType A_norm_F)
{
using Teuchos::NO_TRANS;
typedef Teuchos::ScalarTraits<Scalar> STS;
typedef typename STS::magnitudeType magnitude_type;
std::vector<Scalar> AbsResid (nrows * ncols, std::numeric_limits<Scalar>::quiet_NaN ());
const Ordinal AbsResid_stride = nrows;
Teuchos::BLAS<Ordinal, Scalar> blas;
const magnitude_type ONE (1);
// if (b_debug)
// cerr << "relative_residual:" << endl;
// if (matrix_contains_nan (nrows, ncols, A, lda))
// cerr << "relative_residual: matrix A contains a NaN" << endl;
// if (matrix_contains_nan (nrows, ncols, Q, ldq))
// cerr << "relative_residual: matrix Q contains a NaN" << endl;
// if (matrix_contains_nan (ncols, ncols, R, ldr))
// cerr << "relative_residual: matrix R contains a NaN" << endl;
// A_copy := A_copy - Q * R
copy_matrix (nrows, ncols, &AbsResid[0], AbsResid_stride, A, lda);
// if (NaN_in_matrix (nrows, ncols, AbsResid, AbsResid_stride))
// cerr << "relative_residual: matrix AbsResid := A contains a NaN" << endl;
blas.GEMM (NO_TRANS, NO_TRANS, nrows, ncols, ncols, -ONE, Q, ldq, R, ldr,
ONE, &AbsResid[0], AbsResid_stride);
// if (NaN_in_matrix (nrows, ncols, AbsResid, AbsResid_stride))
// cerr << "relative_residual: matrix AbsResid := A - Q*R contains a NaN" << endl;
const magnitude_type absolute_residual =
local_frobenius_norm (nrows, ncols, &AbsResid[0], AbsResid_stride);
// if (b_debug)
// {
// cerr << "In relative_residual:" << endl;
// cerr << "||Q||_2 = " << matrix_2norm(nrows, ncols, Q, ldq) << endl;
// cerr << "||R||_2 = " << matrix_2norm(ncols, ncols, R, ldr) << endl;
// cerr << "||A - QR||_2 = " << absolute_residual << endl;
// }
return absolute_residual / A_norm_F;
}
/// Test accuracy of the computed QR factorization of the matrix A
///
/// \param nrows [in] Number of rows in the A and Q matrices;
/// nrows >= ncols >= 1
/// \param ncols [in] Number of columns in the A, Q, and R matrices;
/// nrows >= ncols >= 1
/// \param A [in] Column-oriented nrows by ncols matrix with leading
/// dimension lda
/// \param lda [in] Leading dimension of the matrix A; lda >= nrows
/// \param Q [in] Column-oriented nrows by ncols matrix with leading
/// dimension ldq; computed Q factor of A
/// \param ldq [in] Leading dimension of the matrix Q; ldq >= nrows
/// \param R [in] Column-oriented upper triangular ncols by ncols
/// matrix with leading dimension ldr; computed R factor of A
/// \param ldr [in] Leading dimension of the matrix R; ldr >= ncols
/// \return $\| A - Q R \|_F$, $\| I - Q^* Q \|_F$, and $\|A\|_F$.
/// The first is the residual of the QR factorization, the second
/// a measure of the orthogonality of the resulting Q factor, and
/// the third an appropriate scaling factor if we want to compute
/// the relative residual. All are measured in the Frobenius
/// (square root of (sum of squares of the matrix entries) norm.
///
/// \note The reason for the elaborate "magnitude_type" construction
/// is because this function returns norms, and norms always have
/// real-valued type. Scalar may be complex. We could simply set
/// the imaginary part to zero, but it seems more sensible to
/// enforce the norm's value property in the type system. Besides,
/// one could imagine more elaborate Scalars (like rational
/// functions, which do form a field) that have different plausible
/// definitions of magnitude -- this is not just a problem for
/// complex numbers (that are isomorphic to pairs of real numbers).
template< class Ordinal, class Scalar >
std::vector< typename Teuchos::ScalarTraits<Scalar>::magnitudeType >
local_verify (const Ordinal nrows,
const Ordinal ncols,
const Scalar* const A,
const Ordinal lda,
const Scalar* const Q,
const Ordinal ldq,
const Scalar* const R,
const Ordinal ldr)
{
typedef Teuchos::ScalarTraits<Scalar> STS;
typedef typename STS::magnitudeType magnitude_type;
std::vector<magnitude_type> results (3);
// const bool A_contains_NaN = NaN_in_matrix (nrows, ncols, A, lda);
// const bool Q_contains_NaN = NaN_in_matrix (nrows, ncols, Q, ldq);
// const bool R_contains_NaN = NaN_in_matrix (ncols, ncols, R, ldr);
results[0] = localResidual (nrows, ncols, A, lda, Q, ldq, R, ldr);
results[1] = localOrthogonality (nrows, ncols, Q, ldq);
results[2] = local_frobenius_norm (nrows, ncols, A, lda);
return results;
}
} // namespace TSQR
#endif // __TSQR_Tsqr_LocalVerify_hpp
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