libtrilinos-tpetra-dev 12.10.1-3 / usr / include / trilinos / Tsqr_CombineDefault.hpp

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/// \file Tsqr_CombineDefault.hpp
/// \brief Default copy-in, copy-out implementation of \c TSQR::Combine.
///
#ifndef __TSQR_CombineDefault_hpp
#define __TSQR_CombineDefault_hpp

#include <Teuchos_ScalarTraits.hpp>

#include <Tsqr_ApplyType.hpp>
#include <Teuchos_LAPACK.hpp>
#include <Tsqr_Matrix.hpp>

#include <algorithm>
#include <sstream>
#include <stdexcept>


namespace TSQR {

  /// \class CombineDefault
  /// \brief Default copy-in, copy-out implementation of \c TSQR::Combine.
  ///
  /// This is a default implementation of TSQR::Combine, which
  /// TSQR::Combine may use (via a "has-a" relationship) if it doesn't
  /// have a specialized, faster implementation.  This default
  /// implementation copies the inputs into a contiguous matrix
  /// buffer, operates on them there via standard LAPACK calls, and
  /// copies out the results again.  It truncates to zero any values
  /// that should be zero because of the input's structure (e.g.,
  /// upper triangular).
  template<class Ordinal, class Scalar>
  class CombineDefault {
  private:
    typedef Teuchos::LAPACK<Ordinal, Scalar> lapack_type;

  public:
    typedef Ordinal ordinal_type;
    typedef Scalar scalar_type;
    typedef typename Teuchos::ScalarTraits< Scalar >::magnitudeType magnitude_type;
    typedef ConstMatView<Ordinal, Scalar> const_mat_view_type;
    typedef MatView<Ordinal, Scalar> mat_view_type;

    CombineDefault () {}

    /// \brief Does the R factor have a nonnegative diagonal?
    ///
    /// CombineDefault implements a QR factorization (of a matrix with
    /// a special structure).  Some, but not all, QR factorizations
    /// produce an R factor whose diagonal may include negative
    /// entries.  This Boolean tells you whether CombineDefault
    /// promises to compute an R factor whose diagonal entries are all
    /// nonnegative.
    static bool QR_produces_R_factor_with_nonnegative_diagonal()
    {
      return false; // lapack_type::QR_produces_R_factor_with_nonnegative_diagonal();
    }

    void
    factor_first (const Ordinal nrows,
                  const Ordinal ncols,
                  Scalar A[],
                  const Ordinal lda,
                  Scalar tau[],
                  Scalar work[])
    {
      // info must be an int, not a LocalOrdinal, since LAPACK
      // routines always (???) use int for the INFO output argument,
      // whether or not they were built with 64-bit integer index
      // support.
      int info = 0;
      lapack_.GEQR2 (nrows, ncols, A, lda, tau, work, &info);
      if (info != 0)
        {
          std::ostringstream os;
          os << "TSQR::CombineDefault::factor_first(): LAPACK\'s "
             << "GEQR2 failed with INFO = " << info;
          throw std::logic_error (os.str());
        }
    }

    void
    apply_first (const ApplyType& applyType,
                 const Ordinal nrows,
                 const Ordinal ncols_C,
                 const Ordinal ncols_A,
                 const Scalar A[],
                 const Ordinal lda,
                 const Scalar tau[],
                 Scalar C[],
                 const Ordinal ldc,
                 Scalar work[])
    {
      int info = 0;
      // LAPACK has the nice feature that it only reads the first
      // letter of input strings that specify things like which side
      // to which to apply the operator, or whether to apply the
      // transpose.  That means we can make the strings more verbose,
      // as in "Left" here for the SIDE parameter.
      lapack_.UNM2R ('L', (applyType.toString ().c_str ())[0],
                     nrows, ncols_C, ncols_A,
                     A, lda, tau,
                     C, ldc, work, &info);
      if (info != 0) {
        std::ostringstream os;
        os << "TSQR::CombineDefault::apply_first(): LAPACK\'s "
           << "UNM2R failed with INFO = " << info;
        throw std::logic_error (os.str());
      }
    }

    void
    apply_inner (const ApplyType& apply_type,
                 const Ordinal m,
                 const Ordinal ncols_C,
                 const Ordinal ncols_Q,
                 const Scalar A[],
                 const Ordinal lda,
                 const Scalar tau[],
                 Scalar C_top[],
                 const Ordinal ldc_top,
                 Scalar C_bot[],
                 const Ordinal ldc_bot,
                 Scalar work[])
    {
      const Ordinal numRows = m + ncols_Q;

      A_buf_.reshape (numRows, ncols_Q);
      A_buf_.fill (Scalar(0));
      const_mat_view_type A_bot (m, ncols_Q, A, lda);
      mat_view_type A_buf_bot (m, ncols_Q, &A_buf_(ncols_Q, 0), A_buf_.lda());
      deep_copy (A_buf_bot, A_bot);

      C_buf_.reshape (numRows, ncols_C);
      C_buf_.fill (Scalar(0));
      mat_view_type C_buf_top (ncols_Q, ncols_C, &C_buf_(0, 0), C_buf_.lda());
      mat_view_type C_buf_bot (m, ncols_C, &C_buf_(ncols_Q, 0), C_buf_.lda());
      mat_view_type C_top_view (ncols_Q, ncols_C, C_top, ldc_top);
      mat_view_type C_bot_view (m, ncols_C, C_bot, ldc_bot);
      deep_copy (C_buf_top, C_top_view);
      deep_copy (C_buf_bot, C_bot_view);

      int info = 0;
      lapack_.UNM2R ('L', (apply_type.toString ().c_str ())[0],
                     numRows, ncols_C, ncols_Q,
                     A_buf_.get(), A_buf_.lda(), tau,
                     C_buf_.get(), C_buf_.lda(),
                     work, &info);
      if (info != 0) {
        std::ostringstream os;
        os << "TSQR::CombineDefault::apply_inner(): LAPACK\'s "
           << "UNM2R failed with INFO = " << info;
        throw std::logic_error (os.str());
      }
      // Copy back the results.
      deep_copy (C_top_view, C_buf_top);
      deep_copy (C_bot_view, C_buf_bot);
    }

    void
    factor_inner (const Ordinal m,
                  const Ordinal n,
                  Scalar R[],
                  const Ordinal ldr,
                  Scalar A[],
                  const Ordinal lda,
                  Scalar tau[],
                  Scalar work[])
    {
      const Ordinal numRows = m + n;

      A_buf_.reshape (numRows, n);
      A_buf_.fill (Scalar(0));
      // R might be a view of the upper triangle of a cache block, but
      // we only want to include the upper triangle in the
      // factorization.  Thus, only copy the upper triangle of R into
      // the appropriate place in the buffer.
      copy_upper_triangle (n, n, &A_buf_(0, 0), A_buf_.lda(), R, ldr);
      copy_matrix (m, n, &A_buf_(n, 0), A_buf_.lda(), A, lda);

      int info = 0;
      lapack_.GEQR2 (numRows, n, A_buf_.get(), A_buf_.lda(), tau, work, &info);
      if (info != 0)
        throw std::logic_error ("TSQR::CombineDefault: GEQR2 failed");

      // Copy back the results.  R might be a view of the upper
      // triangle of a cache block, so only copy into the upper
      // triangle of R.
      copy_upper_triangle (n, n, R, ldr, &A_buf_(0, 0), A_buf_.lda());
      copy_matrix (m, n, A, lda, &A_buf_(n, 0), A_buf_.lda());
    }

    void
    factor_pair (const Ordinal n,
                 Scalar R_top[],
                 const Ordinal ldr_top,
                 Scalar R_bot[],
                 const Ordinal ldr_bot,
                 Scalar tau[],
                 Scalar work[])
    {
      const Ordinal numRows = Ordinal(2) * n;

      A_buf_.reshape (numRows, n);
      A_buf_.fill (Scalar(0));
      // Copy the inputs into the compute buffer.  Only touch the
      // upper triangles of R_top and R_bot, since they each may be
      // views of some cache block (where the strict lower triangle
      // contains things we don't want to include in the
      // factorization).
      copy_upper_triangle (n, n, &A_buf_(0, 0), A_buf_.lda(), R_top, ldr_top);
      copy_upper_triangle (n, n, &A_buf_(n, 0), A_buf_.lda(), R_bot, ldr_bot);

      int info = 0;
      lapack_.GEQR2 (numRows, n, A_buf_.get(), A_buf_.lda(), tau, work, &info);
      if (info != 0)
        {
          std::ostringstream os;
          os << "TSQR::CombineDefault::factor_pair(): "
             << "GEQR2 failed with INFO = " << info;
          throw std::logic_error (os.str());
        }

      // Copy back the results.  Only read the upper triangles of the
      // two n by n row blocks of A_buf_ (this means we don't have to
      // zero out the strict lower triangles), and only touch the
      // upper triangles of R_top and R_bot.
      copy_upper_triangle (n, n, R_top, ldr_top, &A_buf_(0, 0), A_buf_.lda());
      copy_upper_triangle (n, n, R_bot, ldr_bot, &A_buf_(n, 0), A_buf_.lda());
    }

    void
    apply_pair (const ApplyType& apply_type,
                const Ordinal ncols_C,
                const Ordinal ncols_Q,
                const Scalar R_bot[],
                const Ordinal ldr_bot,
                const Scalar tau[],
                Scalar C_top[],
                const Ordinal ldc_top,
                Scalar C_bot[],
                const Ordinal ldc_bot,
                Scalar work[])
    {
      const Ordinal numRows = Ordinal(2) * ncols_Q;

      A_buf_.reshape (numRows, ncols_Q);
      A_buf_.fill (Scalar(0));
      copy_upper_triangle (ncols_Q, ncols_Q,
                           &A_buf_(ncols_Q, 0), A_buf_.lda(),
                           R_bot, ldr_bot);
      C_buf_.reshape (numRows, ncols_C);
      copy_matrix (ncols_Q, ncols_C, &C_buf_(0, 0), C_buf_.lda(), C_top, ldc_top);
      copy_matrix (ncols_Q, ncols_C, &C_buf_(ncols_Q, 0), C_buf_.lda(), C_bot, ldc_bot);

      int info = 0;
      lapack_.UNM2R ('L', (apply_type.toString ().c_str ())[0],
                     numRows, ncols_C, ncols_Q,
                     A_buf_.get(), A_buf_.lda(), tau,
                     C_buf_.get(), C_buf_.lda(),
                     work, &info);
      if (info != 0) {
        std::ostringstream os;
        os << "TSQR::CombineDefault: UNM2R failed with INFO = " << info;
        throw std::logic_error (os.str ());
      }

      // Copy back the results.
      copy_matrix (ncols_Q, ncols_C, C_top, ldc_top, &C_buf_(0, 0), C_buf_.lda());
      copy_matrix (ncols_Q, ncols_C, C_bot, ldc_bot, &C_buf_(ncols_Q, 0), C_buf_.lda());
    }

  private:
    lapack_type lapack_;
    Matrix<Ordinal, Scalar> A_buf_;
    Matrix<Ordinal, Scalar> C_buf_;
  };


} // namespace TSQR

#endif // __TSQR_CombineDefault_hpp