view liboctave/numeric/sparse-lu.h @ 29931:7faff48840eb

prefer data over fortran_vec for read-only access to data See also the discussion here: https://octave.discourse.group/t/rename-uses-of-fortran-vec-to-data-for-clarity/1439 * Array.h (const T * Array<T>::fortran_vec (void) const): Deprecate. Change all uses to call data instead.
author John W. Eaton <jwe@octave.org>
date Fri, 30 Jul 2021 11:46:05 -0400
parents 7854d5752dd2
children 7215f2324c8a
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////////////////////////////////////////////////////////////////////////
//
// Copyright (C) 1998-2021 The Octave Project Developers
//
// See the file COPYRIGHT.md in the top-level directory of this
// distribution or <https://octave.org/copyright/>.
//
// This file is part of Octave.
//
// Octave is free software: you can redistribute it and/or modify it
// under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// Octave is distributed in the hope that it will be useful, but
// WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with Octave; see the file COPYING.  If not, see
// <https://www.gnu.org/licenses/>.
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////////////////////////////////////////////////////////////////////////

#if ! defined (octave_sparse_lu_h)
#define octave_sparse_lu_h 1

#include "octave-config.h"

#include "MArray.h"
#include "dMatrix.h"
#include "dSparse.h"

class ColumnVector;
class PermMatrix;

namespace octave
{
  namespace math
  {
    // If the sparse matrix classes become templated on the element type
    // (i.e., sparse_matrix<double>), then it might be best to make the
    // template parameter of this class also be the element type instead
    // of the matrix type.

    template <typename lu_type>
    class
    sparse_lu
    {
    public:

      typedef typename lu_type::element_type lu_elt_type;

      sparse_lu (void)
        : Lfact (), Ufact (), Rfact (), cond (0), P (), Q () { }

      OCTAVE_API
      sparse_lu (const lu_type& a, const Matrix& piv_thres = Matrix (),
                 bool scale = false);

      OCTAVE_API
      sparse_lu (const lu_type& a, const ColumnVector& Qinit,
                 const Matrix& piv_thres, bool scale = false,
                 bool FixedQ = false, double droptol = -1.0,
                 bool milu = false, bool udiag = false);

      sparse_lu (const sparse_lu& a)
        : Lfact (a.Lfact), Ufact (a.Ufact), Rfact (), cond (a.cond),
          P (a.P), Q (a.Q)
      { }

      sparse_lu& operator = (const sparse_lu& a)
      {
        if (this != &a)
          {
            Lfact = a.Lfact;
            Ufact = a.Ufact;
            cond = a.cond;
            P = a.P;
            Q = a.Q;
          }

        return *this;
      }

      virtual ~sparse_lu (void) = default;

      lu_type L (void) const { return Lfact; }

      lu_type U (void) const { return Ufact; }

      SparseMatrix R (void) const { return Rfact; }

      OCTAVE_API lu_type Y (void) const;

      OCTAVE_API SparseMatrix Pc (void) const;

      OCTAVE_API SparseMatrix Pr (void) const;

      OCTAVE_API ColumnVector Pc_vec (void) const;

      OCTAVE_API ColumnVector Pr_vec (void) const;

      OCTAVE_API PermMatrix Pc_mat (void) const;

      OCTAVE_API PermMatrix Pr_mat (void) const;

      const octave_idx_type * row_perm (void) const { return P.data (); }

      const octave_idx_type * col_perm (void) const { return Q.data (); }

      double rcond (void) const { return cond; }

    protected:

      lu_type Lfact;
      lu_type Ufact;
      SparseMatrix Rfact;

      double cond;

      MArray<octave_idx_type> P;
      MArray<octave_idx_type> Q;
    };
  }
}

#endif