boolSparse.cc

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/*

Copyright (C) 2004-2012 David Bateman
Copyright (C) 1998-2004 Andy Adler
Copyright (C) 2010 VZLU Prague

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
<http://www.gnu.org/licenses/>.

*/

#ifdef HAVE_CONFIG_H
#include <config.h>
#endif

#include <iostream>
#include <vector>

#include "config.h"
#include "quit.h"
#include "lo-ieee.h"
#include "lo-mappers.h"

#include "boolSparse.h"
#include "dSparse.h"
#include "oct-mem.h"
#include "oct-locbuf.h"

// SparseBoolMatrix class.

bool
SparseBoolMatrix::operator == (const SparseBoolMatrix& a) const
{
  octave_idx_type nr = rows ();
  octave_idx_type nc = cols ();
  octave_idx_type nz = nnz ();
  octave_idx_type nr_a = a.rows ();
  octave_idx_type nc_a = a.cols ();
  octave_idx_type nz_a = a.nnz ();

  if (nr != nr_a || nc != nc_a || nz != nz_a)
    return false;

  for (octave_idx_type i = 0; i < nc + 1; i++)
    if (cidx(i) != a.cidx(i))
        return false;

  for (octave_idx_type i = 0; i < nz; i++)
    if (data(i) != a.data(i) || ridx(i) != a.ridx(i))
      return false;

  return true;
}

bool
SparseBoolMatrix::operator != (const SparseBoolMatrix& a) const
{
  return !(*this == a);
}

SparseBoolMatrix&
SparseBoolMatrix::insert (const SparseBoolMatrix& a, octave_idx_type r, octave_idx_type c)
{
  Sparse<bool>::insert (a, r, c);
  return *this;
}

SparseBoolMatrix&
SparseBoolMatrix::insert (const SparseBoolMatrix& a, const Array<octave_idx_type>& indx)
{
  Sparse<bool>::insert (a, indx);
  return *this;
}

SparseBoolMatrix
SparseBoolMatrix::concat (const SparseBoolMatrix& rb, const Array<octave_idx_type>& ra_idx)
{
  // Don't use numel to avoid all possiblity of an overflow
  if (rb.rows () > 0 && rb.cols () > 0)
    insert (rb, ra_idx(0), ra_idx(1));
  return *this;
}

// unary operations

SparseBoolMatrix
SparseBoolMatrix::operator ! (void) const
{
  octave_idx_type nr = rows ();
  octave_idx_type nc = cols ();
  octave_idx_type nz1 = nnz ();
  octave_idx_type nz2 = nr*nc - nz1;

  SparseBoolMatrix r (nr, nc, nz2);

  octave_idx_type ii = 0;
  octave_idx_type jj = 0;
  r.cidx (0) = 0;
  for (octave_idx_type i = 0; i < nc; i++)
    {
      for (octave_idx_type j = 0; j < nr; j++)
        {
          if (jj < cidx(i+1) && ridx(jj) == j)
            jj++;
          else
            {
              r.data(ii) = true;
              r.ridx(ii++) = j;
            }
        }
      r.cidx (i+1) = ii;
    }

  return r;
}

// other operations

// FIXME Do these really belong here?  Maybe they should be
// in a base class?

SparseBoolMatrix
SparseBoolMatrix::all (int dim) const
{
  SPARSE_ALL_OP (dim);
}

SparseBoolMatrix
SparseBoolMatrix::any (int dim) const
{
  Sparse<bool> retval;
  octave_idx_type nr = rows (), nc = cols (), nz = nnz ();
  if (dim == -1)
    dim = (nr == 1 && nc != 1) ? 1 : 0;

  if (dim == 0)
    {
      // Result is a row vector.
      retval = Sparse<bool> (1, nc);
      retval.xcidx(0) = 0;
      for (octave_idx_type i = 0; i < nc; i++)
        retval.xcidx(i+1) = retval.xcidx(i) + (cidx(i+1) > cidx(i));
      octave_idx_type new_nz = retval.xcidx(nc);
      retval.change_capacity (new_nz);
      fill_or_memset (new_nz, static_cast<octave_idx_type> (0), retval.ridx ());
      fill_or_memset (new_nz, true, retval.data ());
    }
  else if (dim == 1)
    {
      // Result is a column vector.
      if (nz > nr/4)
        {
          // We can use O(nr) memory.
          Array<bool> tmp (dim_vector (nr, 1), false);
          for (octave_idx_type i = 0; i < nz; i++)
            tmp.xelem(ridx(i)) = true;
          retval = tmp;
        }
      else
        {
          Array<octave_idx_type> tmp (dim_vector (nz, 1));
          copy_or_memcpy (nz, ridx (), tmp.fortran_vec ());
          retval = Sparse<bool> (Array<bool> (dim_vector (1, 1), true),
                                 idx_vector (tmp),
                                 idx_vector (static_cast<octave_idx_type> (0)),
                                 nr, 1, false);
        }
    }

  return retval;
}

SparseMatrix
SparseBoolMatrix::sum (int dim) const
{
  Sparse<double> retval;
  octave_idx_type nr = rows (), nc = cols (), nz = nnz ();
  if (dim == -1)
    dim = (nr == 1 && nc != 1) ? 1 : 0;

  if (dim == 0)
    {
      // Result is a row vector.
      retval = Sparse<double> (1, nc);
      for(octave_idx_type i = 0; i < nc; i++)
        retval.xcidx(i+1) = retval.xcidx(i) + (cidx(i+1) > cidx(i));
      octave_idx_type new_nz = retval.xcidx(nc);
      retval.change_capacity (new_nz);
      fill_or_memset (new_nz, static_cast<octave_idx_type> (0), retval.ridx ());
      for(octave_idx_type i = 0, k = 0; i < nc; i++)
        {
          octave_idx_type c = cidx(i+1) - cidx(i);
          if (c > 0)
            retval.xdata(k++) = c;
        }
    }
  else if (dim == 1)
    {
      // Result is a column vector.
      if (nz > nr)
        {
          // We can use O(nr) memory.
          Array<double> tmp (dim_vector (nr, 1), 0);
          for (octave_idx_type i = 0; i < nz; i++)
            tmp.xelem(ridx(i)) += 1.0;
          retval = tmp;
        }
      else
        {
          Array<octave_idx_type> tmp (dim_vector (nz, 1));
          copy_or_memcpy (nz, ridx (), tmp.fortran_vec ());
          retval = Sparse<double> (Array<double> (dim_vector (1, 1), 1.0),
                                   idx_vector (tmp),
                                   idx_vector (static_cast<octave_idx_type> (0)),
                                   nr, 1);
        }
    }

  return retval;
}

SparseBoolMatrix
SparseBoolMatrix::diag (octave_idx_type k) const
{
  return Sparse<bool>::diag (k);
}

boolMatrix
SparseBoolMatrix::matrix_value (void) const
{
  octave_idx_type nr = rows ();
  octave_idx_type nc = cols ();

  boolMatrix retval (nr, nc, false);
  for (octave_idx_type j = 0; j < nc; j++)
    for (octave_idx_type i = cidx(j); i < cidx(j+1); i++)
      retval.elem (ridx(i), j) = data (i);

  return retval;
}

std::ostream&
operator << (std::ostream& os, const SparseBoolMatrix& a)
{
  octave_idx_type nc = a.cols ();

   // add one to the printed indices to go from
   //  zero-based to one-based arrays
   for (octave_idx_type j = 0; j < nc; j++)
     {
       octave_quit ();
       for (octave_idx_type i = a.cidx(j); i < a.cidx(j+1); i++)
         os << a.ridx(i) + 1 << " "  << j + 1 << " " << a.data(i) << "\n";
     }

  return os;
}

std::istream&
operator >> (std::istream& is, SparseBoolMatrix& a)
{
  typedef SparseBoolMatrix::element_type elt_type;

  return read_sparse_matrix<elt_type> (is, a, octave_read_value<bool>);
}

SparseBoolMatrix
SparseBoolMatrix::squeeze (void) const
{
  return Sparse<bool>::squeeze ();
}

SparseBoolMatrix
SparseBoolMatrix::index (const idx_vector& i, bool resize_ok) const
{
  return Sparse<bool>::index (i, resize_ok);
}

SparseBoolMatrix
SparseBoolMatrix::index (const idx_vector& i, const idx_vector& j, bool resize_ok) const
{
  return Sparse<bool>::index (i, j, resize_ok);
}

SparseBoolMatrix
SparseBoolMatrix::reshape (const dim_vector& new_dims) const
{
  return Sparse<bool>::reshape (new_dims);
}

SparseBoolMatrix
SparseBoolMatrix::permute (const Array<octave_idx_type>& vec, bool inv) const
{
  return Sparse<bool>::permute (vec, inv);
}

SparseBoolMatrix
SparseBoolMatrix::ipermute (const Array<octave_idx_type>& vec) const
{
  return Sparse<bool>::ipermute (vec);
}

SPARSE_SMS_EQNE_OPS (SparseBoolMatrix, false, , bool, false, )
SPARSE_SMS_BOOL_OPS (SparseBoolMatrix, bool, false)

SPARSE_SSM_EQNE_OPS (bool, false, , SparseBoolMatrix, false, )
SPARSE_SSM_BOOL_OPS (bool, SparseBoolMatrix, false)

SPARSE_SMSM_EQNE_OPS (SparseBoolMatrix, false, , SparseBoolMatrix, false, )
SPARSE_SMSM_BOOL_OPS (SparseBoolMatrix, SparseBoolMatrix, false)