/*

Copyright (C) 2004, 2005, 2006, 2007, 2008 David Bateman
Copyright (C) 1998, 1999, 2000, 2001, 2002, 2003, 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);
      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 (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 (nz, 1);
          copy_or_memcpy (nz, ridx (), tmp.fortran_vec ());
          retval = Sparse<bool> (Array<bool> (1, 1, true),
                                 idx_vector (tmp), idx_vector (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 (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 (nz, 1);
          copy_or_memcpy (nz, ridx (), tmp.fortran_vec ());
          retval = Sparse<double> (Array<double> (1, 1, 1.0),
                                   idx_vector (tmp), idx_vector (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)