/*

Copyright (C) 2004, 2005, 2006, 2007 David Bateman
Copyright (C) 1998, 1999, 2000, 2001, 2002, 2003, 2004 Andy Adler

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 <cstdlib>
#include <string>

#include "variables.h"
#include "utils.h"
#include "pager.h"
#include "defun-dld.h"
#include "gripes.h"
#include "quit.h"

#include "ov-re-sparse.h"
#include "ov-cx-sparse.h"
#include "ov-bool-sparse.h"

DEFUN_DLD (issparse, args, ,
  "-*- texinfo -*-\n\
@deftypefn {Loadable Function} {} issparse (@var{expr})\n\
Return 1 if the value of the expression @var{expr} is a sparse matrix.\n\
@end deftypefn") 
{
   if (args.length() != 1) 
     {
       print_usage ();
       return octave_value ();
     }
   else 
     return octave_value (args(0).is_sparse_type ());
}

DEFUN_DLD (sparse, args, ,
    "-*- texinfo -*-\n\
@deftypefn {Loadable Function} {@var{s} =} sparse (@var{a})\n\
@deftypefnx {Loadable Function} {@var{s} =} sparse (@var{i}, @var{j}, @var{sv}, @var{m}, @var{n}, @var{nzmax})\n\
@deftypefnx {Loadable Function} {@var{s} =} sparse (@var{i}, @var{j}, @var{sv})\n\
@deftypefnx {Loadable Function} {@var{s} =} sparse (@var{i}, @var{j}, @var{s}, @var{m}, @var{n}, \"unique\")\n\
@deftypefnx {Loadable Function} {@var{s} =} sparse (@var{m}, @var{n})\n\
Create a sparse matrix from the full matrix or row, column, value triplets.\n\
If @var{a} is a full matrix, convert it to a sparse matrix representation,\n\
removing all zero values in the process.\n\
\n\
Given the integer index vectors @var{i} and @var{j}, a 1-by-@code{nnz} vector\n\
of real of complex values @var{sv}, overall dimensions @var{m} and @var{n}\n\
of the sparse matrix.  The argument @code{nzmax} is ignored but accepted for\n\
compatibility with @sc{Matlab}. If @var{m} or @var{n} are not specified their\n\
values are derived from the maximum index in the vectors @var{i} and @var{j}\n\
as given by @code{@var{m} = max (@var{i})}, @code{@var{n} = max (@var{j})}.\n\
\n\
@strong{Note}: if multiple values are specified with the same\n\
@var{i}, @var{j} indices, the corresponding values in @var{s} will\n\
be added.\n\
\n\
The following are all equivalent:\n\
\n\
@example\n\
@group\n\
s = sparse (i, j, s, m, n)\n\
s = sparse (i, j, s, m, n, \"summation\")\n\
s = sparse (i, j, s, m, n, \"sum\")\n\
@end group\n\
@end example\n\
\n\
Given the option \"unique\". if more than two values are specified for the\n\
same @var{i}, @var{j} indices, the last specified value will be used.\n\
\n\
@code{sparse(@var{m}, @var{n})} is equivalent to\n\
@code{sparse ([], [], [], @var{m}, @var{n}, 0)}\n\
\n\
If any of @var{sv}, @var{i} or @var{j} are scalars, they are expanded\n\
to have a common size.\n\
@seealso{full}\n\
@end deftypefn")
{
   octave_value retval;

   // WARNING: This function should always use constructions like
   //   retval = new octave_sparse_matrix (sm);
   // To avoid calling the maybe_mutate function. This is the only
   // function that should not call maybe_mutate

   int nargin= args.length();
   if (nargin < 1 || (nargin == 4 && !args(3).is_string ()) || nargin > 6) 
     {
       print_usage ();
       return retval;
     }

   bool use_complex = false;
   bool use_bool = false;
   if (nargin > 2)
     {
       use_complex= args(2).is_complex_type();
       use_bool = args(2).is_bool_type ();
     }
   else
     {
       use_complex= args(0).is_complex_type();
       use_bool = args(0).is_bool_type ();
     }

   if (nargin == 1)
     {
       octave_value arg = args (0);

       if (arg.is_sparse_type ())
	 {
	   if (use_complex) 
	     {
	       SparseComplexMatrix sm = arg.sparse_complex_matrix_value ();
	       retval = new octave_sparse_complex_matrix (sm);
	     }
	   else if (use_bool) 
	     {
	       SparseBoolMatrix sm = arg.sparse_bool_matrix_value ();
	       retval = new octave_sparse_bool_matrix (sm);
	     }
	   else
	     {
	       SparseMatrix sm = arg.sparse_matrix_value ();
	       retval = new octave_sparse_matrix (sm);
	     }
	 }
       else if (arg.is_diag_matrix ())
         {
           if (arg.is_complex_type ())
             {
	       SparseComplexMatrix sm = arg.sparse_complex_matrix_value ();
	       retval = new octave_sparse_complex_matrix (sm);
             }
           else
             {
	       SparseMatrix sm = arg.sparse_matrix_value ();
	       retval = new octave_sparse_matrix (sm);
             }
         }
       else if (arg.is_perm_matrix ())
         {
           SparseMatrix sm = arg.sparse_matrix_value ();
           retval = new octave_sparse_matrix (sm);
         }
       else
	 {
	   if (use_complex) 
	     {
	       SparseComplexMatrix sm (args (0).complex_matrix_value ());
	       if (error_state) 
		 return retval;
	       retval = new octave_sparse_complex_matrix (sm);
	     } 
	   else if (use_bool) 
	     {
	       SparseBoolMatrix sm (args (0).bool_matrix_value ());
	       if (error_state) 
		 return retval;
	       retval = new octave_sparse_bool_matrix (sm);
	     } 
	   else 
	     {
	       SparseMatrix sm (args (0).matrix_value ());
	       if (error_state) 
		 return retval;
	       retval = new octave_sparse_matrix (sm);
	     }
	 }
     }
   else 
     {
       octave_idx_type m = 1, n = 1;
       if (nargin == 2) 
	 {
	   if (args(0).numel () == 1 && args(1).numel () == 1)
	     {
	       m = args(0).int_value();
	       n = args(1).int_value();
	       if (error_state) return retval;

	       if (use_complex) 
		 retval = new octave_sparse_complex_matrix 
		   (SparseComplexMatrix (m, n));
	       else if (use_bool) 
		 retval = new octave_sparse_bool_matrix 
		   (SparseBoolMatrix (m, n));
	       else
		 retval = new octave_sparse_matrix 
		   (SparseMatrix (m, n));
	     }
	   else
	     error ("sparse: expecting scalar values");
	 }
       else 
	 {
	   if (args(0).is_empty () || args (1).is_empty () 
	       || args(2).is_empty ())
	     {
	       if (nargin > 4)
		 {
		   m = args(3).int_value();
		   n = args(4).int_value();
		 }

	       if (use_bool)
		 retval = new octave_sparse_bool_matrix 
		   (SparseBoolMatrix (m, n));
	       else
		 retval = new octave_sparse_matrix (SparseMatrix (m, n));
	     }
	   else
	     {
// 
//  I use this clumsy construction so that we can use
//  any orientation of args
	       ColumnVector ridxA = ColumnVector (args(0).vector_value 
					      (false, true));
	       ColumnVector cidxA = ColumnVector (args(1).vector_value 
						  (false, true));
	       ColumnVector coefA;
	       boolNDArray coefAB;
	       ComplexColumnVector coefAC;
	       bool assemble_do_sum = true; // this is the default in matlab6

	       if (use_complex) 
		 {
		   if (args(2).is_empty ())
		     coefAC = ComplexColumnVector (0);
		   else
		     coefAC = ComplexColumnVector 
		       (args(2).complex_vector_value (false, true));
		 }
	       else if (use_bool)
		 {
		   if (args(2).is_empty ())
		     coefAB = boolNDArray (dim_vector (1, 0));
		   else
		     coefAB = args(2).bool_array_value ();
		   dim_vector AB_dims = coefAB.dims ();
		   if (AB_dims.length() > 2 || (AB_dims(0) != 1 && 
						AB_dims(1) != 1))
		     error ("sparse: vector arguments required");
		 }
	       else 
		 if (args(2).is_empty ())
		   coefA = ColumnVector (0);
		 else
		   coefA = ColumnVector (args(2).vector_value (false, true));

	       if (error_state)
		 return retval;

	       // Confirm that i,j,s all have the same number of elements
	       octave_idx_type ns;
	       if (use_complex) 
		 ns = coefAC.length();
	       else if (use_bool) 
		 ns = coefAB.length();
	       else 
		 ns = coefA.length();

	       octave_idx_type ni = ridxA.length();
	       octave_idx_type nj = cidxA.length();
	       octave_idx_type nnz = (ni > nj ? ni : nj);
	       if ((ns != 1 && ns != nnz) ||
		   (ni != 1 && ni != nnz) ||
		   (nj != 1 && nj != nnz)) 
		 {
		   error ("sparse i, j and s must have the same length");
		   return retval;
		 }

	       if (nargin == 3 || nargin == 4) 
		 {
		   m = static_cast<octave_idx_type> (ridxA.max());
		   n = static_cast<octave_idx_type> (cidxA.max());

		   // if args(3) is not string, then ignore the value
		   // otherwise check for summation or unique
		   if (nargin == 4 && args(3).is_string())
		     {
		       std::string vv= args(3).string_value();
		       if (error_state) return retval;
		       
		       if ( vv == "summation" ||
			    vv == "sum" ) 
			 assemble_do_sum = true;
		       else
			 if ( vv == "unique" )
			   assemble_do_sum = false;
			 else {
			   error("sparse repeat flag must be 'sum' or 'unique'");
			   return retval;
			 }
		     }
		 } 
	       else 
		 {
		   m = args(3).int_value();
		   n = args(4).int_value();
		   if (error_state) 
		     return retval;

		   // if args(5) is not string, then ignore the value
		   // otherwise check for summation or unique
		   if (nargin >= 6 && args(5).is_string())
		     {
		       std::string vv= args(5).string_value();
		       if (error_state) return retval;
		       
		       if ( vv == "summation" ||
			    vv == "sum" ) 
			 assemble_do_sum = true;
		       else
			 if ( vv == "unique" )
			   assemble_do_sum = false;
			 else {
			   error("sparse repeat flag must be 'sum' or 'unique'");
			   return retval;
			 }
		     }
		   
		 }

	       // Convert indexing to zero-indexing used internally
	       ridxA -= 1.;
	       cidxA -= 1.;

	       if (use_complex) 
		 retval = new octave_sparse_complex_matrix 
		   (SparseComplexMatrix (coefAC, ridxA, cidxA, m, n, 
					 assemble_do_sum));
	       else if (use_bool) 
		 retval = new octave_sparse_bool_matrix 
		   (SparseBoolMatrix (coefAB, ridxA, cidxA, m, n, 
				      assemble_do_sum));
	       else
		 retval = new octave_sparse_matrix 
		   (SparseMatrix (coefA, ridxA, cidxA, m, n, 
				  assemble_do_sum));
	     }
	 }
     }

   return retval;
}

/*
;;; Local Variables: ***
;;; mode: C++ ***
;;; End: ***
*/