view libinterp/corefcn/inv.cc @ 18961:52e01aa1fe8b

Overhaul FLTK pan, rotate, zoom * graphics.in.h: add axes properties pan, rotate3d, mouse_wheel_zoom and custom set_pan which disables rotate3d. * graphics.cc: add custom set_rotate3d and link with pan property. Disable rotate3d for 2D plots. * __init_fltk__.cc: replace gui_mode and mouse_wheel_zoom with axes properties pan, rotate3d and mouse_wheel_zoom. Disable pan for legends, move them instead. * __add_default_menu__.m: Add new menu entries for new pan and zoom modes. * findall.m: Update test for added uimenus. Each axes now has its own properties for interactive GUI control of pan, rotate3d and mouse_wheel_zoom. Now it's possible to have several figures and set pan for the 2D plot in figure x and rotate3d for the 3D plot in figure y. There are two new pan modes: "Pan x only" and "Pan y only". The toolbar buttons "P" and "R" set pan and rotate3d for the last clicked axes object or the object below the center of the canvas if none was clicked yet. The legend can now be moved with the mouse.
author Andreas Weber <andy.weber.aw@gmail.com>
date Sun, 27 Jul 2014 22:31:14 +0200
parents 9feb46ac6847
children
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/*

Copyright (C) 1996-2013 John W. Eaton

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 "defun.h"
#include "error.h"
#include "gripes.h"
#include "oct-obj.h"
#include "ops.h"
#include "ov-re-diag.h"
#include "ov-cx-diag.h"
#include "ov-flt-re-diag.h"
#include "ov-flt-cx-diag.h"
#include "ov-perm.h"
#include "utils.h"

DEFUN (inv, args, nargout,
       "-*- texinfo -*-\n\
@deftypefn  {Built-in Function} {@var{x} =} inv (@var{A})\n\
@deftypefnx {Built-in Function} {[@var{x}, @var{rcond}] =} inv (@var{A})\n\
Compute the inverse of the square matrix @var{A}.  Return an estimate\n\
of the reciprocal condition number if requested, otherwise warn of an\n\
ill-conditioned matrix if the reciprocal condition number is small.\n\
\n\
In general it is best to avoid calculating the inverse of a matrix\n\
directly.  For example, it is both faster and more accurate to solve\n\
systems of equations (@var{A}*@math{x} = @math{b}) with\n\
@code{@var{y} = @var{A} \\ @math{b}}, rather than\n\
@code{@var{y} = inv (@var{A}) * @math{b}}.\n\
\n\
If called with a sparse matrix, then in general @var{x} will be a full\n\
matrix requiring significantly more storage.  Avoid forming the inverse\n\
of a sparse matrix if possible.\n\
@seealso{ldivide, rdivide}\n\
@end deftypefn")
{
  octave_value_list retval;

  int nargin = args.length ();

  if (nargin != 1)
    {
      print_usage ();
      return retval;
    }

  octave_value arg = args(0);

  octave_idx_type nr = arg.rows ();
  octave_idx_type nc = arg.columns ();

  int arg_is_empty = empty_arg ("inverse", nr, nc);

  if (arg_is_empty < 0)
    return retval;
  else if (arg_is_empty > 0)
    return octave_value (Matrix ());

  if (nr != nc)
    {
      gripe_square_matrix_required ("inverse");
      return retval;
    }

  octave_value result;
  octave_idx_type info;
  double rcond = 0.0;
  float frcond = 0.0;
  bool isfloat = arg.is_single_type ();

  if (arg.is_diag_matrix ())
    {
      rcond = 1.0;
      frcond = 1.0f;
      if (arg.is_complex_type ())
        {
          if (isfloat)
            {
              result = arg.float_complex_diag_matrix_value ().inverse (info);
              if (nargout > 1)
                frcond = arg.float_complex_diag_matrix_value ().rcond ();
            }
          else
            {
              result = arg.complex_diag_matrix_value ().inverse (info);
              if (nargout > 1)
                rcond = arg.complex_diag_matrix_value ().rcond ();
            }
        }
      else
        {
          if (isfloat)
            {
              result = arg.float_diag_matrix_value ().inverse (info);
              if (nargout > 1)
                frcond = arg.float_diag_matrix_value ().rcond ();
            }
          else
            {
              result = arg.diag_matrix_value ().inverse (info);
              if (nargout > 1)
                rcond = arg.diag_matrix_value ().rcond ();
            }
        }
    }
  else if (arg.is_perm_matrix ())
    {
      rcond = 1.0;
      info = 0;
      result = arg.perm_matrix_value ().inverse ();
    }
  else if (isfloat)
    {
      if (arg.is_real_type ())
        {
          FloatMatrix m = arg.float_matrix_value ();
          if (! error_state)
            {
              MatrixType mattyp = args(0).matrix_type ();
              result = m.inverse (mattyp, info, frcond, 1);
              args(0).matrix_type (mattyp);
            }
        }
      else if (arg.is_complex_type ())
        {
          FloatComplexMatrix m = arg.float_complex_matrix_value ();
          if (! error_state)
            {
              MatrixType mattyp = args(0).matrix_type ();
              result = m.inverse (mattyp, info, frcond, 1);
              args(0).matrix_type (mattyp);
            }
        }
    }
  else
    {
      if (arg.is_real_type ())
        {
          if (arg.is_sparse_type ())
            {
              SparseMatrix m = arg.sparse_matrix_value ();
              if (! error_state)
                {
                  MatrixType mattyp = args(0).matrix_type ();
                  result = m.inverse (mattyp, info, rcond, 1);
                  args(0).matrix_type (mattyp);
                }
            }
          else
            {
              Matrix m = arg.matrix_value ();
              if (! error_state)
                {
                  MatrixType mattyp = args(0).matrix_type ();
                  result = m.inverse (mattyp, info, rcond, 1);
                  args(0).matrix_type (mattyp);
                }
            }
        }
      else if (arg.is_complex_type ())
        {
          if (arg.is_sparse_type ())
            {
              SparseComplexMatrix m = arg.sparse_complex_matrix_value ();
              if (! error_state)
                {
                  MatrixType mattyp = args(0).matrix_type ();
                  result = m.inverse (mattyp, info, rcond, 1);
                  args(0).matrix_type (mattyp);
                }
            }
          else
            {
              ComplexMatrix m = arg.complex_matrix_value ();
              if (! error_state)
                {
                  MatrixType mattyp = args(0).matrix_type ();
                  result = m.inverse (mattyp, info, rcond, 1);
                  args(0).matrix_type (mattyp);
                }
            }
        }
      else
        gripe_wrong_type_arg ("inv", arg);
    }

  if (! error_state)
    {
      if (nargout > 1)
        retval(1) = isfloat ? octave_value (frcond) : octave_value (rcond);

      retval(0) = result;

      bool rcond_plus_one_eq_one = false;

      if (isfloat)
        {
          volatile float xrcond = frcond;
          rcond_plus_one_eq_one = xrcond + 1.0F == 1.0F;
        }
      else
        {
          volatile double xrcond = rcond;
          rcond_plus_one_eq_one = xrcond + 1.0 == 1.0;
        }

      if (nargout < 2 && (info == -1 || rcond_plus_one_eq_one))
        warning ("inverse: matrix singular to machine precision, rcond = %g",
                 (isfloat ? frcond : rcond));
    }

  return retval;
}

/*
%!assert (inv ([1, 2; 3, 4]), [-2, 1; 1.5, -0.5], sqrt (eps))
%!assert (inv (single ([1, 2; 3, 4])), single ([-2, 1; 1.5, -0.5]), sqrt (eps ("single")))

%!error inv ()
%!error inv ([1, 2; 3, 4], 2)
%!error <argument must be a square matrix> inv ([1, 2; 3, 4; 5, 6])

%!test
%! [xinv, rcond] = inv (single ([1,2;3,4]));
%! assert (isa (xinv, 'single'));
%! assert (isa (rcond, 'single'));

%!test
%! [xinv, rcond] = inv ([1,2;3,4]);
%! assert (isa (xinv, 'double'));
%! assert (isa (rcond, 'double'));
*/

// FIXME: this should really be done with an alias, but
// alias_builtin() won't do the right thing if we are actually using
// dynamic linking.

DEFUN (inverse, args, nargout,
       "-*- texinfo -*-\n\
@deftypefn  {Built-in Function} {@var{x} =} inverse (@var{A})\n\
@deftypefnx {Built-in Function} {[@var{x}, @var{rcond}] =} inverse (@var{A})\n\
Compute the inverse of the square matrix @var{A}.\n\
\n\
This is an alias for @code{inv}.\n\
@seealso{inv}\n\
@end deftypefn")
{
  return Finv (args, nargout);
}