view libinterp/corefcn/fftn.cc @ 20500:44eb1102f8a8

don't recycle scanf format string if all conversions are done (bug #45808) * oct-stream.cc, oct-stream.h (scanf_format_elt::special_conversion): New enum value, no_conversion. (scanf_format_list::next): If not cycling through the list, return dummy scanf_format_elt after list has been exhausted. (octave_base_stream::do_scanf): Only cycle through the format list more than once if there are conversions to make and the limit on the number of values to convert has not been reached.
author John W. Eaton <jwe@octave.org>
date Wed, 26 Aug 2015 16:05:49 -0400
parents 4f45eaf83908
children f90c8372b7ba
line wrap: on
line source

/*

Copyright (C) 2004-2015 David Bateman

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 "lo-mappers.h"

#include "defun.h"
#include "error.h"
#include "gripes.h"
#include "oct-obj.h"
#include "utils.h"

// This function should be merged with Fifft.

#if defined (HAVE_FFTW)
#define FFTSRC "@sc{fftw}"
#else
#define FFTSRC "@sc{fftpack}"
#endif

static octave_value
do_fftn (const octave_value_list &args, const char *fcn, int type)
{
  octave_value retval;

  int nargin = args.length ();

  if (nargin < 1 || nargin > 2)
    {
      print_usage ();
      return retval;
    }

  octave_value arg = args(0);
  dim_vector dims = arg.dims ();

  for (int i = 0; i < dims.length (); i++)
    if (dims(i) < 0)
      return retval;

  if (nargin > 1)
    {
      Matrix val = args(1).matrix_value ();
      if (val.rows () > val.columns ())
        val = val.transpose ();

      if (error_state || val.columns () != dims.length () || val.rows () != 1)
        error ("%s: SIZE must be a vector of length dim", fcn);
      else
        {
          for (int i = 0; i < dims.length (); i++)
            {
              if (xisnan (val(i,0)))
                error ("%s: SIZE has invalid NaN entries", fcn);
              else if (NINTbig (val(i,0)) < 0)
                error ("%s: all dimensions in SIZE must be greater than zero",
                       fcn);
              else
                {
                  dims(i) = NINTbig(val(i,0));
                }
            }
        }
    }

  if (error_state)
    return retval;

  if (dims.all_zero ())
    {
      if (arg.is_single_type ())
        return octave_value (FloatMatrix ());
      else
        return octave_value (Matrix ());
    }

  if (arg.is_single_type ())
    {
      if (arg.is_real_type ())
        {
          FloatNDArray nda = arg.float_array_value ();

          if (! error_state)
            {
              nda.resize (dims, 0.0);
              retval = (type != 0 ? nda.ifourierNd () : nda.fourierNd ());
            }
        }
      else
        {
          FloatComplexNDArray cnda = arg.float_complex_array_value ();

          if (! error_state)
            {
              cnda.resize (dims, 0.0);
              retval = (type != 0 ? cnda.ifourierNd () : cnda.fourierNd ());
            }
        }
    }
  else
    {
      if (arg.is_real_type ())
        {
          NDArray nda = arg.array_value ();

          if (! error_state)
            {
              nda.resize (dims, 0.0);
              retval = (type != 0 ? nda.ifourierNd () : nda.fourierNd ());
            }
        }
      else if (arg.is_complex_type ())
        {
          ComplexNDArray cnda = arg.complex_array_value ();

          if (! error_state)
            {
              cnda.resize (dims, 0.0);
              retval = (type != 0 ? cnda.ifourierNd () : cnda.fourierNd ());
            }
        }
      else
        {
          gripe_wrong_type_arg (fcn, arg);
        }
    }

  return retval;
}

DEFUN (fftn, args, ,
       "-*- texinfo -*-\n\
@deftypefn  {Built-in Function} {} fftn (@var{A})\n\
@deftypefnx {Built-in Function} {} fftn (@var{A}, @var{size})\n\
Compute the N-dimensional discrete Fourier transform of @var{A} using\n\
a Fast Fourier Transform (FFT) algorithm.\n\
\n\
The optional vector argument @var{size} may be used specify the dimensions\n\
of the array to be used.  If an element of @var{size} is smaller than the\n\
corresponding dimension of @var{A}, then the dimension of @var{A} is\n\
truncated prior to performing the FFT@.  Otherwise, if an element of\n\
@var{size} is larger than the corresponding dimension then @var{A} is\n\
resized and padded with zeros.\n\
@seealso{ifftn, fft, fft2, fftw}\n\
@end deftypefn")
{
  return do_fftn (args, "fftn", 0);
}

DEFUN (ifftn, args, ,
       "-*- texinfo -*-\n\
@deftypefn  {Built-in Function} {} ifftn (@var{A})\n\
@deftypefnx {Built-in Function} {} ifftn (@var{A}, @var{size})\n\
Compute the inverse N-dimensional discrete Fourier transform of @var{A}\n\
using a Fast Fourier Transform (FFT) algorithm.\n\
\n\
The optional vector argument @var{size} may be used specify the dimensions\n\
of the array to be used.  If an element of @var{size} is smaller than the\n\
corresponding dimension of @var{A}, then the dimension of @var{A} is\n\
truncated prior to performing the inverse FFT@.  Otherwise, if an element of\n\
@var{size} is larger than the corresponding dimension then @var{A} is\n\
resized and padded with zeros.\n\
@seealso{fftn, ifft, ifft2, fftw}\n\
@end deftypefn")
{
  return do_fftn (args, "ifftn", 1);
}