Mercurial > hg > octave-nkf
view libinterp/corefcn/fftn.cc @ 20759:eb9e2d187ed2
maint: Use Octave coding conventions in scripts/ode/private dir.
* AbsRel_Norm.m, fuzzy_compare.m, hermite_quartic_interpolation.m,
integrate_adaptive.m, integrate_const.m, integrate_n_steps.m, kahan.m,
ode_struct_value_check.m, odepkg_event_handle.m, odepkg_structure_check.m,
runge_kutta_45_dorpri.m, starting_stepsize.m:
Wrap long lines to < 80 chars.
Use double quotes rather than single quotes where possible.
Use ';' at end of keywords "return;" and "break;"
Use '##" for stand-alone comments and '#' for end-of-line comments.
Use two spaces after period before starting new sentence.
Use '!' instead of '~' for logical negation.
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author | Rik <rik@octave.org> |
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date | Sun, 04 Oct 2015 22:18:54 -0700 |
parents | 4f45eaf83908 |
children | f90c8372b7ba |
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/* 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); }