Mercurial > octave-nkf
view src/DLD-FUNCTIONS/__convn__.cc @ 7648:e7b999840056
Added tests to scripts/polynomial/convn.m and allow '__convn__' to actually get N-dimensional complex data.
author | sh@sh-laptop |
---|---|
date | Wed, 26 Mar 2008 15:55:20 -0400 |
parents | 3398ce778b4b |
children | 5f6e11567f70 |
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/* Copyright (C) 2008 Soren Hauberg 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 <algorithm> #include "dNDArray.h" #include "CNDArray.h" #include "defun-dld.h" // FIXME -- this function should maybe be available in liboctave? template <class MT, class ST> octave_value convn (const MT& a, const MT& b) { octave_value retval; // Get sizes const octave_idx_type ndims = a.ndims (); const octave_idx_type b_numel = b.numel (); const dim_vector a_size = a.dims (); const dim_vector b_size = b.dims (); if (ndims != b.ndims ()) { error ("__convn__: first and second argument must have same dimensionality"); return retval; } // Allocate output dim_vector out_size (a_size); for (octave_idx_type n = 0; n < ndims; n++) out_size(n) = std::max (a_size(n) - b_size(n) + 1, 0); MT out = MT (out_size); const octave_idx_type out_numel = out.numel (); // Iterate over every element of 'out'. dim_vector idx_dim (ndims); Array<octave_idx_type> a_idx (idx_dim); Array<octave_idx_type> b_idx (idx_dim); Array<octave_idx_type> out_idx (idx_dim, 0); for (octave_idx_type i = 0; i < out_numel; i++) { OCTAVE_QUIT; // For each neighbour ST sum = 0; for (octave_idx_type n = 0; n < ndims; n++) b_idx(n) = 0; for (octave_idx_type j = 0; j < b_numel; j++) { for (octave_idx_type n = 0; n < ndims; n++) a_idx(n) = out_idx(n) + (b_size(n) - 1 - b_idx(n)); sum += a(a_idx) * b(b_idx); b.increment_index (b_idx, b_size); } // Compute filter result out(out_idx) = sum; // Prepare for next iteration out.increment_index (out_idx, out_size); } return out; } DEFUN_DLD (__convn__, args, , "-*- texinfo -*-\n\ @deftypefn {Loadable Function} {} __convn__(@var{a}, @var{b})\n\ Undocumented internal function.\n\ @end deftypefn\n\ ") { octave_value retval; if (args.length () == 2) { if (args(0).is_real_type () && args(1).is_real_type ()) { const NDArray a = args (0).array_value (); const NDArray b = args (1).array_value (); if (! error_state) retval = convn<NDArray, double> (a, b); } else if (args(0).is_complex_type () && args(1).is_complex_type ()) { const ComplexNDArray a = args (0).complex_array_value (); const ComplexNDArray b = args (1).complex_array_value (); if (! error_state) retval = convn<ComplexNDArray, Complex> (a, b); } else error ("__convn__: first and second input should be real, or complex arrays"); } else print_usage (); return retval; }