GNU Octave 10.1.0
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filter.cc
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1////////////////////////////////////////////////////////////////////////
2//
3// Copyright (C) 1996-2025 The Octave Project Developers
4//
5// See the file COPYRIGHT.md in the top-level directory of this
6// distribution or <https://octave.org/copyright/>.
7//
8// This file is part of Octave.
9//
10// Octave is free software: you can redistribute it and/or modify it
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21// along with Octave; see the file COPYING. If not, see
22// <https://www.gnu.org/licenses/>.
23//
24////////////////////////////////////////////////////////////////////////
25
26// Based on Tony Richardson's filter.m.
27//
28// Originally translated to C++ by KH (Kurt.Hornik@wu-wien.ac.at)
29// with help from Fritz Leisch and Andreas Weingessel on Oct 20, 1994.
30//
31// Rewritten to use templates to handle both real and complex cases by
32// jwe, Wed Nov 1 19:15:29 1995.
33
34#if defined (HAVE_CONFIG_H)
35# include "config.h"
36#endif
37
38#include "quit.h"
39
40#include "defun.h"
41#include "error.h"
42#include "ovl.h"
43
45
46template <typename T>
49 int dim = 0)
50{
51 MArray<T> y;
52
53 octave_idx_type a_len = a.numel ();
54 octave_idx_type b_len = b.numel ();
55
56 octave_idx_type ab_len = (a_len > b_len ? a_len : b_len);
57
58 // FIXME: The two lines below should be unnecessary because
59 // this template is called with a and b as column vectors
60 // already. However the a.resize line is currently (2011/04/26)
61 // necessary to stop bug #33164.
62 b.resize (dim_vector (ab_len, 1), 0.0);
63 if (a_len > 1)
64 a.resize (dim_vector (ab_len, 1), 0.0);
65
66 T norm = a (0);
67
68 if (norm == static_cast<T> (0.0))
69 error ("filter: the first element of A must be nonzero");
70
71 const dim_vector& x_dims = x.dims ();
72 if (dim < 0 || dim > x_dims.ndims ())
73 error ("filter: DIM must be a valid dimension");
74
75 octave_idx_type x_len = x_dims(dim);
76
77 const dim_vector& si_dims = si.dims ();
78 octave_idx_type si_len = si_dims(0);
79
80 if (si_len != ab_len - 1)
81 error ("filter: first dimension of SI must be of length max (length (a), length (b)) - 1");
82
83 if (si_dims.ndims () != x_dims.ndims ())
84 error ("filter: dimensionality of SI and X must agree");
85
86 for (octave_idx_type i = 1; i < dim; i++)
87 {
88 if (si_dims(i) != x_dims(i-1))
89 error ("filter: dimensionality of SI and X must agree");
90 }
91 for (octave_idx_type i = dim+1; i < x_dims.ndims (); i++)
92 {
93 if (si_dims(i) != x_dims(i))
94 error ("filter: dimensionality of SI and X must agree");
95 }
96
97 if (x_len == 0)
98 return x;
99
100 if (norm != static_cast<T> (1.0))
101 {
102 a /= norm;
103 b /= norm;
104 }
105
106 if (a_len <= 1 && si_len <= 0)
107 return b(0) * x;
108
109 // Here onwards, either a_len > 1 or si_len >= 1 or both.
110
111 y.resize (x_dims, 0.0);
112
113 octave_idx_type x_stride = 1;
114 for (int i = 0; i < dim; i++)
115 x_stride *= x_dims(i);
116
117 octave_idx_type x_num = x_dims.numel () / x_len;
118 // For deconv and fftfilt, x_num seems to always be 1.
119 // For directly calling filter, it can be more than 1.
120
121 for (octave_idx_type num = 0; num < x_num; num++)
122 {
123 octave_idx_type x_offset = (x_stride == 1) ? num * x_len
124 : num + (num / x_stride) * x_stride * (x_len - 1);
125
126 octave_idx_type si_offset = num * si_len;
127
128 // Try to achieve a balance between speed and interruptibility.
129 //
130 // One extreme is to not check for interruptions at all, which gives
131 // good speed but the user cannot use Ctrl-C for the whole duration.
132 // The other end is to check frequently from inside an inner loop,
133 // which slows down performance by 5X or 6X.
134 //
135 // Putting any sort of check in an inner loop seems to prevent the
136 // compiler from optimizing the loop, so we cannot say "check for
137 // interruptions every M iterations" using an if-statement.
138 //
139 // This is a compromise approach to split the total numer of loop
140 // executions into num_outer and num_inner, to provide periodic checks
141 // for interruptions without writing a conditional inside a tight loop.
142 //
143 // To make it more interruptible and run more slowly, reduce num_inner.
144 // To speed it up but make it less interruptible, increase it.
145 // May need to increase it slowly over time as computers get faster.
146 // The aim is to not lose Ctrl-C ability for longer than about 2 seconds.
147 //
148 // In December 2021, num_inner = 100000 is acceptable.
149
150 octave_idx_type num_execs = si_len-1; // 0 to num_execs-1
151 octave_idx_type num_inner = 100000;
152 octave_idx_type num_outer = num_execs / num_inner;
153
154 // The following if-else block depends on a_len and si_len,
155 // both of which are loop invariants in this 0 <= num < x_num loop.
156 // But x_num is so small in practice that using the if-else inside
157 // the loop has more benefits than duplicating the outer for-loop,
158 // even though the checks are on loop invariants.
159
160 // We cannot have a_len <= 1 AND si_len <= 0 because that case already
161 // returned above. This means exactly one of the following blocks
162 // inside the if-conditional will be obeyed: it is not possible for the
163 // if-block and the else-block to *both* skip. Therefore any code that
164 // is common to both branches can be pulled out here without affecting
165 // correctness or speed.
166
167 T *py = y.rwdata ();
168 T *psi = si.rwdata ();
169 const T *pb = b.data ();
170 const T *px = x.data ();
171 psi += si_offset;
172
173 if (a_len > 1)
174 {
175 const T *pa = a.data ();
176
177 // Usually the last element to be written will be si_len-1
178 // but if si_len is 0, then we need the 0th element to be written.
179 // Pulling this check out of the for-loop makes it run faster.
180 octave_idx_type iidx = (si_len > 0) ? si_len-1 : 0;
181
182 for (octave_idx_type i = 0, idx = x_offset;
183 i < x_len;
184 i++, idx += x_stride)
185 {
186 py[idx] = psi[0] + pb[0] * px[idx];
187
188 // Outer and inner loops for interruption management
189 for (octave_idx_type u = 0; u <= num_outer; u++)
190 {
191 octave_idx_type lo = u * num_inner;
192 octave_idx_type hi = (lo + num_inner < num_execs-1)
193 ? lo + num_inner : num_execs-1;
194
195 // Inner loop, no interruption
196 for (octave_idx_type j = lo; j <= hi; j++)
197 psi[j] = psi[j+1] - pa[j+1] * py[idx] + pb[j+1] * px[idx];
198
199 octave_quit(); // Check for interruptions
200 }
201
202 psi[iidx] = pb[si_len] * px[idx] - pa[si_len] * py[idx];
203 }
204 }
205 else // a_len <= 1 ==> si_len MUST be > 0
206 {
207 // This else-block is almost the same as the above if-block,
208 // except for the absence of variable pa.
209
210 for (octave_idx_type i = 0, idx = x_offset;
211 i < x_len;
212 i++, idx += x_stride)
213 {
214 py[idx] = psi[0] + pb[0] * px[idx];
215
216 // Outer and inner loops for interruption management
217 for (octave_idx_type u = 0; u <= num_outer; u++)
218 {
219 octave_idx_type lo = u * num_inner;
220 octave_idx_type hi = (lo + num_inner < num_execs-1)
221 ? lo + num_inner : num_execs-1;
222
223 // Inner loop, no interruption
224 for (octave_idx_type j = lo; j <= hi; j++)
225 psi[j] = psi[j+1] + pb[j+1] * px[idx];
226
227 octave_quit(); // Check for interruptions
228 }
229
230 psi[si_len-1] = pb[si_len] * px[idx];
231 }
232 }
233 }
234
235 return y;
236}
237
238template <typename T>
240filter (MArray<T>& b, MArray<T>& a, MArray<T>& x, int dim = -1)
241{
242 const dim_vector& x_dims = x.dims ();
243
244 if (dim < 0)
245 dim = x_dims.first_non_singleton ();
246 else if (dim > x_dims.ndims ())
247 error ("filter: DIM must be a valid dimension");
248
249 octave_idx_type a_len = a.numel ();
250 octave_idx_type b_len = b.numel ();
251
252 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1;
253 dim_vector si_dims = x.dims ();
254 for (int i = dim; i > 0; i--)
255 si_dims(i) = si_dims(i-1);
256 si_dims(0) = si_len;
257
258 MArray<T> si (si_dims, T (0.0));
259
260 return filter (b, a, x, si, dim);
261}
262
263DEFUN (filter, args, ,
264 doc: /* -*- texinfo -*-
265@deftypefn {} {@var{y} =} filter (@var{b}, @var{a}, @var{x})
266@deftypefnx {} {[@var{y}, @var{sf}] =} filter (@var{b}, @var{a}, @var{x}, @var{si})
267@deftypefnx {} {[@var{y}, @var{sf}] =} filter (@var{b}, @var{a}, @var{x}, [], @var{dim})
268@deftypefnx {} {[@var{y}, @var{sf}] =} filter (@var{b}, @var{a}, @var{x}, @var{si}, @var{dim})
269Apply a 1-D digital filter to the data @var{x}.
270
271@code{filter} returns the solution to the following linear, time-invariant
272difference equation:
273@tex
274$$
275\sum_{k=0}^N a_{k+1} y_{n-k} = \sum_{k=0}^M b_{k+1} x_{n-k}, \qquad
276 1 \le n \le P
277$$
278@end tex
279@ifnottex
280@c Set example in small font to prevent overfull line
281
282@smallexample
283@group
284 N M
285SUM a(k+1) y(n-k) = SUM b(k+1) x(n-k) for 1<=n<=length(x)
286k=0 k=0
287@end group
288@end smallexample
289
290@end ifnottex
291
292@noindent
293where
294@ifnottex
295N=length(a)-1 and M=length(b)-1.
296@end ifnottex
297@tex
298$a \in \Re^{N-1}$, $b \in \Re^{M-1}$, and $x \in \Re^P$.
299@end tex
300The result is calculated over the first non-singleton dimension of @var{x}
301or over @var{dim} if supplied.
302
303An equivalent form of the equation is:
304@tex
305$$
306y_n = -\sum_{k=1}^N c_{k+1} y_{n-k} + \sum_{k=0}^M d_{k+1} x_{n-k}, \qquad
307 1 \le n \le P
308$$
309@end tex
310@ifnottex
311@c Set example in small font to prevent overfull line
312
313@smallexample
314@group
315 N M
316y(n) = - SUM c(k+1) y(n-k) + SUM d(k+1) x(n-k) for 1<=n<=length(x)
317 k=1 k=0
318@end group
319@end smallexample
320
321@end ifnottex
322
323@noindent
324where
325@ifnottex
326 c = a/a(1) and d = b/a(1).
327@end ifnottex
328@tex
329$c = a/a_1$ and $d = b/a_1$.
330@end tex
331
332If the fourth argument @var{si} is provided, it is taken as the
333initial state of the system and the final state is returned as
334@var{sf}. The state vector is a column vector whose length is
335equal to the length of the longest coefficient vector minus one.
336If @var{si} is not supplied, the initial state vector is set to all
337zeros.
338
339In terms of the Z Transform, @var{y} is the result of passing the
340discrete-time signal @var{x} through a system characterized by the following
341rational system function:
342@tex
343$$
344H(z) = {\displaystyle\sum_{k=0}^M d_{k+1} z^{-k}
345 \over 1 + \displaystyle\sum_{k+1}^N c_{k+1} z^{-k}}
346$$
347@end tex
348@ifnottex
349
350@example
351@group
352 M
353 SUM d(k+1) z^(-k)
354 k=0
355H(z) = ---------------------
356 N
357 1 + SUM c(k+1) z^(-k)
358 k=1
359@end group
360@end example
361
362@end ifnottex
363@seealso{filter2, fftfilt, freqz}
364@end deftypefn */)
365{
366 int nargin = args.length ();
367
368 if (nargin < 3 || nargin > 5)
369 print_usage ();
370
371 int dim;
372 const dim_vector& x_dims = args(2).dims ();
373
374 if (nargin == 5)
375 {
376 dim = args(4).strict_int_value () - 1;
377 if (dim < 0 || dim >= x_dims.ndims ())
378 error ("filter: DIM must be a valid dimension");
379 }
380 else
381 dim = x_dims.first_non_singleton ();
382
383 octave_value_list retval;
384
385 const char *a_b_errmsg = "filter: A and B must be vectors";
386 const char *x_si_errmsg = "filter: X and SI must be arrays";
387
388 bool isfloat = (args(0).is_single_type ()
389 || args(1).is_single_type ()
390 || args(2).is_single_type ()
391 || (nargin >= 4 && args(3).is_single_type ()));
392
393 if (args(0).iscomplex ()
394 || args(1).iscomplex ()
395 || args(2).iscomplex ()
396 || (nargin >= 4 && args(3).iscomplex ()))
397 {
398 if (isfloat)
399 {
400 FloatComplexColumnVector b = args(0).xfloat_complex_vector_value (a_b_errmsg);
401 FloatComplexColumnVector a = args(1).xfloat_complex_vector_value (a_b_errmsg);
402 FloatComplexNDArray x = args(2).xfloat_complex_array_value (x_si_errmsg);
403
405
406 if (nargin == 3 || args(3).isempty ())
407 {
408 octave_idx_type a_len = a.numel ();
409 octave_idx_type b_len = b.numel ();
410
411 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1;
412
413 dim_vector si_dims = x.dims ();
414 for (int i = dim; i > 0; i--)
415 si_dims(i) = si_dims(i-1);
416 si_dims(0) = si_len;
417
418 si.resize (si_dims, 0.0);
419 }
420 else
421 {
422 si = args(3).xfloat_complex_array_value (x_si_errmsg);
423
424 if (si.isvector () && x.isvector ())
425 si = si.reshape (dim_vector (si.numel (), 1));
426 }
427
428 FloatComplexNDArray y (filter (b, a, x, si, dim));
429
430 retval = ovl (y, si);
431 }
432 else
433 {
434 ComplexColumnVector b = args(0).xcomplex_vector_value (a_b_errmsg);
435 ComplexColumnVector a = args(1).xcomplex_vector_value (a_b_errmsg);
436
437 ComplexNDArray x = args(2).xcomplex_array_value (x_si_errmsg);
438
440
441 if (nargin == 3 || args(3).isempty ())
442 {
443 octave_idx_type a_len = a.numel ();
444 octave_idx_type b_len = b.numel ();
445
446 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1;
447
448 dim_vector si_dims = x.dims ();
449 for (int i = dim; i > 0; i--)
450 si_dims(i) = si_dims(i-1);
451 si_dims(0) = si_len;
452
453 si.resize (si_dims, 0.0);
454 }
455 else
456 {
457 si = args(3).xcomplex_array_value (x_si_errmsg);
458
459 if (si.isvector () && x.isvector ())
460 si = si.reshape (dim_vector (si.numel (), 1));
461 }
462
463 ComplexNDArray y (filter (b, a, x, si, dim));
464
465 retval = ovl (y, si);
466 }
467 }
468 else
469 {
470 if (isfloat)
471 {
472 FloatColumnVector b = args(0).xfloat_vector_value (a_b_errmsg);
473 FloatColumnVector a = args(1).xfloat_vector_value (a_b_errmsg);
474
475 FloatNDArray x = args(2).xfloat_array_value (x_si_errmsg);
476
477 FloatNDArray si;
478
479 if (nargin == 3 || args(3).isempty ())
480 {
481 octave_idx_type a_len = a.numel ();
482 octave_idx_type b_len = b.numel ();
483
484 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1;
485
486 dim_vector si_dims = x.dims ();
487 for (int i = dim; i > 0; i--)
488 si_dims(i) = si_dims(i-1);
489 si_dims(0) = si_len;
490
491 si.resize (si_dims, 0.0);
492 }
493 else
494 {
495 si = args(3).xfloat_array_value (x_si_errmsg);
496
497 if (si.isvector () && x.isvector ())
498 si = si.reshape (dim_vector (si.numel (), 1));
499 }
500
501 FloatNDArray y (filter (b, a, x, si, dim));
502
503 retval = ovl (y, si);
504 }
505 else
506 {
507 ColumnVector b = args(0).xvector_value (a_b_errmsg);
508 ColumnVector a = args(1).xvector_value (a_b_errmsg);
509
510 NDArray x = args(2).xarray_value (x_si_errmsg);
511
512 NDArray si;
513
514 if (nargin == 3 || args(3).isempty ())
515 {
516 octave_idx_type a_len = a.numel ();
517 octave_idx_type b_len = b.numel ();
518
519 octave_idx_type si_len = (a_len > b_len ? a_len : b_len) - 1;
520
521 dim_vector si_dims = x.dims ();
522 for (int i = dim; i > 0; i--)
523 si_dims(i) = si_dims(i-1);
524 si_dims(0) = si_len;
525
526 si.resize (si_dims, 0.0);
527 }
528 else
529 {
530 si = args(3).xarray_value (x_si_errmsg);
531
532 if (si.isvector () && x.isvector ())
533 si = si.reshape (dim_vector (si.numel (), 1));
534 }
535
536 NDArray y (filter (b, a, x, si, dim));
537
538 retval = ovl (y, si);
539 }
540 }
541
542 return retval;
543}
544
545template MArray<double>
547 MArray<double>&, int dim);
548
549template MArray<double>
551
552template MArray<Complex>
554 MArray<Complex>&, int dim);
555
556template MArray<Complex>
558
559template MArray<float>
561 MArray<float>&, int dim);
562
563template MArray<float>
565
568 MArray<FloatComplex>&, int dim);
569
572 int dim);
573
574/*
575%!shared a, b, x, r
576%!test
577%! a = [1 1];
578%! b = [1 1];
579%! x = zeros (1,10); x(1) = 1;
580%! assert (filter (b, [1], x ), [1 1 0 0 0 0 0 0 0 0]);
581%! assert (filter (b, [1], x.'), [1 1 0 0 0 0 0 0 0 0].');
582%! assert (filter (b.', [1], x ), [1 1 0 0 0 0 0 0 0 0] );
583%! assert (filter (b.', [1], x.'), [1 1 0 0 0 0 0 0 0 0].');
584%! assert (filter ([1], a, x ), [+1 -1 +1 -1 +1 -1 +1 -1 +1 -1] );
585%! assert (filter ([1], a, x.'), [+1 -1 +1 -1 +1 -1 +1 -1 +1 -1].');
586%! assert (filter ([1], a.', x ), [+1 -1 +1 -1 +1 -1 +1 -1 +1 -1] );
587%! assert (filter ([1], a.', x.'), [+1 -1 +1 -1 +1 -1 +1 -1 +1 -1].');
588%! assert (filter (b, a, x ), [1 0 0 0 0 0 0 0 0 0] );
589%! assert (filter (b.', a, x ), [1 0 0 0 0 0 0 0 0 0] );
590%! assert (filter (b, a.', x ), [1 0 0 0 0 0 0 0 0 0] );
591%! assert (filter (b.', a, x ), [1 0 0 0 0 0 0 0 0 0] );
592%! assert (filter (b, a, x.'), [1 0 0 0 0 0 0 0 0 0].');
593%! assert (filter (b.', a, x.'), [1 0 0 0 0 0 0 0 0 0].');
594%! assert (filter (b, a.', x.'), [1 0 0 0 0 0 0 0 0 0].');
595%! assert (filter (b.', a, x.'), [1 0 0 0 0 0 0 0 0 0].');
596
597%!test
598%! r = sqrt (1/2) * (1+i);
599%! a = a*r;
600%! b = b*r;
601%! assert (filter (b, [1], x ), r*[1 1 0 0 0 0 0 0 0 0] );
602%! assert (filter (b, [1], r*x ), r*r*[1 1 0 0 0 0 0 0 0 0] );
603%! assert (filter (b, [1], x.' ), r*[1 1 0 0 0 0 0 0 0 0].' );
604%! assert (filter (b, a, x ), [1 0 0 0 0 0 0 0 0 0], eps);
605%! assert (filter (b, a, r*x ), r*[1 0 0 0 0 0 0 0 0 0], eps);
606
607%!shared a, b, x, y, so
608%!test
609%! a = [1,1];
610%! b = [1,1];
611%! x = zeros (1,10); x(1) = 1;
612%! [y, so] = filter (b, [1], x, [-1]);
613%! assert (y, [0 1 0 0 0 0 0 0 0 0]);
614%! assert (so, 0);
615
616%!test
617%! x = zeros (10,3); x(1,1) = -1; x(1,2) = 1;
618%! y0 = zeros (10,3); y0(1:2,1) = -1; y0(1:2,2) = 1;
619%! y = filter (b, [1], x);
620%! assert (y, y0);
621
622%!test
623%! a = [1,1];
624%! b=[1,1];
625%! x = zeros (4,4,2); x(1,1:4,1) = +1; x(1,1:4,2) = -1;
626%! y0 = zeros (4,4,2); y0(1:2,1:4,1) = +1; y0(1:2,1:4,2) = -1;
627%! y = filter (b, [1], x);
628%! assert (y, y0);
629
630%!assert (filter (1, ones (10,1) / 10, []), [])
631%!assert (filter (1, ones (10,1) / 10, zeros (0,10)), zeros (0,10))
632%!assert (filter (1, ones (10,1) / 10, single (1:5)),
633%! repmat (single (10), 1, 5))
634
635## Test using initial conditions
636%!assert (filter ([1, 1, 1], [1, 1], [1 2], [1, 1]), [2 2])
637%!assert (filter ([1, 1, 1], [1, 1], [1 2], [1, 1]'), [2 2])
638%!assert (filter ([1, 3], [1], [1 2; 3 4; 5 6], [4, 5]), [5 7; 6 10; 14 18])
639%!error filter ([1, 3], [1], [1 2; 3 4; 5 6], [4, 5]')
640%!assert (filter ([1, 3, 2], [1], [1 2; 3 4; 5 6], [1 0 0; 1 0 0], 2),
641%! [2 6; 3 13; 5 21])
642
643## Test of DIM parameter
644%!test
645%! x = ones (2, 1, 3, 4);
646%! x(1,1,:,:) = [1 2 3 4; 5 6 7 8; 9 10 11 12];
647%! y0 = [1 1 6 2 15 3 2 1 8 2 18 3 3 1 10 2 21 3 4 1 12 2 24 3];
648%! y0 = reshape (y0, size (x));
649%! y = filter ([1 1 1], 1, x, [], 3);
650%! assert (y, y0);
651*/
652
653OCTAVE_END_NAMESPACE(octave)
const dim_vector & dims() const
Return a const-reference so that dims ()(i) works efficiently.
Definition Array.h:507
bool isvector() const
Size of the specified dimension.
Definition Array.h:655
void resize(const dim_vector &dv, const T &rfv)
Size of the specified dimension.
const T * data() const
Size of the specified dimension.
Definition Array.h:665
T * rwdata()
Size of the specified dimension.
octave_idx_type numel() const
Number of elements in the array.
Definition Array.h:418
Template for N-dimensional array classes with like-type math operators.
Definition MArray.h:61
MArray< T > reshape(const dim_vector &new_dims) const
Definition MArray.h:85
Vector representing the dimensions (size) of an Array.
Definition dim-vector.h:90
octave_idx_type numel(int n=0) const
Number of elements that a matrix with this dimensions would have.
Definition dim-vector.h:331
octave_idx_type ndims() const
Number of dimensions.
Definition dim-vector.h:253
int first_non_singleton(int def=0) const
Definition dim-vector.h:440
OCTAVE_BEGIN_NAMESPACE(octave) static octave_value daspk_fcn
void print_usage()
Definition defun-int.h:72
#define DEFUN(name, args_name, nargout_name, doc)
Macro to define a builtin function.
Definition defun.h:56
void error(const char *fmt,...)
Definition error.cc:1003
MArray< T > filter(MArray< T > &b, MArray< T > &a, MArray< T > &x, MArray< T > &si, int dim=0)
Definition filter.cc:48
double norm(const ColumnVector &v)
Definition graphics.cc:5778
F77_RET_T const F77_DBLE * x
double psi(double z)
octave_value_list ovl(const OV_Args &... args)
Construct an octave_value_list with less typing.
Definition ovl.h:217