GNU Octave  8.1.0
A high-level interpreted language, primarily intended for numerical computations, mostly compatible with Matlab
conv2.cc
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25 
26 #if defined (HAVE_CONFIG_H)
27 # include "config.h"
28 #endif
29 
30 #include "oct-convn.h"
31 
32 #include "defun.h"
33 #include "error.h"
34 #include "ovl.h"
35 #include "utils.h"
36 
37 OCTAVE_BEGIN_NAMESPACE(octave)
38 
39 enum Shape { SHAPE_FULL, SHAPE_SAME, SHAPE_VALID };
40 
41 DEFUN (conv2, args, ,
42  doc: /* -*- texinfo -*-
43 @deftypefn {} {@var{C} =} conv2 (@var{A}, @var{B})
44 @deftypefnx {} {@var{C} =} conv2 (@var{v1}, @var{v2}, @var{m})
45 @deftypefnx {} {@var{C} =} conv2 (@dots{}, @var{shape})
46 Return the 2-D convolution of @var{A} and @var{B}.
47 
48 The size of the result is determined by the optional @var{shape} argument
49 which takes the following values
50 
51 @table @asis
52 @item @var{shape} = @qcode{"full"}
53 Return the full convolution. (default)
54 
55 @item @var{shape} = @qcode{"same"}
56 Return the central part of the convolution with the same size as @var{A}.
57 The central part of the convolution begins at the indices
58 @code{floor ([size(@var{B})/2] + 1)}.
59 
60 @item @var{shape} = @qcode{"valid"}
61 Return only the parts which do not include zero-padded edges.
62 The size of the result is @code{max (size (A) - size (B) + 1, 0)}.
63 @end table
64 
65 When the third argument is a matrix, return the convolution of the matrix
66 @var{m} by the vector @var{v1} in the column direction and by the vector
67 @var{v2} in the row direction.
68 @seealso{conv, convn}
69 @end deftypefn */)
70 {
71  int nargin = args.length ();
72 
73  if (nargin < 2 || nargin > 4)
74  print_usage ();
75 
76  std::string shape = "full"; // default
77  bool separable = false;
78  convn_type ct = convn_full;
79 
80  if (nargin == 3)
81  {
82  if (args(2).is_string ())
83  shape = args(2).string_value ();
84  else
85  separable = true;
86  }
87  else if (nargin == 4)
88  {
89  separable = true;
90  shape = args(3).string_value ();
91  }
92 
93  if (args(0).ndims () > 2 || args(1).ndims () > 2)
94  error ("conv2: A and B must be 1-D vectors or 2-D matrices");
95 
96  if (shape == "full")
97  ct = convn_full;
98  else if (shape == "same")
99  ct = convn_same;
100  else if (shape == "valid")
101  ct = convn_valid;
102  else
103  error ("conv2: SHAPE type not valid");
104 
105  octave_value retval;
106 
107  if (separable)
108  {
109  // If user requests separable, check first two params are vectors
110  if (! (1 == args(0).rows () || 1 == args(0).columns ())
111  || ! (1 == args(1).rows () || 1 == args(1).columns ()))
112  error ("conv2: arguments must be vectors for separable option");
113 
114  if (args(0).is_single_type () || args(1).is_single_type ()
115  || args(2).is_single_type ())
116  {
117  if (args(0).iscomplex () || args(1).iscomplex ()
118  || args(2).iscomplex ())
119  {
120  FloatComplexMatrix a (args(2).float_complex_matrix_value ());
121  if (args(1).isreal () && args(2).isreal ())
122  {
123  FloatColumnVector v1 (args(0).float_vector_value ());
124  FloatRowVector v2 (args(1).float_vector_value ());
125  retval = convn (a, v1, v2, ct);
126  }
127  else
128  {
129  FloatComplexColumnVector v1 (args(0).float_complex_vector_value ());
130  FloatComplexRowVector v2 (args(1).float_complex_vector_value ());
131  retval = convn (a, v1, v2, ct);
132  }
133  }
134  else
135  {
136  FloatColumnVector v1 (args(0).float_vector_value ());
137  FloatRowVector v2 (args(1).float_vector_value ());
138  FloatMatrix a (args(2).float_matrix_value ());
139  retval = convn (a, v1, v2, ct);
140  }
141  }
142  else
143  {
144  if (args(0).iscomplex () || args(1).iscomplex ()
145  || args(2).iscomplex ())
146  {
147  ComplexMatrix a (args(2).complex_matrix_value ());
148  if (args(1).isreal () && args(2).isreal ())
149  {
150  ColumnVector v1 (args(0).vector_value ());
151  RowVector v2 (args(1).vector_value ());
152  retval = convn (a, v1, v2, ct);
153  }
154  else
155  {
156  ComplexColumnVector v1 (args(0).complex_vector_value ());
157  ComplexRowVector v2 (args(1).complex_vector_value ());
158  retval = convn (a, v1, v2, ct);
159  }
160  }
161  else
162  {
163  ColumnVector v1 (args(0).vector_value ());
164  RowVector v2 (args(1).vector_value ());
165  Matrix a (args(2).matrix_value ());
166  retval = convn (a, v1, v2, ct);
167  }
168  }
169  } // if (separable)
170  else
171  {
172  if (args(0).is_single_type () || args(1).is_single_type ())
173  {
174  if (args(0).iscomplex () || args(1).iscomplex ())
175  {
176  FloatComplexMatrix a (args(0).float_complex_matrix_value ());
177  if (args(1).isreal ())
178  {
179  FloatMatrix b (args(1).float_matrix_value ());
180  retval = convn (a, b, ct);
181  }
182  else
183  {
184  FloatComplexMatrix b (args(1).float_complex_matrix_value ());
185  retval = convn (a, b, ct);
186  }
187  }
188  else
189  {
190  FloatMatrix a (args(0).float_matrix_value ());
191  FloatMatrix b (args(1).float_matrix_value ());
192  retval = convn (a, b, ct);
193  }
194  }
195  else
196  {
197  if (args(0).iscomplex () || args(1).iscomplex ())
198  {
199  ComplexMatrix a (args(0).complex_matrix_value ());
200  if (args(1).isreal ())
201  {
202  Matrix b (args(1).matrix_value ());
203  retval = convn (a, b, ct);
204  }
205  else
206  {
207  ComplexMatrix b (args(1).complex_matrix_value ());
208  retval = convn (a, b, ct);
209  }
210  }
211  else
212  {
213  Matrix a (args(0).matrix_value ());
214  Matrix b (args(1).matrix_value ());
215  retval = convn (a, b, ct);
216  }
217  }
218 
219  } // if (separable)
220 
221  return retval;
222 }
223 
224 /*
225 %!test
226 %! c = [0,1,2,3;1,8,12,12;4,20,24,21;7,22,25,18];
227 %! assert (conv2 ([0,1;1,2], [1,2,3;4,5,6;7,8,9]), c);
228 
229 %!test
230 %! c = single ([0,1,2,3;1,8,12,12;4,20,24,21;7,22,25,18]);
231 %! assert (conv2 (single ([0,1;1,2]), single ([1,2,3;4,5,6;7,8,9])), c);
232 
233 %!test
234 %! c = [1,4,4;5,18,16;14,48,40;19,62,48;15,48,36];
235 %! assert (conv2 (1:3, 1:2, [1,2;3,4;5,6]), c);
236 
237 %!assert (conv2 (1:3, 1:2, [1,2;3,4;5,6], "full"),
238 %! conv2 (1:3, 1:2, [1,2;3,4;5,6]));
239 
240 ## Test shapes
241 %!shared A, B, C
242 %! A = rand (3, 4);
243 %! B = rand (4);
244 %! C = conv2 (A, B);
245 %!assert (conv2 (A,B, "full"), C)
246 %!assert (conv2 (A,B, "same"), C(3:5,3:6))
247 %!assert (conv2 (A,B, "valid"), zeros (0, 1))
248 %!assert (size (conv2 (B,A, "valid")), [2 1])
249 
250 %!test
251 %! B = rand (5);
252 %! C = conv2 (A, B);
253 %!assert (conv2 (A,B, "full"), C)
254 %!assert (conv2 (A,B, "same"), C(3:5,3:6))
255 %!assert (conv2 (A,B, "valid"), zeros (0, 0))
256 %!assert (size (conv2 (B,A, "valid")), [3 2])
257 
258 ## Clear shared variables so they are not reported for tests below
259 %!shared
260 
261 ## Test cases from Bug #34893
262 %!assert <*34893> (conv2 ([1:5;1:5], [1:2], "same"),
263 %! [4 7 10 13 10; 4 7 10 13 10])
264 %!assert <*34893> (conv2 ([1:5;1:5]', [1:2]', "same"),
265 %! [4 7 10 13 10; 4 7 10 13 10]')
266 %!assert <*34893> (conv2 ([1:5;1:5], [1:2], "valid"),
267 %! [4 7 10 13; 4 7 10 13])
268 %!assert <*34893> (conv2 ([1:5;1:5]', [1:2]', "valid"),
269 %! [4 7 10 13; 4 7 10 13]')
270 
271 %% Restore the rand "seed" and "state" values in order, so that the
272 %% new "state" algorithm remains active after these tests complete.
273 %!function restore_rand_state (seed, state)
274 %! rand ("seed", seed);
275 %! rand ("state", state);
276 %!endfunction
277 
278 %% FIXME: This test only passes when using the "old" random number
279 %% generator by setting the "seed" parameter to any value. If
280 %% the "state" parameter is used, the test fails. This probably
281 %% indicates that this test is particularly fragile. This might
282 %% need further investigation or a rewrite, for example using
283 %% random integer values to avoid precision overflow.
284 %!test
285 %! old_seed = rand ("seed");
286 %! old_state = rand ("state");
287 %! restore_state = onCleanup (@() restore_rand_state (old_seed, old_state));
288 %! rand ("seed", 42);
289 %! x = rand (100);
290 %! y = ones (5);
291 %! A = conv2 (x, y)(5:end-4,5:end-4);
292 %! B = conv2 (x, y, "valid");
293 %! assert (B, A); # Yes, this test is for *exact* equivalence.
294 
295 ## Test input validation
296 %!error conv2 ()
297 %!error conv2 (1)
298 %!error <must be 1-D vectors or 2-D matrices> conv2 (ones (2), ones (2,2,2))
299 %!error <SHAPE type not valid> conv2 (1,2, "NOT_A_SHAPE")
300 ## Test alternate calling form which should be 2 vectors and a matrix
301 %!error conv2 (ones (2), 1, 1)
302 %!error conv2 (1, ones (2), 1)
303 */
304 
305 DEFUN (convn, args, ,
306  doc: /* -*- texinfo -*-
307 @deftypefn {} {@var{C} =} convn (@var{A}, @var{B})
308 @deftypefnx {} {@var{C} =} convn (@var{A}, @var{B}, @var{shape})
309 Return the n-D convolution of @var{A} and @var{B}.
310 
311 The size of the result is determined by the optional @var{shape} argument
312 which takes the following values
313 
314 @table @asis
315 @item @var{shape} = @qcode{"full"}
316 Return the full convolution. (default)
317 
318 @item @var{shape} = @qcode{"same"}
319 Return central part of the convolution with the same size as @var{A}.
320 The central part of the convolution begins at the indices
321 @code{floor ([size(@var{B})/2] + 1)}.
322 
323 @item @var{shape} = @qcode{"valid"}
324 Return only the parts which do not include zero-padded edges.
325 The size of the result is @code{max (size (A) - size (B) + 1, 0)}.
326 @end table
327 
328 @seealso{conv2, conv}
329 @end deftypefn */)
330 {
331  int nargin = args.length ();
332 
333  if (nargin < 2 || nargin > 3)
334  print_usage ();
335 
336  std::string shape = "full"; // default
337  convn_type ct = convn_full;
338 
339  if (nargin == 3)
340  shape = args(2).xstring_value ("convn: SHAPE must be a string");
341 
342  if (shape == "full")
343  ct = convn_full;
344  else if (shape == "same")
345  ct = convn_same;
346  else if (shape == "valid")
347  ct = convn_valid;
348  else
349  error ("convn: SHAPE type not valid");
350 
351  octave_value retval;
352 
353  if (args(0).is_single_type () || args(1).is_single_type ())
354  {
355  if (args(0).iscomplex () || args(1).iscomplex ())
356  {
357  FloatComplexNDArray a (args(0).float_complex_array_value ());
358  if (args(1).isreal ())
359  {
360  FloatNDArray b (args(1).float_array_value ());
361  retval = convn (a, b, ct);
362  }
363  else
364  {
365  FloatComplexNDArray b (args(1).float_complex_array_value ());
366  retval = convn (a, b, ct);
367  }
368  }
369  else
370  {
371  FloatNDArray a (args(0).float_array_value ());
372  FloatNDArray b (args(1).float_array_value ());
373  retval = convn (a, b, ct);
374  }
375  }
376  else
377  {
378  if (args(0).iscomplex () || args(1).iscomplex ())
379  {
380  ComplexNDArray a (args(0).complex_array_value ());
381  if (args(1).isreal ())
382  {
383  NDArray b (args(1).array_value ());
384  retval = convn (a, b, ct);
385  }
386  else
387  {
388  ComplexNDArray b (args(1).complex_array_value ());
389  retval = convn (a, b, ct);
390  }
391  }
392  else
393  {
394  NDArray a (args(0).array_value ());
395  NDArray b (args(1).array_value ());
396  retval = convn (a, b, ct);
397  }
398  }
399 
400  return retval;
401 }
402 
403 /*
404 %!test <39314>
405 %! v = reshape ([1 2], [1 1 2]);
406 %! assert (convn (v, v), reshape ([1 4 4], [1 1 3]));
407 %! assert (convn (v, v, "same"), reshape ([4 4], [1 1 2]));
408 %! assert (convn (v, v, "valid"), 4);
409 
410 ## The following test may look weird since we are using the output
411 ## of convn to test itself. However, because calculations are done
412 ## differently based on the shape option, it will help to catch some
413 ## bugs. See also bug #39314.
414 ## FIXME: The "valid" option uses an entirely different code path
415 ## through C++ and Fortran to calculate inner convolution.
416 ## The terms in the convolution added in reverse order compared
417 ## to the "full" option. This produces differences on the order
418 ## of tens of eps. This should be fixed, but in the meantime
419 ## the tests will be marked as known failures.
420 %!shared a, b, c
421 %! ## test 3D by 3D
422 %! a = rand (10, 10, 10);
423 %! b = rand (3, 3, 3);
424 %! c = convn (a, b, "full");
425 %!assert (convn (a, b, "same"), c(2:11,2:11,2:11))
426 %!test <39314>
427 %! assert (convn (a, b, "valid"), c(3:10,3:10,3:10));
428 %!
429 %!test
430 %! ## test 3D by 2D
431 %! a = rand (10, 10, 10);
432 %! b = rand (3, 3);
433 %! c = convn (a, b, "full");
434 %!assert (convn (a, b, "same"), c(2:11,2:11,:))
435 %!test <39314>
436 %! assert (convn (a, b, "valid"), c(3:10,3:10,:));
437 %!
438 %!test
439 %! ## test 2D by 3D
440 %! a = rand (10, 10);
441 %! b = rand (3, 3, 3);
442 %! c = convn (a, b, "full");
443 %!assert (convn (a, b, "same"), c(2:11,2:11,2))
444 %!assert (convn (a, b, "valid"), c(3:10,3:10,3:2)) # a 7x7x0 matrix
445 %!
446 %!test
447 %! ## test multiple different number of dimensions, with odd and even numbers
448 %! a = rand (10, 15, 7, 8, 10);
449 %! b = rand (4, 3, 2, 3);
450 %! c = convn (a, b, "full");
451 %!assert (convn (a, b, "same"), c(3:12,2:16,2:8,2:9,:))
452 %!test <39314>
453 %! assert (convn (a, b, "valid"), c(4:10,3:15,2:7,3:8,:));
454 
455 %!test
456 %! a = reshape (floor (magic (16) /10), [4 8 4 2]);
457 %! b = reshape (magic (6), [4 3 3]);
458 %! c = zeros (7, 10, 6, 2);
459 %! c(:,:,1,1) = [
460 %! 875 1415 1215 741 288 264 635 1109 687 171
461 %! 110 467 1551 1790 1891 1651 1165 900 659 568
462 %! 883 1047 1475 1964 2181 2302 2117 1674 579 234
463 %! 940 2330 3099 2573 2306 2207 2442 2918 2272 1004
464 %! 161 500 1564 2066 2355 2270 2099 1621 1144 831
465 %! 644 622 886 1121 1652 1967 1907 1668 529 228
466 %! 160 752 1232 768 360 284 668 1132 1380 864];
467 %! c(:,:,2,1) = [
468 %! 150 1174 1903 1971 2030 1719 1467 1420 1220 472
469 %! 986 2243 2603 2385 2308 2530 2971 3181 2266 768
470 %! 914 2443 3750 3782 3976 3821 3723 3709 2599 1178
471 %! 1922 3374 5198 5472 5563 5853 5794 5543 3578 1820
472 %! 1060 2471 3846 3724 3682 3803 3812 3927 2876 1390
473 %! 470 2078 3283 3225 2701 2265 2165 2261 2324 1124
474 %! 700 1130 1486 1515 1830 2097 2081 2028 1009 348];
475 %! c(:,:,3,1) = [
476 %! 1350 2127 2461 2082 1694 1909 2230 2621 1681 683
477 %! 877 2473 4362 4556 4543 4314 3879 3703 2863 1497
478 %! 1934 4219 5874 6117 5966 6051 5984 5714 3891 1562
479 %! 1927 5997 8573 8456 8517 8025 7957 8101 6121 2500
480 %! 1558 3533 5595 6064 6453 6491 6275 5743 3794 1832
481 %! 1950 2762 3455 3423 4019 4578 4807 4857 2304 907
482 %! 525 1860 2731 2392 1872 1724 1961 2312 2315 1141];
483 %! c(:,:,4,1) = [
484 %! 150 1317 2230 2621 2996 2767 2472 2049 1514 583
485 %! 1429 3056 3879 3703 3756 3964 4394 4570 3111 1250
486 %! 1833 4037 5984 5714 5846 5788 5883 6129 4157 2011
487 %! 3143 5469 7957 8101 8063 8475 8564 8439 5306 2538
488 %! 2001 4514 6275 5743 5391 5389 5578 6110 4473 1953
489 %! 817 3196 4807 4857 4229 3659 3477 3375 3208 1400
490 %! 750 1365 1961 2312 2840 2993 2722 2344 1092 323];
491 %! c(:,:,5,1) = [
492 %! 475 734 1296 1352 1400 1595 1557 1517 960 490
493 %! 751 1977 2831 2746 2607 2665 2733 2833 2186 912
494 %! 1065 3142 4344 4150 3768 3734 3876 4086 3366 1327
495 %! 976 3712 5530 5921 6158 5802 5481 5071 3821 1491
496 %! 1397 2996 3971 4003 4088 4180 4199 4146 2649 985
497 %! 1273 2121 2555 2247 2378 2624 2908 3229 1788 705
498 %! 365 1108 1530 1652 1550 1407 1274 1127 889 264];
499 %! c(:,:,6,1) = [
500 %! 0 133 345 683 982 1058 960 623 310 100
501 %! 437 806 1313 1332 1383 1391 1397 1370 864 495
502 %! 928 1573 2201 1928 1864 1932 2183 2445 1557 855
503 %! 1199 2083 2739 2573 2507 2656 2786 2928 1795 736
504 %! 912 1997 2404 2028 1692 1591 1803 2159 1603 599
505 %! 345 1092 1526 1666 1593 1437 1275 1116 863 253
506 %! 50 235 510 811 998 894 615 318 77 0];
507 %! c(:,:,1,2) = [
508 %! 840 1350 1176 697 293 320 674 1153 717 180
509 %! 142 490 1563 1824 1929 1604 1132 857 624 587
510 %! 890 1084 1539 1979 2238 2333 2072 1610 509 202
511 %! 966 2263 3034 2518 2250 2235 2512 2992 2305 1016
512 %! 200 561 1607 2107 2361 2277 2030 1548 1102 818
513 %! 652 631 922 1128 1670 1997 1895 1665 467 197
514 %! 160 744 1192 692 292 256 708 1208 1448 900];
515 %! c(:,:,2,2) = [
516 %! 179 1199 1886 1987 1997 1716 1479 1383 1215 485
517 %! 988 2213 2552 2358 2304 2615 3011 3210 2246 744
518 %! 921 2483 3747 3768 3960 3835 3712 3698 2588 1183
519 %! 1903 3416 5254 5490 5572 5826 5761 5505 3502 1814
520 %! 1064 2507 3825 3666 3680 3748 3821 3958 2892 1395
521 %! 495 2129 3277 3228 2566 2216 2154 2250 2390 1154
522 %! 700 1105 1472 1524 1856 2113 2059 2019 975 325];
523 %! c(:,:,3,2) = [
524 %! 1302 2104 2439 2006 1723 1931 2280 2685 1678 690
525 %! 877 2507 4408 4580 4523 4233 3852 3647 2850 1516
526 %! 1949 4238 5895 6143 6018 6063 5930 5656 3847 1538
527 %! 1953 5975 8547 8433 8407 8060 7955 8069 6170 2506
528 %! 1621 3536 5624 6117 6459 6456 6180 5666 3735 1815
529 %! 1904 2751 3429 3366 4122 4622 4840 4864 2242 882
530 %! 517 1843 2674 2337 1777 1686 2005 2367 2385 1175];
531 %! c(:,:,4,2) = [
532 %! 198 1346 2280 2685 2980 2759 2396 1982 1497 576
533 %! 1413 2994 3852 3647 3756 4035 4418 4595 3109 1231
534 %! 1873 4025 5930 5656 5792 5772 5909 6152 4185 2035
535 %! 3110 5510 7955 8069 8139 8456 8541 8439 5276 2541
536 %! 1964 4462 6180 5666 5315 5409 5631 6178 4536 1998
537 %! 869 3215 4840 4864 4121 3579 3420 3386 3271 1430
538 %! 725 1361 2005 2367 2925 3006 2667 2297 1054 325];
539 %! c(:,:,5,2) = [
540 %! 462 754 1285 1359 1441 1605 1556 1488 938 488
541 %! 729 1967 2788 2732 2608 2683 2744 2830 2195 912
542 %! 1052 3139 4302 4101 3742 3730 3895 4103 3403 1335
543 %! 1007 3725 5577 5964 6165 5754 5407 5006 3846 1507
544 %! 1375 2969 3951 3990 4144 4183 4200 4150 2661 998
545 %! 1258 2090 2495 2188 2403 2664 2954 3279 1814 723
546 %! 388 1127 1551 1673 1525 1390 1253 1139 912 275];
547 %! c(:,:,6,2) = [
548 %! 19 147 384 716 1016 1059 927 570 276 80
549 %! 441 791 1298 1320 1401 1396 1409 1367 865 500
550 %! 932 1537 2155 1870 1860 1946 2221 2487 1584 874
551 %! 1201 2067 2705 2538 2512 2687 2806 2971 1812 756
552 %! 925 1976 2363 1971 1636 1600 1844 2239 1664 626
553 %! 372 1133 1558 1687 1570 1401 1243 1122 883 264
554 %! 60 270 556 857 1024 870 569 282 66 0];
555 %!assert (convn (a, b, "full"), c)
556 %!assert (convn (a, b, "same"), c(3:6,2:9,2:5,:))
557 %!assert (convn (a, b, "valid"), c(4,3:8,3:4,:))
558 
559 ## test correct class
560 %!assert (class (convn (rand (5), rand (3))), "double")
561 %!assert (class (convn (rand (5, "single"), rand (3))), "single")
562 %!assert (class (convn (rand (5), rand (3, "single"))), "single")
563 %!assert (class (convn (true (5), rand (3))), "double")
564 %!assert (class (convn (true (5), rand (3, "single"))), "single")
565 %!assert (class (convn (ones (5, "uint8"), rand (3))), "double")
566 %!assert (class (convn (rand (3, "single"), ones (5, "uint8"))), "single")
567 
568 %!error convn ()
569 %!error convn (1)
570 %!error <SHAPE type not valid> convn (1,2, "NOT_A_SHAPE")
571 %!error convn (rand (3), 1, 1)
572 */
573 
574 OCTAVE_END_NAMESPACE(octave)
OCTAVE_END_NAMESPACE
OCTAVE_END_NAMESPACE(octave)
Matrix
Definition: dMatrix.h:42
octave_value
Definition: ov.h:73
Shape
Shape
Definition: conv2.cc:39
SHAPE_VALID
@ SHAPE_VALID
Definition: conv2.cc:39
SHAPE_SAME
@ SHAPE_SAME
Definition: conv2.cc:39
SHAPE_FULL
@ SHAPE_FULL
Definition: conv2.cc:39
OCTAVE_BEGIN_NAMESPACE
OCTAVE_BEGIN_NAMESPACE(octave) static octave_value daspk_fcn
print_usage
OCTINTERP_API void print_usage(void)
Definition: defun-int.h:72
DEFUN
#define DEFUN(name, args_name, nargout_name, doc)
Macro to define a builtin function.
Definition: defun.h:56
error
void error(const char *fmt,...)
Definition: error.cc:979
convn
NDArray convn(const NDArray &a, const NDArray &b, convn_type ct)
Definition: oct-convn.cc:217
convn_type
convn_type
Definition: oct-convn.h:52
convn_same
@ convn_same
Definition: oct-convn.h:54
convn_valid
@ convn_valid
Definition: oct-convn.h:55
convn_full
@ convn_full
Definition: oct-convn.h:53
v2
const octave_char_matrix & v2
Definition: op-int-concat.cc:170