-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathgain_analysis.c
562 lines (501 loc) · 18.5 KB
/
gain_analysis.c
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
/*
* ReplayGainAnalysis - analyzes input samples and give the recommended dB
* change
* Copyright (C) 2001 David Robinson and Glen Sawyer
* Improvements and optimizations added by Frank Klemm, and by Marcel Mller
*
* This library is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 2.1 of the License, or (at your option) any later version.
*
* This library 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
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with this library; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*
* concept and filter values by David Robinson ([email protected])
* -- blame him if you think the idea is flawed
* original coding by Glen Sawyer ([email protected])
* -- blame him if you think this runs too slowly, or the coding is
* otherwise flawed
*
* lots of code improvements by Frank Klemm
* (http://www.uni-jena.de/~pfk/mpp/)
* -- credit him for all the _good_ programming ;)
*
* interface changes by Markus Peloquin <[email protected]>
*
* For an explanation of the concepts and the basic algorithms involved, go
* to:
* http://www.replaygain.org/
*/
/*
* So here's the main source of potential code confusion:
*
* The filters applied to the incoming samples are IIR filters,
* meaning they rely on up to <filter order> number of previous samples
* AND up to <filter order> number of previous filtered samples.
*
* I set up the gain_analyze_samples routine to minimize memory usage and
* interface complexity. The speed isn't compromised too much (I don't think),
* but the internal complexity is higher than it should be for such a
* relatively simple routine.
*
* Optimization/clarity suggestions are welcome.
*/
#include <assert.h>
#include <math.h>
#include <stdbool.h>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include "gain_analysis.h"
#define YULE_ORDER 10
#define BUTTER_ORDER 2
/* percentile which is louder than the proposed level */
//const double RMS_PERCENTILE = 0.95;
const double RMS_DIVISOR = 20;
/* maximum allowed sample frequency [Hz] */
#define MAX_SAMP_FREQ 48000
/* Time slice size [s] */
#define RMS_WINDOW_TIME_NUM 1
#define RMS_WINDOW_TIME_DEN 20
/* Table entries per dB */
#define MAX_ORDER (BUTTER_ORDER > YULE_ORDER ? BUTTER_ORDER : YULE_ORDER)
/* max. Samples per Time slice */
#define MAX_SAMPLES_PER_WINDOW (size_t)(MAX_SAMP_FREQ * RMS_WINDOW_TIME_NUM / RMS_WINDOW_TIME_DEN + 1) // FIXME should there be a +1 in here?
/* calibration value; ref_pink.wav must get 6.0 dB */
const double PINK_REF = 64.82; /* 298640883795 */
/* Type used for filtering */
typedef double Float_t;
struct replaygain_ctx {
Float_t linprebuf[MAX_ORDER * 2];
/* left input samples, with pre-buffer */
Float_t *linpre;
Float_t lstepbuf[MAX_SAMPLES_PER_WINDOW + MAX_ORDER];
/* left "first step" (i.e. post first filter) samples */
Float_t *lstep;
Float_t loutbuf[MAX_SAMPLES_PER_WINDOW + MAX_ORDER];
/* left "out" (i.e. post second filter) samples */
Float_t *lout;
Float_t rinprebuf[MAX_ORDER * 2];
/* right input samples ... */
Float_t *rinpre;
Float_t rstepbuf[MAX_SAMPLES_PER_WINDOW + MAX_ORDER];
Float_t *rstep;
Float_t routbuf[MAX_SAMPLES_PER_WINDOW + MAX_ORDER];
Float_t *rout;
/* number of samples required to reach number of milliseconds required
* for RMS window */
unsigned long sample_window;
unsigned long totsamp;
Float_t lsum;
Float_t rsum;
int freqindex;
int first;
struct replaygain_value value;
};
static void filter_butter(const Float_t *, Float_t *, size_t,
const Float_t *);
static void filter_yule(const Float_t *, Float_t *, size_t,
const Float_t *);
static inline Float_t fsqr(const Float_t);
static Float_t peak_value(const Float_t *, size_t);
/* for each filter:
* [0] 48 kHz, [1] 44.1 kHz, [2] 32 kHz, [3] 24 kHz, [4] 22050 Hz,
* [5] 16 kHz, [6] 12 kHz, [7] is 11025 Hz, [8] 8 kHz */
#ifdef WIN32
#ifndef __GNUC__
#pragma warning(disable : 4305)
#endif
#endif
static const Float_t ABYule[9][2*YULE_ORDER + 1] = {
{ 0.03857599435200, -3.84664617118067, -0.02160367184185,
7.81501653005538, -0.00123395316851, -11.34170355132042,
-0.00009291677959, 13.05504219327545, -0.01655260341619,
-12.28759895145294, 0.02161526843274, 9.48293806319790,
-0.02074045215285, -5.87257861775999, 0.00594298065125,
2.75465861874613, 0.00306428023191, -0.86984376593551,
0.00012025322027, 0.13919314567432, 0.00288463683916 },
{ 0.05418656406430, -3.47845948550071, -0.02911007808948,
6.36317777566148, -0.00848709379851, -8.54751527471874,
-0.00851165645469, 9.47693607801280, -0.00834990904936,
-8.81498681370155, 0.02245293253339, 6.85401540936998,
-0.02596338512915, -4.39470996079559, 0.01624864962975,
2.19611684890774, -0.00240879051584, -0.75104302451432,
0.00674613682247, 0.13149317958808, -0.00187763777362 },
{ 0.15457299681924, -2.37898834973084, -0.09331049056315,
2.84868151156327, -0.06247880153653, -2.64577170229825,
0.02163541888798, 2.23697657451713, -0.05588393329856,
-1.67148153367602, 0.04781476674921, 1.00595954808547,
0.00222312597743, -0.45953458054983, 0.03174092540049,
0.16378164858596, -0.01390589421898, -0.05032077717131,
0.00651420667831, 0.02347897407020, -0.00881362733839 },
{ 0.30296907319327, -1.61273165137247, -0.22613988682123,
1.07977492259970, -0.08587323730772, -0.25656257754070,
0.03282930172664, -0.16276719120440, -0.00915702933434,
-0.22638893773906, -0.02364141202522, 0.39120800788284,
-0.00584456039913, -0.22138138954925, 0.06276101321749,
0.04500235387352, -0.00000828086748, 0.02005851806501,
0.00205861885564, 0.00302439095741, -0.02950134983287 },
{ 0.33642304856132, -1.49858979367799, -0.25572241425570,
0.87350271418188, -0.11828570177555, 0.12205022308084,
0.11921148675203, -0.80774944671438, -0.07834489609479,
0.47854794562326, -0.00469977914380, -0.12453458140019,
-0.00589500224440, -0.04067510197014, 0.05724228140351,
0.08333755284107, 0.00832043980773, -0.04237348025746,
-0.01635381384540, 0.02977207319925, -0.01760176568150 },
{ 0.44915256608450, -0.62820619233671, -0.14351757464547,
0.29661783706366, -0.22784394429749, -0.37256372942400,
-0.01419140100551, 0.00213767857124, 0.04078262797139,
-0.42029820170918, -0.12398163381748, 0.22199650564824,
0.04097565135648, 0.00613424350682, 0.10478503600251,
0.06747620744683, -0.01863887810927, 0.05784820375801,
-0.03193428438915, 0.03222754072173, 0.00541907748707 },
{ 0.56619470757641, -1.04800335126349, -0.75464456939302,
0.29156311971249, 0.16242137742230, -0.26806001042947,
0.16744243493672, 0.00819999645858, -0.18901604199609,
0.45054734505008, 0.30931782841830, -0.33032403314006,
-0.27562961986224, 0.06739368333110, 0.00647310677246,
-0.04784254229033, 0.08647503780351, 0.01639907836189,
-0.03788984554840, 0.01807364323573, -0.00588215443421 },
{ 0.58100494960553, -0.51035327095184, -0.53174909058578,
-0.31863563325245, -0.14289799034253, -0.20256413484477,
0.17520704835522, 0.14728154134330, 0.02377945217615,
0.38952639978999, 0.15558449135573, -0.23313271880868,
-0.25344790059353, -0.05246019024463, 0.01628462406333,
-0.02505961724053, 0.06920467763959, 0.02442357316099,
-0.03721611395801, 0.01818801111503, -0.00749618797172 },
{ 0.53648789255105, -0.25049871956020, -0.42163034350696,
-0.43193942311114, -0.00275953611929, -0.03424681017675,
0.04267842219415, -0.04678328784242, -0.10214864179676,
0.26408300200955, 0.14590772289388, 0.15113130533216,
-0.02459864859345, -0.17556493366449, -0.11202315195388,
-0.18823009262115, -0.04060034127000, 0.05477720428674,
0.04788665548180, 0.04704409688120, -0.02217936801134 }
};
static const Float_t ABButter[9][2*BUTTER_ORDER + 1] = {
{ 0.98621192462708, -1.97223372919527, -1.97242384925416,
0.97261396931306, 0.98621192462708 },
{ 0.98500175787242, -1.96977855582618, -1.97000351574484,
0.97022847566350, 0.98500175787242 },
{ 0.97938932735214, -1.95835380975398, -1.95877865470428,
0.95920349965459, 0.97938932735214 },
{ 0.97531843204928, -1.95002759149878, -1.95063686409857,
0.95124613669835, 0.97531843204928 },
{ 0.97316523498161, -1.94561023566527, -1.94633046996323,
0.94705070426118, 0.97316523498161 },
{ 0.96454515552826, -1.92783286977036, -1.92909031105652,
0.93034775234268, 0.96454515552826 },
{ 0.96009142950541, -1.91858953033784, -1.92018285901082,
0.92177618768381, 0.96009142950541 },
{ 0.95856916599601, -1.91542108074780, -1.91713833199203,
0.91885558323625, 0.95856916599601 },
{ 0.94597685600279, -1.88903307939452, -1.89195371200558,
0.89487434461664, 0.94597685600279 }
};
#ifdef WIN32
#ifndef __GNUC__
#pragma warning(default : 4305)
#endif
#endif
/* When calling these filter procedures, make sure that ip[-order] and
* op[-order] point to real data! */
/* If your compiler complains that "'operation on 'output' may be undefined",
* you can either ignore the warnings or uncomment the three "y" lines (and
* comment out the indicated line) */
static void
filter_yule(const Float_t *input, Float_t *output, size_t nSamples,
const Float_t *kernel) {
while (nSamples--) {
/* 1e-10 is a hack to avoid slowdown because of denormals */
*output = 1e-10 + input[ 0] * kernel[ 0] -
output[ -1] * kernel[ 1] + input[ -1] * kernel[ 2] -
output[ -2] * kernel[ 3] + input[ -2] * kernel[ 4] -
output[ -3] * kernel[ 5] + input[ -3] * kernel[ 6] -
output[ -4] * kernel[ 7] + input[ -4] * kernel[ 8] -
output[ -5] * kernel[ 9] + input[ -5] * kernel[10] -
output[ -6] * kernel[11] + input[ -6] * kernel[12] -
output[ -7] * kernel[13] + input[ -7] * kernel[14] -
output[ -8] * kernel[15] + input[ -8] * kernel[16] -
output[ -9] * kernel[17] + input[ -9] * kernel[18] -
output[-10] * kernel[19] + input[-10] * kernel[20];
++output;
++input;
}
}
static void
filter_butter(const Float_t *input, Float_t *output, size_t nSamples,
const Float_t *kernel) {
while (nSamples--) {
*output = input[0] * kernel[0] -
output[-1] * kernel[1] + input[-1] * kernel[2] -
output[-2] * kernel[3] + input[-2] * kernel[4];
++output;
++input;
}
}
enum replaygain_status
replaygain_reset_frequency(struct replaygain_ctx *ctx, unsigned long freq) {
/* zero out initial values */
memset(ctx->linprebuf, 0, sizeof(Float_t) * MAX_ORDER);
memset(ctx->rinprebuf, 0, sizeof(Float_t) * MAX_ORDER);
memset(ctx->lstepbuf, 0, sizeof(Float_t) * MAX_ORDER);
memset(ctx->rstepbuf, 0, sizeof(Float_t) * MAX_ORDER);
memset(ctx->loutbuf, 0, sizeof(Float_t) * MAX_ORDER);
memset(ctx->routbuf, 0, sizeof(Float_t) * MAX_ORDER);
switch (freq) {
case 48000L: ctx->freqindex = 0; break;
case 44100L: ctx->freqindex = 1; break;
case 32000L: ctx->freqindex = 2; break;
case 24000L: ctx->freqindex = 3; break;
case 22050L: ctx->freqindex = 4; break;
case 16000L: ctx->freqindex = 5; break;
case 12000L: ctx->freqindex = 6; break;
case 11025L: ctx->freqindex = 7; break;
case 8000L: ctx->freqindex = 8; break;
default:
return REPLAYGAIN_ERR_SAMPLEFREQ;
}
/* ceil(freq * (float)NUM/DEN) */
ctx->sample_window =
(freq * RMS_WINDOW_TIME_NUM + RMS_WINDOW_TIME_DEN-1) /
RMS_WINDOW_TIME_DEN;
ctx->lsum = 0.0;
ctx->rsum = 0.0;
ctx->totsamp = 0L;
memset(&ctx->value, 0, sizeof(ctx->value));
return REPLAYGAIN_OK;
}
struct replaygain_ctx *
replaygain_alloc(unsigned long freq, enum replaygain_status *out_status) {
struct replaygain_ctx *ctx;
enum replaygain_status status;
if (!(ctx = malloc(sizeof(struct replaygain_ctx)))) {
if (out_status) *out_status = REPLAYGAIN_ERR_MEM;
return 0;
}
status = replaygain_reset_frequency(ctx, freq);
if (status != REPLAYGAIN_OK) {
free(ctx);
if (out_status) *out_status = status;
return 0;
}
ctx->linpre = ctx->linprebuf + MAX_ORDER;
ctx->rinpre = ctx->rinprebuf + MAX_ORDER;
ctx->lstep = ctx->lstepbuf + MAX_ORDER;
ctx->rstep = ctx->rstepbuf + MAX_ORDER;
ctx->lout = ctx->loutbuf + MAX_ORDER;
ctx->rout = ctx->routbuf + MAX_ORDER;
memset(ctx->value.value, 0, sizeof(ctx->value.value));
if (out_status) *out_status = REPLAYGAIN_OK;
return ctx;
}
static inline Float_t
fsqr(const Float_t d) {
return d * d;
}
static Float_t
peak_value(const Float_t *samples, size_t num_samples) {
Float_t peak = 0.0;
while (num_samples--) {
Float_t sample = *samples++;
if (peak < sample)
peak = sample;
else if (peak < -sample)
peak = -sample;
}
return peak;
}
enum replaygain_status
replaygain_analyze(struct replaygain_ctx *ctx, const Float_t *lsamples,
const Float_t *rsamples, size_t num_samples, unsigned channels) {
unsigned long batchsamples;
unsigned long cursamplepos;
size_t copy_samples;
if (!num_samples)
return REPLAYGAIN_OK;
cursamplepos = 0;
batchsamples = num_samples;
double peak = peak_value(lsamples, num_samples);
switch (channels) {
case 1:
rsamples = lsamples;
break;
case 2:
{
double peak0 = peak_value(rsamples, num_samples);
if (peak0 > peak) peak = peak0;
break;
}
default:
return REPLAYGAIN_ERROR;
}
if (ctx->value.peak < peak)
ctx->value.peak = peak;
copy_samples = num_samples;
if (MAX_ORDER < copy_samples) copy_samples = MAX_ORDER;
memcpy(ctx->linprebuf + MAX_ORDER, lsamples,
copy_samples * sizeof(Float_t));
memcpy(ctx->rinprebuf + MAX_ORDER, rsamples,
copy_samples * sizeof(Float_t));
while (batchsamples > 0) {
const Float_t *curleft;
const Float_t *curright;
unsigned long cursamples;
unsigned i;
cursamples =
batchsamples > ctx->sample_window - ctx->totsamp ?
ctx->sample_window - ctx->totsamp : batchsamples;
if (cursamplepos < MAX_ORDER) {
curleft = ctx->linpre + cursamplepos;
curright = ctx->rinpre + cursamplepos;
if (cursamples > MAX_ORDER - cursamplepos)
cursamples = MAX_ORDER - cursamplepos;
} else {
curleft = lsamples + cursamplepos;
curright = rsamples + cursamplepos;
}
filter_yule(curleft, ctx->lstep + ctx->totsamp, cursamples,
ABYule[ctx->freqindex]);
filter_yule(curright, ctx->rstep + ctx->totsamp, cursamples,
ABYule[ctx->freqindex]);
filter_butter(ctx->lstep + ctx->totsamp,
ctx->lout + ctx->totsamp, cursamples,
ABButter[ctx->freqindex]);
filter_butter(ctx->rstep + ctx->totsamp,
ctx->rout + ctx->totsamp, cursamples,
ABButter[ctx->freqindex]);
/* get the squared values */
curleft = ctx->lout + ctx->totsamp;
curright = ctx->rout + ctx->totsamp;
for (i = cursamples % 16; i; i--) {
ctx->lsum += fsqr(*curleft++);
ctx->rsum += fsqr(*curright++);
}
for (i = cursamples / 16; i; i--) {
ctx->lsum += fsqr(curleft[0]) +
fsqr(curleft[1]) +
fsqr(curleft[2]) +
fsqr(curleft[3]) +
fsqr(curleft[4]) +
fsqr(curleft[5]) +
fsqr(curleft[6]) +
fsqr(curleft[7]) +
fsqr(curleft[8]) +
fsqr(curleft[9]) +
fsqr(curleft[10]) +
fsqr(curleft[11]) +
fsqr(curleft[12]) +
fsqr(curleft[13]) +
fsqr(curleft[14]) +
fsqr(curleft[15]);
curleft += 16;
ctx->rsum += fsqr(curright[0]) +
fsqr(curright[1]) +
fsqr(curright[2]) +
fsqr(curright[3]) +
fsqr(curright[4]) +
fsqr(curright[5]) +
fsqr(curright[6]) +
fsqr(curright[7]) +
fsqr(curright[8]) +
fsqr(curright[9]) +
fsqr(curright[10]) +
fsqr(curright[11]) +
fsqr(curright[12]) +
fsqr(curright[13]) +
fsqr(curright[14]) +
fsqr(curright[15]);
curright += 16;
}
batchsamples -= cursamples;
cursamplepos += cursamples;
ctx->totsamp += cursamples;
/* get the RMS for this set of samples */
if (ctx->totsamp == ctx->sample_window) {
double val;
size_t ival;
val = STEPS_PER_DB * 10 * log10(
(ctx->lsum + ctx->rsum) / (ctx->totsamp * 2) +
1.0e-37);
ival = val < 0.0 ? 0 : (size_t)val;
if (ival >= ANALYZE_SIZE)
ival = ANALYZE_SIZE - 1;
ctx->value.value[ival]++;
ctx->lsum = ctx->rsum = 0.0;
memmove(ctx->loutbuf, ctx->loutbuf + ctx->totsamp,
MAX_ORDER * sizeof(Float_t));
memmove(ctx->routbuf, ctx->routbuf + ctx->totsamp,
MAX_ORDER * sizeof(Float_t));
memmove(ctx->lstepbuf, ctx->lstepbuf + ctx->totsamp,
MAX_ORDER * sizeof(Float_t));
memmove(ctx->rstepbuf, ctx->rstepbuf + ctx->totsamp,
MAX_ORDER * sizeof(Float_t));
ctx->totsamp = 0L;
}
/* XXX somehow I really screwed up: Error in programming!
* Contact author about totsamp > sample_window
*
* Markus: I'm not sure who wrote above note or what it
* means; maybe it's an assertion */
if (ctx->totsamp > ctx->sample_window)
return REPLAYGAIN_ERROR;
}
if (num_samples < MAX_ORDER) {
memmove(ctx->linprebuf, ctx->linprebuf + num_samples,
(MAX_ORDER - num_samples) * sizeof(Float_t));
memmove(ctx->rinprebuf, ctx->rinprebuf + num_samples,
(MAX_ORDER - num_samples) * sizeof(Float_t));
memcpy(ctx->linprebuf + MAX_ORDER - num_samples,
lsamples, num_samples * sizeof(Float_t));
memcpy(ctx->rinprebuf + MAX_ORDER - num_samples,
rsamples, num_samples * sizeof(Float_t));
} else {
memcpy(ctx->linprebuf,
lsamples + num_samples - MAX_ORDER,
MAX_ORDER * sizeof(Float_t));
memcpy(ctx->rinprebuf,
rsamples + num_samples - MAX_ORDER,
MAX_ORDER * sizeof(Float_t));
}
return REPLAYGAIN_OK;
}
Float_t
replaygain_adjustment(const struct replaygain_value *out) {
uint32_t elems;
int32_t upper;
size_t i;
elems = 0;
for (i = 0; i < ANALYZE_SIZE; i++)
elems += out->value[i];
if (!elems)
return GAIN_NOT_ENOUGH_SAMPLES;
upper = (elems + RMS_DIVISOR - 1) / RMS_DIVISOR;
for (i = ANALYZE_SIZE; i-- != 0;) {
upper -= out->value[i];
if (upper <= 0)
break;
}
assert(i < ANALYZE_SIZE);
return PINK_REF - (Float_t)i / STEPS_PER_DB;
}
void
replaygain_pop(struct replaygain_ctx *ctx, struct replaygain_value *out) {
memcpy(out, &ctx->value, sizeof(ctx->value));
memset(&ctx->value, 0, sizeof(ctx->value));
memset(ctx->linprebuf, 0, sizeof(Float_t) * MAX_ORDER);
memset(ctx->rinprebuf, 0, sizeof(Float_t) * MAX_ORDER);
memset(ctx->lstepbuf, 0, sizeof(Float_t) * MAX_ORDER);
memset(ctx->rstepbuf, 0, sizeof(Float_t) * MAX_ORDER);
memset(ctx->loutbuf, 0, sizeof(Float_t) * MAX_ORDER);
memset(ctx->routbuf, 0, sizeof(Float_t) * MAX_ORDER);
ctx->totsamp = 0L;
ctx->lsum = ctx->rsum = 0.0;
}