git.sesse.net Git - c64tapwav/blob - decode.cpp

   1 #include <stdio.h>
   2 #include <string.h>
   3 #include <math.h>
   4 #include <assert.h>
   5 #include <limits.h>
   6 #include <getopt.h>
   7 #include <vector>
   8 #include <algorithm>
   9
  10 #include "audioreader.h"
  11 #include "interpolate.h"
  12 #include "level.h"
  13 #include "tap.h"
  14 #include "filter.h"
  15
  16 #define BUFSIZE 4096
  17 #define C64_FREQUENCY 985248
  18 #define SYNC_PULSE_START 1000
  19 #define SYNC_PULSE_END 20000
  20 #define SYNC_PULSE_LENGTH 378.0
  21 #define SYNC_TEST_TOLERANCE 1.10
  22
  23 // SPSA options
  24 #define NUM_FILTER_COEFF 32
  25 #define NUM_ITER 5000
  26 #define A NUM_ITER/10  // approx
  27 #define INITIAL_A 0.005 // A bit of trial and error...
  28 #define INITIAL_C 0.02  // This too.
  29 #define GAMMA 0.166
  30 #define ALPHA 1.0
  31
  32 static float hysteresis_limit = 3000.0 / 32768.0;
  33 static bool do_calibrate = true;
  34 static bool output_cycles_plot = false;
  35 static bool do_crop = false;
  36 static float crop_start = 0.0f, crop_end = HUGE_VAL;
  37
  38 static bool use_fir_filter = false;
  39 static float filter_coeff[NUM_FILTER_COEFF] = { 1.0f };  // The rest is filled with 0.
  40 static bool use_rc_filter = false;
  41 static float rc_filter_freq;
  42 static bool output_filtered = false;
  43
  44 static bool quiet = false;
  45 static bool do_auto_level = false;
  46 static bool output_leveled = false;
  47 static std::vector<float> train_snap_points;
  48 static bool do_train = false;
  49
  50 // The minimum estimated sound level (for do_auto_level) at any given point.
  51 // If you decrease this, you'll be able to amplify really silent signals
  52 // by more, but you'll also increase the level of silent (ie. noise-only) segments,
  53 // possibly caused misdetected pulses in these segments.
  54 static float min_level = 0.05f;
  55
  56 // between [x,x+1]
  57 double find_zerocrossing(const std::vector<float> &pcm, int x)
  58 {
  59         if (pcm[x] == 0) {
  60                 return x;
  61         }
  62         if (pcm[x + 1] == 0) {
  63                 return x + 1;
  64         }
  65
  66         assert(pcm[x + 1] < 0);
  67         assert(pcm[x] > 0);
  68
  69         double upper = x;
  70         double lower = x + 1;
  71         while (lower - upper > 1e-3) {
  72                 double mid = 0.5f * (upper + lower);
  73                 if (lanczos_interpolate(pcm, mid) > 0) {
  74                         upper = mid;
  75                 } else {
  76                         lower = mid;
  77                 }
  78         }
  79
  80         return 0.5f * (upper + lower);
  81 }
  82
  83 struct pulse {
  84         double time;  // in seconds from start
  85         double len;   // in seconds
  86 };
  87
  88 // Calibrate on the first ~25k pulses (skip a few, just to be sure).
  89 double calibrate(const std::vector<pulse> &pulses) {
  90         if (pulses.size() < SYNC_PULSE_END) {
  91                 fprintf(stderr, "Too few pulses, not calibrating!\n");
  92                 return 1.0;
  93         }
  94
  95         int sync_pulse_end = -1;
  96         double sync_pulse_stddev = -1.0;
  97
  98         // Compute the standard deviation (to check for uneven speeds).
  99         // If it suddenly skyrockets, we assume that sync ended earlier
 100         // than we thought (it should be 25000 cycles), and that we should
 101         // calibrate on fewer cycles.
 102         for (int try_end : { 2000, 4000, 5000, 7500, 10000, 15000, SYNC_PULSE_END }) {
 103                 double sum2 = 0.0;
 104                 for (int i = SYNC_PULSE_START; i < try_end; ++i) {
 105                         double cycles = pulses[i].len * C64_FREQUENCY;
 106                         sum2 += (cycles - SYNC_PULSE_LENGTH) * (cycles - SYNC_PULSE_LENGTH);
 107                 }
 108                 double stddev = sqrt(sum2 / (try_end - SYNC_PULSE_START - 1));
 109                 if (sync_pulse_end != -1 && stddev > 5.0 && stddev / sync_pulse_stddev > 1.3) {
 110                         fprintf(stderr, "Stopping at %d sync pulses because standard deviation would be too big (%.2f cycles); shorter-than-usual trailer?\n",
 111                                 sync_pulse_end, stddev);
 112                         break;
 113                 }
 114                 sync_pulse_end = try_end;
 115                 sync_pulse_stddev = stddev;
 116         }
 117         if (!quiet) {
 118                 fprintf(stderr, "Sync pulse length standard deviation: %.2f cycles\n",
 119                         sync_pulse_stddev);
 120         }
 121
 122         double sum = 0.0;
 123         for (int i = SYNC_PULSE_START; i < sync_pulse_end; ++i) {
 124                 sum += pulses[i].len;
 125         }
 126         double mean_length = C64_FREQUENCY * sum / (sync_pulse_end - SYNC_PULSE_START);
 127         double calibration_factor = SYNC_PULSE_LENGTH / mean_length;
 128         if (!quiet) {
 129                 fprintf(stderr, "Calibrated sync pulse length: %.2f -> %.2f (change %+.2f%%)\n",
 130                         mean_length, SYNC_PULSE_LENGTH, 100.0 * (calibration_factor - 1.0));
 131         }
 132
 133         // Check for pulses outside +/- 10% (sign of misdetection).
 134         for (int i = SYNC_PULSE_START; i < sync_pulse_end; ++i) {
 135                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 136                 if (cycles < SYNC_PULSE_LENGTH / SYNC_TEST_TOLERANCE || cycles > SYNC_PULSE_LENGTH * SYNC_TEST_TOLERANCE) {
 137                         fprintf(stderr, "Sync cycle with downflank at %.6f was detected at %.0f cycles; misdetect?\n",
 138                                 pulses[i].time, cycles);
 139                 }
 140         }
 141
 142         return calibration_factor;
 143 }
 144
 145 void output_tap(const std::vector<pulse>& pulses, double calibration_factor)
 146 {
 147         std::vector<char> tap_data;
 148         for (unsigned i = 0; i < pulses.size(); ++i) {
 149                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 150                 int len = lrintf(cycles / TAP_RESOLUTION);
 151                 if (i > SYNC_PULSE_END && (cycles < 100 || cycles > 800)) {
 152                         fprintf(stderr, "Cycle with downflank at %.6f was detected at %.0f cycles; misdetect?\n",
 153                                         pulses[i].time, cycles);
 154                 }
 155                 if (len <= 255) {
 156                         tap_data.push_back(len);
 157                 } else {
 158                         int overflow_len = lrintf(cycles);
 159                         tap_data.push_back(0);
 160                         tap_data.push_back(overflow_len & 0xff);
 161                         tap_data.push_back((overflow_len >> 8) & 0xff);
 162                         tap_data.push_back(overflow_len >> 16);
 163                 }
 164         }
 165
 166         tap_header hdr;
 167         memcpy(hdr.identifier, "C64-TAPE-RAW", 12);
 168         hdr.version = 1;
 169         hdr.reserved[0] = hdr.reserved[1] = hdr.reserved[2] = 0;
 170         hdr.data_len = tap_data.size();
 171
 172         fwrite(&hdr, sizeof(hdr), 1, stdout);
 173         fwrite(tap_data.data(), tap_data.size(), 1, stdout);
 174 }
 175
 176 static struct option long_options[] = {
 177         {"auto-level",       0,                 0, 'a' },
 178         {"output-leveled",   0,                 0, 'A' },
 179         {"no-calibrate",     0,                 0, 's' },
 180         {"plot-cycles",      0,                 0, 'p' },
 181         {"hysteresis-limit", required_argument, 0, 'l' },
 182         {"filter",           required_argument, 0, 'f' },
 183         {"rc-filter",        required_argument, 0, 'r' },
 184         {"output-filtered",  0,                 0, 'F' },
 185         {"crop",             required_argument, 0, 'c' },
 186         {"quiet",            0,                 0, 'q' },
 187         {"help",             0,                 0, 'h' },
 188         {0,                  0,                 0, 0   }
 189 };
 190
 191 void help()
 192 {
 193         fprintf(stderr, "decode [OPTIONS] AUDIO-FILE > TAP-FILE\n");
 194         fprintf(stderr, "\n");
 195         fprintf(stderr, "  -a, --auto-level             automatically adjust amplitude levels throughout the file\n");
 196         fprintf(stderr, "  -A, --output-leveled         output leveled waveform to leveled.raw\n");
 197         fprintf(stderr, "  -m, --min-level              minimum estimated sound level (0..32768) for --auto-level\n");
 198         fprintf(stderr, "  -s, --no-calibrate           do not try to calibrate on sync pulse length\n");
 199         fprintf(stderr, "  -p, --plot-cycles            output debugging info to cycles.plot\n");
 200         fprintf(stderr, "  -l, --hysteresis-limit VAL   change amplitude threshold for ignoring pulses (0..32768)\n");
 201         fprintf(stderr, "  -f, --filter C1:C2:C3:...    specify FIR filter (up to %d coefficients)\n", NUM_FILTER_COEFF);
 202         fprintf(stderr, "  -r, --rc-filter FREQ         send signal through a highpass RC filter with given frequency (in Hertz)\n");
 203         fprintf(stderr, "  -F, --output-filtered        output filtered waveform to filtered.raw\n");
 204         fprintf(stderr, "  -c, --crop START[:END]       use only the given part of the file\n");
 205         fprintf(stderr, "  -t, --train LEN1:LEN2:...    train a filter for detecting any of the given number of cycles\n");
 206         fprintf(stderr, "                               (implies --no-calibrate and --quiet unless overridden)\n");
 207         fprintf(stderr, "  -q, --quiet                  suppress some informational messages\n");
 208         fprintf(stderr, "  -h, --help                   display this help, then exit\n");
 209         exit(1);
 210 }
 211
 212 void parse_options(int argc, char **argv)
 213 {
 214         for ( ;; ) {
 215                 int option_index = 0;
 216                 int c = getopt_long(argc, argv, "aAm:spl:f:r:Fc:t:qh", long_options, &option_index);
 217                 if (c == -1)
 218                         break;
 219
 220                 switch (c) {
 221                 case 'a':
 222                         do_auto_level = true;
 223                         break;
 224
 225                 case 'A':
 226                         output_leveled = true;
 227                         break;
 228
 229                 case 'm':
 230                         min_level = atof(optarg) / 32768.0;
 231                         break;
 232
 233                 case 's':
 234                         do_calibrate = false;
 235                         break;
 236
 237                 case 'p':
 238                         output_cycles_plot = true;
 239                         break;
 240
 241                 case 'l':
 242                         hysteresis_limit = atof(optarg) / 32768.0;
 243                         break;
 244
 245                 case 'f': {
 246                         const char *coeffstr = strtok(optarg, ": ");
 247                         int coeff_index = 0;
 248                         while (coeff_index < NUM_FILTER_COEFF && coeffstr != NULL) {
 249                                 filter_coeff[coeff_index++] = atof(coeffstr);
 250                                 coeffstr = strtok(NULL, ": ");
 251                         }
 252                         use_fir_filter = true;
 253                         break;
 254                 }
 255
 256                 case 'r':
 257                         use_rc_filter = true;
 258                         rc_filter_freq = atof(optarg);
 259                         break;
 260
 261                 case 'F':
 262                         output_filtered = true;
 263                         break;
 264
 265                 case 'c': {
 266                         const char *cropstr = strtok(optarg, ":");
 267                         crop_start = atof(cropstr);
 268                         cropstr = strtok(NULL, ":");
 269                         if (cropstr == NULL) {
 270                                 crop_end = HUGE_VAL;
 271                         } else {
 272                                 crop_end = atof(cropstr);
 273                         }
 274                         do_crop = true;
 275                         break;
 276                 }
 277
 278                 case 't': {
 279                         const char *cyclestr = strtok(optarg, ":");
 280                         while (cyclestr != NULL) {
 281                                 train_snap_points.push_back(atof(cyclestr));
 282                                 cyclestr = strtok(NULL, ":");
 283                         }
 284                         do_train = true;
 285
 286                         // Set reasonable defaults (can be overridden later on the command line).
 287                         do_calibrate = false;
 288                         quiet = true;
 289                         break;
 290                 }
 291
 292                 case 'q':
 293                         quiet = true;
 294                         break;
 295
 296                 case 'h':
 297                 default:
 298                         help();
 299                         exit(1);
 300                 }
 301         }
 302 }
 303
 304 std::vector<float> crop(const std::vector<float>& pcm, float crop_start, float crop_end, int sample_rate)
 305 {
 306         size_t start_sample, end_sample;
 307         if (crop_start >= 0.0f) {
 308                 start_sample = std::min<size_t>(lrintf(crop_start * sample_rate), pcm.size());
 309         }
 310         if (crop_end >= 0.0f) {
 311                 end_sample = std::min<size_t>(lrintf(crop_end * sample_rate), pcm.size());
 312         }
 313         return std::vector<float>(pcm.begin() + start_sample, pcm.begin() + end_sample);
 314 }
 315
 316 // TODO: Support AVX here.
 317 std::vector<float> do_fir_filter(const std::vector<float>& pcm, const float* filter)
 318 {
 319         std::vector<float> filtered_pcm;
 320         filtered_pcm.reserve(pcm.size());
 321         for (unsigned i = NUM_FILTER_COEFF; i < pcm.size(); ++i) {
 322                 float s = 0.0f;
 323                 for (int j = 0; j < NUM_FILTER_COEFF; ++j) {
 324                         s += filter[j] * pcm[i - j];
 325                 }
 326                 filtered_pcm.push_back(s);
 327         }
 328
 329         if (output_filtered) {
 330                 FILE *fp = fopen("filtered.raw", "wb");
 331                 fwrite(filtered_pcm.data(), filtered_pcm.size() * sizeof(filtered_pcm[0]), 1, fp);
 332                 fclose(fp);
 333         }
 334
 335         return filtered_pcm;
 336 }
 337
 338 std::vector<float> do_rc_filter(const std::vector<float>& pcm, float freq, int sample_rate)
 339 {
 340         std::vector<float> filtered_pcm;
 341         filtered_pcm.resize(pcm.size());
 342         Filter filter = Filter::hpf(M_PI * freq / sample_rate);
 343         for (unsigned i = 0; i < pcm.size(); ++i) {
 344                 filtered_pcm[i] = filter.update(pcm[i]);
 345         }
 346
 347         if (output_filtered) {
 348                 FILE *fp = fopen("filtered.raw", "wb");
 349                 fwrite(filtered_pcm.data(), filtered_pcm.size() * sizeof(filtered_pcm[0]), 1, fp);
 350                 fclose(fp);
 351         }
 352
 353         return filtered_pcm;
 354 }
 355
 356 std::vector<pulse> detect_pulses(const std::vector<float> &pcm, int sample_rate)
 357 {
 358         std::vector<pulse> pulses;
 359
 360         // Find the flanks.
 361         int last_bit = -1;
 362         double last_downflank = -1;
 363         for (unsigned i = 0; i < pcm.size(); ++i) {
 364                 int bit = (pcm[i] > 0) ? 1 : 0;
 365                 if (bit == 0 && last_bit == 1) {
 366                         // Check if we ever go up above <hysteresis_limit> before we dip down again.
 367                         bool true_pulse = false;
 368                         unsigned j;
 369                         int min_level_after = 32767;
 370                         for (j = i; j < pcm.size(); ++j) {
 371                                 min_level_after = std::min<int>(min_level_after, pcm[j]);
 372                                 if (pcm[j] > 0) break;
 373                                 if (pcm[j] < -hysteresis_limit) {
 374                                         true_pulse = true;
 375                                         break;
 376                                 }
 377                         }
 378
 379                         if (!true_pulse) {
 380 #if 0
 381                                 fprintf(stderr, "Ignored down-flank at %.6f seconds due to hysteresis (%d < %d).\n",
 382                                         double(i) / sample_rate, -min_level_after, hysteresis_limit);
 383 #endif
 384                                 i = j;
 385                                 continue;
 386                         }
 387
 388                         // down-flank!
 389                         double t = find_zerocrossing(pcm, i - 1) * (1.0 / sample_rate) + crop_start;
 390                         if (last_downflank > 0) {
 391                                 pulse p;
 392                                 p.time = t;
 393                                 p.len = t - last_downflank;
 394                                 pulses.push_back(p);
 395                         }
 396                         last_downflank = t;
 397                 }
 398                 last_bit = bit;
 399         }
 400         return pulses;
 401 }
 402
 403 void output_cycle_plot(const std::vector<pulse> &pulses, double calibration_factor)
 404 {
 405         FILE *fp = fopen("cycles.plot", "w");
 406         for (unsigned i = 0; i < pulses.size(); ++i) {
 407                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 408                 fprintf(fp, "%f %f\n", pulses[i].time, cycles);
 409         }
 410         fclose(fp);
 411 }
 412
 413 std::pair<int, double> find_closest_point(double x, const std::vector<float> &points)
 414 {
 415         int best_point = 0;
 416         double best_dist = (x - points[0]) * (x - points[0]);
 417         for (unsigned j = 1; j < train_snap_points.size(); ++j) {
 418                 double dist = (x - points[j]) * (x - points[j]);
 419                 if (dist < best_dist) {
 420                         best_point = j;
 421                         best_dist = dist;
 422                 }
 423         }
 424         return std::make_pair(best_point, best_dist);
 425 }
 426
 427 float eval_badness(const std::vector<pulse>& pulses, double calibration_factor)
 428 {
 429         double sum_badness = 0.0;
 430         for (unsigned i = 0; i < pulses.size(); ++i) {
 431                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 432                 if (cycles > 2000.0) cycles = 2000.0;  // Don't make pauses arbitrarily bad.
 433                 std::pair<int, double> selected_point_and_sq_dist = find_closest_point(cycles, train_snap_points);
 434                 sum_badness += selected_point_and_sq_dist.second;
 435         }
 436         return sqrt(sum_badness / (pulses.size() - 1));
 437 }
 438
 439 void find_kmeans(const std::vector<pulse> &pulses, double calibration_factor, const std::vector<float> &initial_centers)
 440 {
 441         std::vector<float> last_centers = initial_centers;
 442         std::vector<float> sums;
 443         std::vector<float> num;
 444         sums.resize(initial_centers.size());
 445         num.resize(initial_centers.size());
 446         for ( ;; ) {
 447                 for (unsigned i = 0; i < initial_centers.size(); ++i) {
 448                         sums[i] = 0.0f;
 449                         num[i] = 0;
 450                 }
 451                 for (unsigned i = 0; i < pulses.size(); ++i) {
 452                         double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 453                         // Ignore heavy outliers, which are almost always long pauses.
 454                         if (cycles > 2000.0) {
 455                                 continue;
 456                         }
 457                         std::pair<int, double> selected_point_and_sq_dist = find_closest_point(cycles, last_centers);
 458                         int p = selected_point_and_sq_dist.first;
 459                         sums[p] += cycles;
 460                         ++num[p];
 461                 }
 462                 bool any_moved = false;
 463                 for (unsigned i = 0; i < initial_centers.size(); ++i) {
 464                         if (num[i] == 0) {
 465                                 printf("K-means broke down, can't output new reference training points\n");
 466                                 return;
 467                         }
 468                         float new_center = sums[i] / num[i];
 469                         if (fabs(new_center - last_centers[i]) > 1e-3) {
 470                                 any_moved = true;
 471                         }
 472                         last_centers[i] = new_center;
 473                 }
 474                 if (!any_moved) {
 475                         break;
 476                 }
 477         }
 478         printf("New reference training points:");
 479         for (unsigned i = 0; i < last_centers.size(); ++i) {
 480                 printf(" %.3f", last_centers[i]);
 481         }
 482         printf("\n");
 483 }
 484
 485 void spsa_train(const std::vector<float> &pcm, int sample_rate)
 486 {
 487         float filter[NUM_FILTER_COEFF] = { 1.0f };  // The rest is filled with 0.
 488
 489         float start_c = INITIAL_C;
 490         double best_badness = HUGE_VAL;
 491
 492         for (int n = 1; n < NUM_ITER; ++n) {
 493                 float a = INITIAL_A * pow(n + A, -ALPHA);
 494                 float c = start_c * pow(n, -GAMMA);
 495
 496                 // find a random perturbation
 497                 float p[NUM_FILTER_COEFF];
 498                 float filter1[NUM_FILTER_COEFF], filter2[NUM_FILTER_COEFF];
 499                 for (int i = 0; i < NUM_FILTER_COEFF; ++i) {
 500                         p[i] = (rand() % 2) ? 1.0 : -1.0;
 501                         filter1[i] = std::max(std::min(filter[i] - c * p[i], 1.0f), -1.0f);
 502                         filter2[i] = std::max(std::min(filter[i] + c * p[i], 1.0f), -1.0f);
 503                 }
 504
 505                 std::vector<pulse> pulses1 = detect_pulses(do_fir_filter(pcm, filter1), sample_rate);
 506                 std::vector<pulse> pulses2 = detect_pulses(do_fir_filter(pcm, filter2), sample_rate);
 507                 float badness1 = eval_badness(pulses1, 1.0);
 508                 float badness2 = eval_badness(pulses2, 1.0);
 509
 510                 // Find the gradient estimator
 511                 float g[NUM_FILTER_COEFF];
 512                 for (int i = 0; i < NUM_FILTER_COEFF; ++i) {
 513                         g[i] = (badness2 - badness1) / (2.0 * c * p[i]);
 514                         filter[i] -= a * g[i];
 515                         filter[i] = std::max(std::min(filter[i], 1.0f), -1.0f);
 516                 }
 517                 if (badness2 < badness1) {
 518                         std::swap(badness1, badness2);
 519                         std::swap(filter1, filter2);
 520                         std::swap(pulses1, pulses2);
 521                 }
 522                 if (badness1 < best_badness) {
 523                         printf("\nNew best filter (badness=%f):", badness1);
 524                         for (int i = 0; i < NUM_FILTER_COEFF; ++i) {
 525                                 printf(" %.5f", filter1[i]);
 526                         }
 527                         best_badness = badness1;
 528                         printf("\n");
 529
 530                         find_kmeans(pulses1, 1.0, train_snap_points);
 531
 532                         if (output_cycles_plot) {
 533                                 output_cycle_plot(pulses1, 1.0);
 534                         }
 535                 }
 536                 printf("%d ", n);
 537                 fflush(stdout);
 538         }
 539 }
 540
 541 int main(int argc, char **argv)
 542 {
 543         parse_options(argc, argv);
 544
 545         make_lanczos_weight_table();
 546         std::vector<float> pcm;
 547         int sample_rate;
 548         if (!read_audio_file(argv[optind], &pcm, &sample_rate)) {
 549                 exit(1);
 550         }
 551
 552         if (do_crop) {
 553                 pcm = crop(pcm, crop_start, crop_end, sample_rate);
 554         }
 555
 556         if (use_fir_filter) {
 557                 pcm = do_fir_filter(pcm, filter_coeff);
 558         }
 559
 560         if (use_rc_filter) {
 561                 pcm = do_rc_filter(pcm, rc_filter_freq, sample_rate);
 562         }
 563
 564         if (do_auto_level) {
 565                 pcm = level_samples(pcm, min_level, sample_rate);
 566                 if (output_leveled) {
 567                         FILE *fp = fopen("leveled.raw", "wb");
 568                         fwrite(pcm.data(), pcm.size() * sizeof(pcm[0]), 1, fp);
 569                         fclose(fp);
 570                 }
 571         }
 572
 573 #if 0
 574         for (int i = 0; i < LEN; ++i) {
 575                 in[i] += rand() % 10000;
 576         }
 577 #endif
 578
 579 #if 0
 580         for (int i = 0; i < LEN; ++i) {
 581                 printf("%d\n", in[i]);
 582         }
 583 #endif
 584
 585         if (do_train) {
 586                 spsa_train(pcm, sample_rate);
 587                 exit(0);
 588         }
 589
 590         std::vector<pulse> pulses = detect_pulses(pcm, sample_rate);
 591
 592         double calibration_factor = 1.0;
 593         if (do_calibrate) {
 594                 calibration_factor = calibrate(pulses);
 595         }
 596
 597         if (output_cycles_plot) {
 598                 output_cycle_plot(pulses, calibration_factor);
 599         }
 600
 601         output_tap(pulses, calibration_factor);
 602 }