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

   1 // Copyright Steinar H. Gunderson <sgunderson@bigfoot.com>
   2 // Licensed under the GPL, v2. (See the file COPYING.)
   3
   4 #include <stdio.h>
   5 #include <string.h>
   6 #include <math.h>
   7 #include <assert.h>
   8 #include <limits.h>
   9 #include <getopt.h>
  10 #include <vector>
  11 #include <algorithm>
  12
  13 #include "audioreader.h"
  14 #include "interpolate.h"
  15 #include "level.h"
  16 #include "tap.h"
  17 #include "filter.h"
  18
  19 #define BUFSIZE 4096
  20 #define C64_FREQUENCY 985248
  21 #define SYNC_PULSE_START 1000
  22 #define SYNC_PULSE_END 20000
  23 #define SYNC_PULSE_LENGTH 378.0
  24 #define SYNC_TEST_TOLERANCE 1.10
  25
  26 // SPSA options
  27 #define NUM_FILTER_COEFF 32
  28 #define NUM_ITER 5000
  29 #define A NUM_ITER/10  // approx
  30 #define INITIAL_A 0.005 // A bit of trial and error...
  31 #define INITIAL_C 0.02  // This too.
  32 #define GAMMA 0.166
  33 #define ALPHA 1.0
  34
  35 static float hysteresis_limit = 3000.0 / 32768.0;
  36 static bool do_calibrate = true;
  37 static bool output_cycles_plot = false;
  38 static bool do_crop = false;
  39 static float crop_start = 0.0f, crop_end = HUGE_VAL;
  40
  41 static bool use_fir_filter = false;
  42 static float filter_coeff[NUM_FILTER_COEFF] = { 1.0f };  // The rest is filled with 0.
  43 static bool use_rc_filter = false;
  44 static float rc_filter_freq;
  45 static bool output_filtered = false;
  46
  47 static bool quiet = false;
  48 static bool do_auto_level = false;
  49 static bool output_leveled = false;
  50 static std::vector<float> train_snap_points;
  51 static bool do_train = false;
  52
  53 // The minimum estimated sound level (for do_auto_level) at any given point.
  54 // If you decrease this, you'll be able to amplify really silent signals
  55 // by more, but you'll also increase the level of silent (ie. noise-only) segments,
  56 // possibly caused misdetected pulses in these segments.
  57 static float min_level = 0.05f;
  58
  59 // between [x,x+1]
  60 double find_zerocrossing(const std::vector<float> &pcm, int x)
  61 {
  62         if (pcm[x] == 0) {
  63                 return x;
  64         }
  65         if (pcm[x + 1] == 0) {
  66                 return x + 1;
  67         }
  68
  69         assert(pcm[x + 1] < 0);
  70         assert(pcm[x] > 0);
  71
  72         double upper = x;
  73         double lower = x + 1;
  74         while (lower - upper > 1e-3) {
  75                 double mid = 0.5f * (upper + lower);
  76                 if (lanczos_interpolate(pcm, mid) > 0) {
  77                         upper = mid;
  78                 } else {
  79                         lower = mid;
  80                 }
  81         }
  82
  83         return 0.5f * (upper + lower);
  84 }
  85
  86 struct pulse {
  87         double time;  // in seconds from start
  88         double len;   // in seconds
  89 };
  90
  91 // Calibrate on the first ~25k pulses (skip a few, just to be sure).
  92 double calibrate(const std::vector<pulse> &pulses) {
  93         if (pulses.size() < SYNC_PULSE_END) {
  94                 fprintf(stderr, "Too few pulses, not calibrating!\n");
  95                 return 1.0;
  96         }
  97
  98         int sync_pulse_end = -1;
  99         double sync_pulse_stddev = -1.0;
 100
 101         // Compute the standard deviation (to check for uneven speeds).
 102         // If it suddenly skyrockets, we assume that sync ended earlier
 103         // than we thought (it should be 25000 cycles), and that we should
 104         // calibrate on fewer cycles.
 105         for (int try_end : { 2000, 4000, 5000, 7500, 10000, 15000, SYNC_PULSE_END }) {
 106                 double sum2 = 0.0;
 107                 for (int i = SYNC_PULSE_START; i < try_end; ++i) {
 108                         double cycles = pulses[i].len * C64_FREQUENCY;
 109                         sum2 += (cycles - SYNC_PULSE_LENGTH) * (cycles - SYNC_PULSE_LENGTH);
 110                 }
 111                 double stddev = sqrt(sum2 / (try_end - SYNC_PULSE_START - 1));
 112                 if (sync_pulse_end != -1 && stddev > 5.0 && stddev / sync_pulse_stddev > 1.3) {
 113                         fprintf(stderr, "Stopping at %d sync pulses because standard deviation would be too big (%.2f cycles); shorter-than-usual trailer?\n",
 114                                 sync_pulse_end, stddev);
 115                         break;
 116                 }
 117                 sync_pulse_end = try_end;
 118                 sync_pulse_stddev = stddev;
 119         }
 120         if (!quiet) {
 121                 fprintf(stderr, "Sync pulse length standard deviation: %.2f cycles\n",
 122                         sync_pulse_stddev);
 123         }
 124
 125         double sum = 0.0;
 126         for (int i = SYNC_PULSE_START; i < sync_pulse_end; ++i) {
 127                 sum += pulses[i].len;
 128         }
 129         double mean_length = C64_FREQUENCY * sum / (sync_pulse_end - SYNC_PULSE_START);
 130         double calibration_factor = SYNC_PULSE_LENGTH / mean_length;
 131         if (!quiet) {
 132                 fprintf(stderr, "Calibrated sync pulse length: %.2f -> %.2f (change %+.2f%%)\n",
 133                         mean_length, SYNC_PULSE_LENGTH, 100.0 * (calibration_factor - 1.0));
 134         }
 135
 136         // Check for pulses outside +/- 10% (sign of misdetection).
 137         for (int i = SYNC_PULSE_START; i < sync_pulse_end; ++i) {
 138                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 139                 if (cycles < SYNC_PULSE_LENGTH / SYNC_TEST_TOLERANCE || cycles > SYNC_PULSE_LENGTH * SYNC_TEST_TOLERANCE) {
 140                         fprintf(stderr, "Sync cycle with downflank at %.6f was detected at %.0f cycles; misdetect?\n",
 141                                 pulses[i].time, cycles);
 142                 }
 143         }
 144
 145         return calibration_factor;
 146 }
 147
 148 void output_tap(const std::vector<pulse>& pulses, double calibration_factor)
 149 {
 150         std::vector<char> tap_data;
 151         for (unsigned i = 0; i < pulses.size(); ++i) {
 152                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 153                 int len = lrintf(cycles / TAP_RESOLUTION);
 154                 if (i > SYNC_PULSE_END && (cycles < 100 || cycles > 800)) {
 155                         fprintf(stderr, "Cycle with downflank at %.6f was detected at %.0f cycles; misdetect?\n",
 156                                         pulses[i].time, cycles);
 157                 }
 158                 if (len <= 255) {
 159                         tap_data.push_back(len);
 160                 } else {
 161                         int overflow_len = lrintf(cycles);
 162                         tap_data.push_back(0);
 163                         tap_data.push_back(overflow_len & 0xff);
 164                         tap_data.push_back((overflow_len >> 8) & 0xff);
 165                         tap_data.push_back(overflow_len >> 16);
 166                 }
 167         }
 168
 169         tap_header hdr;
 170         memcpy(hdr.identifier, "C64-TAPE-RAW", 12);
 171         hdr.version = 1;
 172         hdr.reserved[0] = hdr.reserved[1] = hdr.reserved[2] = 0;
 173         hdr.data_len = tap_data.size();
 174
 175         fwrite(&hdr, sizeof(hdr), 1, stdout);
 176         fwrite(tap_data.data(), tap_data.size(), 1, stdout);
 177 }
 178
 179 static struct option long_options[] = {
 180         {"auto-level",       0,                 0, 'a' },
 181         {"output-leveled",   0,                 0, 'A' },
 182         {"no-calibrate",     0,                 0, 's' },
 183         {"plot-cycles",      0,                 0, 'p' },
 184         {"hysteresis-limit", required_argument, 0, 'l' },
 185         {"filter",           required_argument, 0, 'f' },
 186         {"rc-filter",        required_argument, 0, 'r' },
 187         {"output-filtered",  0,                 0, 'F' },
 188         {"crop",             required_argument, 0, 'c' },
 189         {"quiet",            0,                 0, 'q' },
 190         {"help",             0,                 0, 'h' },
 191         {0,                  0,                 0, 0   }
 192 };
 193
 194 void help()
 195 {
 196         fprintf(stderr, "decode [OPTIONS] AUDIO-FILE > TAP-FILE\n");
 197         fprintf(stderr, "\n");
 198         fprintf(stderr, "  -a, --auto-level             automatically adjust amplitude levels throughout the file\n");
 199         fprintf(stderr, "  -A, --output-leveled         output leveled waveform to leveled.raw\n");
 200         fprintf(stderr, "  -m, --min-level              minimum estimated sound level (0..32768) for --auto-level\n");
 201         fprintf(stderr, "  -s, --no-calibrate           do not try to calibrate on sync pulse length\n");
 202         fprintf(stderr, "  -p, --plot-cycles            output debugging info to cycles.plot\n");
 203         fprintf(stderr, "  -l, --hysteresis-limit VAL   change amplitude threshold for ignoring pulses (0..32768)\n");
 204         fprintf(stderr, "  -f, --filter C1:C2:C3:...    specify FIR filter (up to %d coefficients)\n", NUM_FILTER_COEFF);
 205         fprintf(stderr, "  -r, --rc-filter FREQ         send signal through a highpass RC filter with given frequency (in Hertz)\n");
 206         fprintf(stderr, "  -F, --output-filtered        output filtered waveform to filtered.raw\n");
 207         fprintf(stderr, "  -c, --crop START[:END]       use only the given part of the file\n");
 208         fprintf(stderr, "  -t, --train LEN1:LEN2:...    train a filter for detecting any of the given number of cycles\n");
 209         fprintf(stderr, "                               (implies --no-calibrate and --quiet unless overridden)\n");
 210         fprintf(stderr, "  -q, --quiet                  suppress some informational messages\n");
 211         fprintf(stderr, "  -h, --help                   display this help, then exit\n");
 212         exit(1);
 213 }
 214
 215 void parse_options(int argc, char **argv)
 216 {
 217         for ( ;; ) {
 218                 int option_index = 0;
 219                 int c = getopt_long(argc, argv, "aAm:spl:f:r:Fc:t:qh", long_options, &option_index);
 220                 if (c == -1)
 221                         break;
 222
 223                 switch (c) {
 224                 case 'a':
 225                         do_auto_level = true;
 226                         break;
 227
 228                 case 'A':
 229                         output_leveled = true;
 230                         break;
 231
 232                 case 'm':
 233                         min_level = atof(optarg) / 32768.0;
 234                         break;
 235
 236                 case 's':
 237                         do_calibrate = false;
 238                         break;
 239
 240                 case 'p':
 241                         output_cycles_plot = true;
 242                         break;
 243
 244                 case 'l':
 245                         hysteresis_limit = atof(optarg) / 32768.0;
 246                         break;
 247
 248                 case 'f': {
 249                         const char *coeffstr = strtok(optarg, ": ");
 250                         int coeff_index = 0;
 251                         while (coeff_index < NUM_FILTER_COEFF && coeffstr != NULL) {
 252                                 filter_coeff[coeff_index++] = atof(coeffstr);
 253                                 coeffstr = strtok(NULL, ": ");
 254                         }
 255                         use_fir_filter = true;
 256                         break;
 257                 }
 258
 259                 case 'r':
 260                         use_rc_filter = true;
 261                         rc_filter_freq = atof(optarg);
 262                         break;
 263
 264                 case 'F':
 265                         output_filtered = true;
 266                         break;
 267
 268                 case 'c': {
 269                         const char *cropstr = strtok(optarg, ":");
 270                         crop_start = atof(cropstr);
 271                         cropstr = strtok(NULL, ":");
 272                         if (cropstr == NULL) {
 273                                 crop_end = HUGE_VAL;
 274                         } else {
 275                                 crop_end = atof(cropstr);
 276                         }
 277                         do_crop = true;
 278                         break;
 279                 }
 280
 281                 case 't': {
 282                         const char *cyclestr = strtok(optarg, ":");
 283                         while (cyclestr != NULL) {
 284                                 train_snap_points.push_back(atof(cyclestr));
 285                                 cyclestr = strtok(NULL, ":");
 286                         }
 287                         do_train = true;
 288
 289                         // Set reasonable defaults (can be overridden later on the command line).
 290                         do_calibrate = false;
 291                         quiet = true;
 292                         break;
 293                 }
 294
 295                 case 'q':
 296                         quiet = true;
 297                         break;
 298
 299                 case 'h':
 300                 default:
 301                         help();
 302                         exit(1);
 303                 }
 304         }
 305 }
 306
 307 std::vector<float> crop(const std::vector<float>& pcm, float crop_start, float crop_end, int sample_rate)
 308 {
 309         size_t start_sample, end_sample;
 310         if (crop_start >= 0.0f) {
 311                 start_sample = std::min<size_t>(lrintf(crop_start * sample_rate), pcm.size());
 312         }
 313         if (crop_end >= 0.0f) {
 314                 end_sample = std::min<size_t>(lrintf(crop_end * sample_rate), pcm.size());
 315         }
 316         return std::vector<float>(pcm.begin() + start_sample, pcm.begin() + end_sample);
 317 }
 318
 319 // TODO: Support AVX here.
 320 std::vector<float> do_fir_filter(const std::vector<float>& pcm, const float* filter)
 321 {
 322         std::vector<float> filtered_pcm;
 323         filtered_pcm.reserve(pcm.size());
 324         for (unsigned i = NUM_FILTER_COEFF; i < pcm.size(); ++i) {
 325                 float s = 0.0f;
 326                 for (int j = 0; j < NUM_FILTER_COEFF; ++j) {
 327                         s += filter[j] * pcm[i - j];
 328                 }
 329                 filtered_pcm.push_back(s);
 330         }
 331
 332         if (output_filtered) {
 333                 FILE *fp = fopen("filtered.raw", "wb");
 334                 fwrite(filtered_pcm.data(), filtered_pcm.size() * sizeof(filtered_pcm[0]), 1, fp);
 335                 fclose(fp);
 336         }
 337
 338         return filtered_pcm;
 339 }
 340
 341 std::vector<float> do_rc_filter(const std::vector<float>& pcm, float freq, int sample_rate)
 342 {
 343         std::vector<float> filtered_pcm;
 344         filtered_pcm.resize(pcm.size());
 345         Filter filter = Filter::hpf(M_PI * freq / sample_rate);
 346         for (unsigned i = 0; i < pcm.size(); ++i) {
 347                 filtered_pcm[i] = filter.update(pcm[i]);
 348         }
 349
 350         if (output_filtered) {
 351                 FILE *fp = fopen("filtered.raw", "wb");
 352                 fwrite(filtered_pcm.data(), filtered_pcm.size() * sizeof(filtered_pcm[0]), 1, fp);
 353                 fclose(fp);
 354         }
 355
 356         return filtered_pcm;
 357 }
 358
 359 std::vector<pulse> detect_pulses(const std::vector<float> &pcm, int sample_rate)
 360 {
 361         std::vector<pulse> pulses;
 362
 363         // Find the flanks.
 364         int last_bit = -1;
 365         double last_downflank = -1;
 366         for (unsigned i = 0; i < pcm.size(); ++i) {
 367                 int bit = (pcm[i] > 0) ? 1 : 0;
 368                 if (bit == 0 && last_bit == 1) {
 369                         // Check if we ever go up above <hysteresis_limit> before we dip down again.
 370                         bool true_pulse = false;
 371                         unsigned j;
 372                         int min_level_after = 32767;
 373                         for (j = i; j < pcm.size(); ++j) {
 374                                 min_level_after = std::min<int>(min_level_after, pcm[j]);
 375                                 if (pcm[j] > 0) break;
 376                                 if (pcm[j] < -hysteresis_limit) {
 377                                         true_pulse = true;
 378                                         break;
 379                                 }
 380                         }
 381
 382                         if (!true_pulse) {
 383 #if 0
 384                                 fprintf(stderr, "Ignored down-flank at %.6f seconds due to hysteresis (%d < %d).\n",
 385                                         double(i) / sample_rate, -min_level_after, hysteresis_limit);
 386 #endif
 387                                 i = j;
 388                                 continue;
 389                         }
 390
 391                         // down-flank!
 392                         double t = find_zerocrossing(pcm, i - 1) * (1.0 / sample_rate) + crop_start;
 393                         if (last_downflank > 0) {
 394                                 pulse p;
 395                                 p.time = t;
 396                                 p.len = t - last_downflank;
 397                                 pulses.push_back(p);
 398                         }
 399                         last_downflank = t;
 400                 }
 401                 last_bit = bit;
 402         }
 403         return pulses;
 404 }
 405
 406 void output_cycle_plot(const std::vector<pulse> &pulses, double calibration_factor)
 407 {
 408         FILE *fp = fopen("cycles.plot", "w");
 409         for (unsigned i = 0; i < pulses.size(); ++i) {
 410                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 411                 fprintf(fp, "%f %f\n", pulses[i].time, cycles);
 412         }
 413         fclose(fp);
 414 }
 415
 416 std::pair<int, double> find_closest_point(double x, const std::vector<float> &points)
 417 {
 418         int best_point = 0;
 419         double best_dist = (x - points[0]) * (x - points[0]);
 420         for (unsigned j = 1; j < train_snap_points.size(); ++j) {
 421                 double dist = (x - points[j]) * (x - points[j]);
 422                 if (dist < best_dist) {
 423                         best_point = j;
 424                         best_dist = dist;
 425                 }
 426         }
 427         return std::make_pair(best_point, best_dist);
 428 }
 429
 430 float eval_badness(const std::vector<pulse>& pulses, double calibration_factor)
 431 {
 432         double sum_badness = 0.0;
 433         for (unsigned i = 0; i < pulses.size(); ++i) {
 434                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 435                 if (cycles > 2000.0) cycles = 2000.0;  // Don't make pauses arbitrarily bad.
 436                 std::pair<int, double> selected_point_and_sq_dist = find_closest_point(cycles, train_snap_points);
 437                 sum_badness += selected_point_and_sq_dist.second;
 438         }
 439         return sqrt(sum_badness / (pulses.size() - 1));
 440 }
 441
 442 void find_kmeans(const std::vector<pulse> &pulses, double calibration_factor, const std::vector<float> &initial_centers)
 443 {
 444         std::vector<float> last_centers = initial_centers;
 445         std::vector<float> sums;
 446         std::vector<float> num;
 447         sums.resize(initial_centers.size());
 448         num.resize(initial_centers.size());
 449         for ( ;; ) {
 450                 for (unsigned i = 0; i < initial_centers.size(); ++i) {
 451                         sums[i] = 0.0f;
 452                         num[i] = 0;
 453                 }
 454                 for (unsigned i = 0; i < pulses.size(); ++i) {
 455                         double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 456                         // Ignore heavy outliers, which are almost always long pauses.
 457                         if (cycles > 2000.0) {
 458                                 continue;
 459                         }
 460                         std::pair<int, double> selected_point_and_sq_dist = find_closest_point(cycles, last_centers);
 461                         int p = selected_point_and_sq_dist.first;
 462                         sums[p] += cycles;
 463                         ++num[p];
 464                 }
 465                 bool any_moved = false;
 466                 for (unsigned i = 0; i < initial_centers.size(); ++i) {
 467                         if (num[i] == 0) {
 468                                 printf("K-means broke down, can't output new reference training points\n");
 469                                 return;
 470                         }
 471                         float new_center = sums[i] / num[i];
 472                         if (fabs(new_center - last_centers[i]) > 1e-3) {
 473                                 any_moved = true;
 474                         }
 475                         last_centers[i] = new_center;
 476                 }
 477                 if (!any_moved) {
 478                         break;
 479                 }
 480         }
 481         printf("New reference training points:");
 482         for (unsigned i = 0; i < last_centers.size(); ++i) {
 483                 printf(" %.3f", last_centers[i]);
 484         }
 485         printf("\n");
 486 }
 487
 488 void spsa_train(const std::vector<float> &pcm, int sample_rate)
 489 {
 490         float filter[NUM_FILTER_COEFF] = { 1.0f };  // The rest is filled with 0.
 491
 492         float start_c = INITIAL_C;
 493         double best_badness = HUGE_VAL;
 494
 495         for (int n = 1; n < NUM_ITER; ++n) {
 496                 float a = INITIAL_A * pow(n + A, -ALPHA);
 497                 float c = start_c * pow(n, -GAMMA);
 498
 499                 // find a random perturbation
 500                 float p[NUM_FILTER_COEFF];
 501                 float filter1[NUM_FILTER_COEFF], filter2[NUM_FILTER_COEFF];
 502                 for (int i = 0; i < NUM_FILTER_COEFF; ++i) {
 503                         p[i] = (rand() % 2) ? 1.0 : -1.0;
 504                         filter1[i] = std::max(std::min(filter[i] - c * p[i], 1.0f), -1.0f);
 505                         filter2[i] = std::max(std::min(filter[i] + c * p[i], 1.0f), -1.0f);
 506                 }
 507
 508                 std::vector<pulse> pulses1 = detect_pulses(do_fir_filter(pcm, filter1), sample_rate);
 509                 std::vector<pulse> pulses2 = detect_pulses(do_fir_filter(pcm, filter2), sample_rate);
 510                 float badness1 = eval_badness(pulses1, 1.0);
 511                 float badness2 = eval_badness(pulses2, 1.0);
 512
 513                 // Find the gradient estimator
 514                 float g[NUM_FILTER_COEFF];
 515                 for (int i = 0; i < NUM_FILTER_COEFF; ++i) {
 516                         g[i] = (badness2 - badness1) / (2.0 * c * p[i]);
 517                         filter[i] -= a * g[i];
 518                         filter[i] = std::max(std::min(filter[i], 1.0f), -1.0f);
 519                 }
 520                 if (badness2 < badness1) {
 521                         std::swap(badness1, badness2);
 522                         std::swap(filter1, filter2);
 523                         std::swap(pulses1, pulses2);
 524                 }
 525                 if (badness1 < best_badness) {
 526                         printf("\nNew best filter (badness=%f):", badness1);
 527                         for (int i = 0; i < NUM_FILTER_COEFF; ++i) {
 528                                 printf(" %.5f", filter1[i]);
 529                         }
 530                         best_badness = badness1;
 531                         printf("\n");
 532
 533                         find_kmeans(pulses1, 1.0, train_snap_points);
 534
 535                         if (output_cycles_plot) {
 536                                 output_cycle_plot(pulses1, 1.0);
 537                         }
 538                 }
 539                 printf("%d ", n);
 540                 fflush(stdout);
 541         }
 542 }
 543
 544 int main(int argc, char **argv)
 545 {
 546         parse_options(argc, argv);
 547
 548         make_lanczos_weight_table();
 549         std::vector<float> pcm;
 550         int sample_rate;
 551         if (!read_audio_file(argv[optind], &pcm, &sample_rate)) {
 552                 exit(1);
 553         }
 554
 555         if (do_crop) {
 556                 pcm = crop(pcm, crop_start, crop_end, sample_rate);
 557         }
 558
 559         if (use_fir_filter) {
 560                 pcm = do_fir_filter(pcm, filter_coeff);
 561         }
 562
 563         if (use_rc_filter) {
 564                 pcm = do_rc_filter(pcm, rc_filter_freq, sample_rate);
 565         }
 566
 567         if (do_auto_level) {
 568                 pcm = level_samples(pcm, min_level, sample_rate);
 569                 if (output_leveled) {
 570                         FILE *fp = fopen("leveled.raw", "wb");
 571                         fwrite(pcm.data(), pcm.size() * sizeof(pcm[0]), 1, fp);
 572                         fclose(fp);
 573                 }
 574         }
 575
 576 #if 0
 577         for (int i = 0; i < LEN; ++i) {
 578                 in[i] += rand() % 10000;
 579         }
 580 #endif
 581
 582 #if 0
 583         for (int i = 0; i < LEN; ++i) {
 584                 printf("%d\n", in[i]);
 585         }
 586 #endif
 587
 588         if (do_train) {
 589                 spsa_train(pcm, sample_rate);
 590                 exit(0);
 591         }
 592
 593         std::vector<pulse> pulses = detect_pulses(pcm, sample_rate);
 594
 595         double calibration_factor = 1.0;
 596         if (do_calibrate) {
 597                 calibration_factor = calibrate(pulses);
 598         }
 599
 600         if (output_cycles_plot) {
 601                 output_cycle_plot(pulses, calibration_factor);
 602         }
 603
 604         output_tap(pulses, calibration_factor);
 605 }