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