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 = 0.1;
  36 static float hysteresis_lower_limit = -0.1;
  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 frequency to filter on (for do_auto_level), in Hertz.
  55 // Larger values makes the compressor react faster, but if it is too large,
  56 // you'll ruin the waveforms themselves.
  57 static float auto_level_freq = 200.0;
  58
  59 // The minimum estimated sound level (for do_auto_level) at any given point.
  60 // If you decrease this, you'll be able to amplify really silent signals
  61 // by more, but you'll also increase the level of silent (ie. noise-only) segments,
  62 // possibly caused misdetected pulses in these segments.
  63 static float min_level = 0.05f;
  64
  65 // search for the value <limit> between [x,x+1]
  66 double find_crossing(const std::vector<float> &pcm, int x, float limit)
  67 {
  68         double upper = x;
  69         double lower = x + 1;
  70         while (lower - upper > 1e-3) {
  71                 double mid = 0.5f * (upper + lower);
  72                 if (lanczos_interpolate(pcm, mid) > limit) {
  73                         upper = mid;
  74                 } else {
  75                         lower = mid;
  76                 }
  77         }
  78
  79         return 0.5f * (upper + lower);
  80 }
  81
  82 struct pulse {
  83         double time;  // in seconds from start
  84         double len;   // in seconds
  85 };
  86
  87 // Calibrate on the first ~25k pulses (skip a few, just to be sure).
  88 double calibrate(const std::vector<pulse> &pulses) {
  89         if (pulses.size() < SYNC_PULSE_END) {
  90                 fprintf(stderr, "Too few pulses, not calibrating!\n");
  91                 return 1.0;
  92         }
  93
  94         int sync_pulse_end = -1;
  95         double sync_pulse_stddev = -1.0;
  96
  97         // Compute the standard deviation (to check for uneven speeds).
  98         // If it suddenly skyrockets, we assume that sync ended earlier
  99         // than we thought (it should be 25000 cycles), and that we should
 100         // calibrate on fewer cycles.
 101         for (int try_end : { 2000, 4000, 5000, 7500, 10000, 15000, SYNC_PULSE_END }) {
 102                 double sum2 = 0.0;
 103                 for (int i = SYNC_PULSE_START; i < try_end; ++i) {
 104                         double cycles = pulses[i].len * C64_FREQUENCY;
 105                         sum2 += (cycles - SYNC_PULSE_LENGTH) * (cycles - SYNC_PULSE_LENGTH);
 106                 }
 107                 double stddev = sqrt(sum2 / (try_end - SYNC_PULSE_START - 1));
 108                 if (sync_pulse_end != -1 && stddev > 5.0 && stddev / sync_pulse_stddev > 1.3) {
 109                         fprintf(stderr, "Stopping at %d sync pulses because standard deviation would be too big (%.2f cycles); shorter-than-usual trailer?\n",
 110                                 sync_pulse_end, stddev);
 111                         break;
 112                 }
 113                 sync_pulse_end = try_end;
 114                 sync_pulse_stddev = stddev;
 115         }
 116         if (!quiet) {
 117                 fprintf(stderr, "Sync pulse length standard deviation: %.2f cycles\n",
 118                         sync_pulse_stddev);
 119         }
 120
 121         double sum = 0.0;
 122         for (int i = SYNC_PULSE_START; i < sync_pulse_end; ++i) {
 123                 sum += pulses[i].len;
 124         }
 125         double mean_length = C64_FREQUENCY * sum / (sync_pulse_end - SYNC_PULSE_START);
 126         double calibration_factor = SYNC_PULSE_LENGTH / mean_length;
 127         if (!quiet) {
 128                 fprintf(stderr, "Calibrated sync pulse length: %.2f -> %.2f (change %+.2f%%)\n",
 129                         mean_length, SYNC_PULSE_LENGTH, 100.0 * (calibration_factor - 1.0));
 130         }
 131
 132         // Check for pulses outside +/- 10% (sign of misdetection).
 133         for (int i = SYNC_PULSE_START; i < sync_pulse_end; ++i) {
 134                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 135                 if (cycles < SYNC_PULSE_LENGTH / SYNC_TEST_TOLERANCE || cycles > SYNC_PULSE_LENGTH * SYNC_TEST_TOLERANCE) {
 136                         fprintf(stderr, "Sync cycle with downflank at %.6f was detected at %.0f cycles; misdetect?\n",
 137                                 pulses[i].time, cycles);
 138                 }
 139         }
 140
 141         return calibration_factor;
 142 }
 143
 144 void output_tap(const std::vector<pulse>& pulses, double calibration_factor)
 145 {
 146         std::vector<char> tap_data;
 147         for (unsigned i = 0; i < pulses.size(); ++i) {
 148                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 149                 int len = lrintf(cycles / TAP_RESOLUTION);
 150                 if (i > SYNC_PULSE_END && (cycles < 100 || cycles > 800)) {
 151                         fprintf(stderr, "Cycle with downflank at %.6f was detected at %.0f cycles; misdetect?\n",
 152                                         pulses[i].time, cycles);
 153                 }
 154                 if (len <= 255) {
 155                         tap_data.push_back(len);
 156                 } else {
 157                         int overflow_len = lrintf(cycles);
 158                         tap_data.push_back(0);
 159                         tap_data.push_back(overflow_len & 0xff);
 160                         tap_data.push_back((overflow_len >> 8) & 0xff);
 161                         tap_data.push_back(overflow_len >> 16);
 162                 }
 163         }
 164
 165         tap_header hdr;
 166         memcpy(hdr.identifier, "C64-TAPE-RAW", 12);
 167         hdr.version = 1;
 168         hdr.reserved[0] = hdr.reserved[1] = hdr.reserved[2] = 0;
 169         hdr.data_len = tap_data.size();
 170
 171         fwrite(&hdr, sizeof(hdr), 1, stdout);
 172         fwrite(tap_data.data(), tap_data.size(), 1, stdout);
 173 }
 174
 175 static struct option long_options[] = {
 176         {"auto-level",       0,                 0, 'a' },
 177         {"auto-level-freq",  required_argument, 0, 'b' },
 178         {"output-leveled",   0,                 0, 'A' },
 179         {"min-level",        required_argument, 0, 'm' },
 180         {"no-calibrate",     0,                 0, 's' },
 181         {"plot-cycles",      0,                 0, 'p' },
 182         {"hysteresis-limit", required_argument, 0, 'l' },
 183         {"filter",           required_argument, 0, 'f' },
 184         {"rc-filter",        required_argument, 0, 'r' },
 185         {"output-filtered",  0,                 0, 'F' },
 186         {"crop",             required_argument, 0, 'c' },
 187         {"quiet",            0,                 0, 'q' },
 188         {"help",             0,                 0, 'h' },
 189         {0,                  0,                 0, 0   }
 190 };
 191
 192 void help()
 193 {
 194         fprintf(stderr, "decode [OPTIONS] AUDIO-FILE > TAP-FILE\n");
 195         fprintf(stderr, "\n");
 196         fprintf(stderr, "  -a, --auto-level             automatically adjust amplitude levels throughout the file\n");
 197         fprintf(stderr, "  -b, --auto-level-freq        minimum frequency in Hertz of corrected level changes (default 200 Hz)\n");
 198         fprintf(stderr, "  -A, --output-leveled         output leveled waveform to leveled.raw\n");
 199         fprintf(stderr, "  -m, --min-level              minimum estimated sound level (0..1) for --auto-level\n");
 200         fprintf(stderr, "  -s, --no-calibrate           do not try to calibrate on sync pulse length\n");
 201         fprintf(stderr, "  -p, --plot-cycles            output debugging info to cycles.plot\n");
 202         fprintf(stderr, "  -l, --hysteresis-limit U[:L] change amplitude threshold for ignoring pulses (-1..1)\n");
 203         fprintf(stderr, "  -f, --filter C1:C2:C3:...    specify FIR filter (up to %d coefficients)\n", NUM_FILTER_COEFF);
 204         fprintf(stderr, "  -r, --rc-filter FREQ         send signal through a highpass RC filter with given frequency (in Hertz)\n");
 205         fprintf(stderr, "  -F, --output-filtered        output filtered waveform to filtered.raw\n");
 206         fprintf(stderr, "  -c, --crop START[:END]       use only the given part of the file\n");
 207         fprintf(stderr, "  -t, --train LEN1:LEN2:...    train a filter for detecting any of the given number of cycles\n");
 208         fprintf(stderr, "                               (implies --no-calibrate and --quiet unless overridden)\n");
 209         fprintf(stderr, "  -q, --quiet                  suppress some informational messages\n");
 210         fprintf(stderr, "  -h, --help                   display this help, then exit\n");
 211         exit(1);
 212 }
 213
 214 void parse_options(int argc, char **argv)
 215 {
 216         for ( ;; ) {
 217                 int option_index = 0;
 218                 int c = getopt_long(argc, argv, "ab:Am:spl:f:r:Fc:t:qh", long_options, &option_index);
 219                 if (c == -1)
 220                         break;
 221
 222                 switch (c) {
 223                 case 'a':
 224                         do_auto_level = true;
 225                         break;
 226
 227                 case 'b':
 228                         auto_level_freq = atof(optarg);
 229                         break;
 230
 231                 case 'A':
 232                         output_leveled = true;
 233                         break;
 234
 235                 case 'm':
 236                         min_level = atof(optarg);
 237                         break;
 238
 239                 case 's':
 240                         do_calibrate = false;
 241                         break;
 242
 243                 case 'p':
 244                         output_cycles_plot = true;
 245                         break;
 246
 247                 case 'l': {
 248                         const char *hyststr = strtok(optarg, ": ");
 249                         hysteresis_upper_limit = atof(hyststr);
 250                         hyststr = strtok(NULL, ": ");
 251                         if (hyststr == NULL) {
 252                                 hysteresis_lower_limit = -hysteresis_upper_limit;
 253                         } else {
 254                                 hysteresis_lower_limit = atof(hyststr);
 255                         }
 256                         break;
 257                 }
 258
 259                 case 'f': {
 260                         const char *coeffstr = strtok(optarg, ": ");
 261                         int coeff_index = 0;
 262                         while (coeff_index < NUM_FILTER_COEFF && coeffstr != NULL) {
 263                                 filter_coeff[coeff_index++] = atof(coeffstr);
 264                                 coeffstr = strtok(NULL, ": ");
 265                         }
 266                         use_fir_filter = true;
 267                         break;
 268                 }
 269
 270                 case 'r':
 271                         use_rc_filter = true;
 272                         rc_filter_freq = atof(optarg);
 273                         break;
 274
 275                 case 'F':
 276                         output_filtered = true;
 277                         break;
 278
 279                 case 'c': {
 280                         const char *cropstr = strtok(optarg, ":");
 281                         crop_start = atof(cropstr);
 282                         cropstr = strtok(NULL, ":");
 283                         if (cropstr == NULL) {
 284                                 crop_end = HUGE_VAL;
 285                         } else {
 286                                 crop_end = atof(cropstr);
 287                         }
 288                         do_crop = true;
 289                         break;
 290                 }
 291
 292                 case 't': {
 293                         const char *cyclestr = strtok(optarg, ":");
 294                         while (cyclestr != NULL) {
 295                                 train_snap_points.push_back(atof(cyclestr));
 296                                 cyclestr = strtok(NULL, ":");
 297                         }
 298                         do_train = true;
 299
 300                         // Set reasonable defaults (can be overridden later on the command line).
 301                         do_calibrate = false;
 302                         quiet = true;
 303                         break;
 304                 }
 305
 306                 case 'q':
 307                         quiet = true;
 308                         break;
 309
 310                 case 'h':
 311                 default:
 312                         help();
 313                         exit(1);
 314                 }
 315         }
 316 }
 317
 318 std::vector<float> crop(const std::vector<float>& pcm, float crop_start, float crop_end, int sample_rate)
 319 {
 320         size_t start_sample, end_sample;
 321         if (crop_start >= 0.0f) {
 322                 start_sample = std::min<size_t>(lrintf(crop_start * sample_rate), pcm.size());
 323         }
 324         if (crop_end >= 0.0f) {
 325                 end_sample = std::min<size_t>(lrintf(crop_end * sample_rate), pcm.size());
 326         }
 327         return std::vector<float>(pcm.begin() + start_sample, pcm.begin() + end_sample);
 328 }
 329
 330 // TODO: Support AVX here.
 331 std::vector<float> do_fir_filter(const std::vector<float>& pcm, const float* filter)
 332 {
 333         std::vector<float> filtered_pcm;
 334         filtered_pcm.reserve(pcm.size());
 335         for (unsigned i = NUM_FILTER_COEFF; i < pcm.size(); ++i) {
 336                 float s = 0.0f;
 337                 for (int j = 0; j < NUM_FILTER_COEFF; ++j) {
 338                         s += filter[j] * pcm[i - j];
 339                 }
 340                 filtered_pcm.push_back(s);
 341         }
 342
 343         if (output_filtered) {
 344                 FILE *fp = fopen("filtered.raw", "wb");
 345                 fwrite(filtered_pcm.data(), filtered_pcm.size() * sizeof(filtered_pcm[0]), 1, fp);
 346                 fclose(fp);
 347         }
 348
 349         return filtered_pcm;
 350 }
 351
 352 std::vector<float> do_rc_filter(const std::vector<float>& pcm, float freq, int sample_rate)
 353 {
 354         // This is only a 6 dB/oct filter, which seemingly works better
 355         // than the Filter class, which is a standard biquad (12 dB/oct).
 356         // The b/c calculations come from libnyquist (atone.c);
 357         // I haven't checked, but I suppose they fall out of the bilinear
 358         // transform of the transfer function H(s) = s/(s + w).
 359         std::vector<float> filtered_pcm;
 360         filtered_pcm.resize(pcm.size());
 361         const float b = 2.0f - cos(2.0 * M_PI * freq / sample_rate);
 362         const float c = b - sqrt(b * b - 1.0f);
 363         float prev_in = 0.0f;
 364         float prev_out = 0.0f;
 365         for (unsigned i = 0; i < pcm.size(); ++i) {
 366                 float in = pcm[i];
 367                 float out = c * (prev_out + in - prev_in);
 368                 filtered_pcm[i] = out;
 369                 prev_in = in;
 370                 prev_out = out;
 371         }
 372
 373         if (output_filtered) {
 374                 FILE *fp = fopen("filtered.raw", "wb");
 375                 fwrite(filtered_pcm.data(), filtered_pcm.size() * sizeof(filtered_pcm[0]), 1, fp);
 376                 fclose(fp);
 377         }
 378
 379         return filtered_pcm;
 380 }
 381
 382 std::vector<pulse> detect_pulses(const std::vector<float> &pcm, int sample_rate)
 383 {
 384         std::vector<pulse> pulses;
 385
 386         // Find the flanks.
 387         enum State { START, ABOVE, BELOW } state = START;
 388         double last_downflank = -1;
 389         for (unsigned i = 0; i < pcm.size(); ++i) {
 390                 if (pcm[i] > hysteresis_upper_limit) {
 391                         state = ABOVE;
 392                 } else if (pcm[i] < hysteresis_lower_limit) {
 393                         if (state == ABOVE) {
 394                                 // down-flank!
 395                                 double t = find_crossing(pcm, i - 1, hysteresis_lower_limit) * (1.0 / sample_rate) + crop_start;
 396                                 if (last_downflank > 0) {
 397                                         pulse p;
 398                                         p.time = t;
 399                                         p.len = t - last_downflank;
 400                                         pulses.push_back(p);
 401                                 }
 402                                 last_downflank = t;
 403                         }
 404                         state = BELOW;
 405                 }
 406         }
 407         return pulses;
 408 }
 409
 410 void output_cycle_plot(const std::vector<pulse> &pulses, double calibration_factor)
 411 {
 412         FILE *fp = fopen("cycles.plot", "w");
 413         for (unsigned i = 0; i < pulses.size(); ++i) {
 414                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 415                 fprintf(fp, "%f %f\n", pulses[i].time, cycles);
 416         }
 417         fclose(fp);
 418 }
 419
 420 std::pair<int, double> find_closest_point(double x, const std::vector<float> &points)
 421 {
 422         int best_point = 0;
 423         double best_dist = (x - points[0]) * (x - points[0]);
 424         for (unsigned j = 1; j < train_snap_points.size(); ++j) {
 425                 double dist = (x - points[j]) * (x - points[j]);
 426                 if (dist < best_dist) {
 427                         best_point = j;
 428                         best_dist = dist;
 429                 }
 430         }
 431         return std::make_pair(best_point, best_dist);
 432 }
 433
 434 float eval_badness(const std::vector<pulse>& pulses, double calibration_factor)
 435 {
 436         double sum_badness = 0.0;
 437         for (unsigned i = 0; i < pulses.size(); ++i) {
 438                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 439                 if (cycles > 2000.0) cycles = 2000.0;  // Don't make pauses arbitrarily bad.
 440                 std::pair<int, double> selected_point_and_sq_dist = find_closest_point(cycles, train_snap_points);
 441                 sum_badness += selected_point_and_sq_dist.second;
 442         }
 443         return sqrt(sum_badness / (pulses.size() - 1));
 444 }
 445
 446 void find_kmeans(const std::vector<pulse> &pulses, double calibration_factor, const std::vector<float> &initial_centers)
 447 {
 448         std::vector<float> last_centers = initial_centers;
 449         std::vector<float> sums;
 450         std::vector<float> num;
 451         sums.resize(initial_centers.size());
 452         num.resize(initial_centers.size());
 453         for ( ;; ) {
 454                 for (unsigned i = 0; i < initial_centers.size(); ++i) {
 455                         sums[i] = 0.0f;
 456                         num[i] = 0;
 457                 }
 458                 for (unsigned i = 0; i < pulses.size(); ++i) {
 459                         double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 460                         // Ignore heavy outliers, which are almost always long pauses.
 461                         if (cycles > 2000.0) {
 462                                 continue;
 463                         }
 464                         std::pair<int, double> selected_point_and_sq_dist = find_closest_point(cycles, last_centers);
 465                         int p = selected_point_and_sq_dist.first;
 466                         sums[p] += cycles;
 467                         ++num[p];
 468                 }
 469                 bool any_moved = false;
 470                 for (unsigned i = 0; i < initial_centers.size(); ++i) {
 471                         if (num[i] == 0) {
 472                                 fprintf(stderr, "K-means broke down, can't output new reference training points\n");
 473                                 return;
 474                         }
 475                         float new_center = sums[i] / num[i];
 476                         if (fabs(new_center - last_centers[i]) > 1e-3) {
 477                                 any_moved = true;
 478                         }
 479                         last_centers[i] = new_center;
 480                 }
 481                 if (!any_moved) {
 482                         break;
 483                 }
 484         }
 485         fprintf(stderr, "New reference training points:");
 486         for (unsigned i = 0; i < last_centers.size(); ++i) {
 487                 fprintf(stderr, " %.3f", last_centers[i]);
 488         }
 489         fprintf(stderr, "\n");
 490 }
 491
 492 void spsa_train(const std::vector<float> &pcm, int sample_rate)
 493 {
 494         float filter[NUM_FILTER_COEFF] = { 1.0f };  // The rest is filled with 0.
 495
 496         float start_c = INITIAL_C;
 497         double best_badness = HUGE_VAL;
 498
 499         for (int n = 1; n < NUM_ITER; ++n) {
 500                 float a = INITIAL_A * pow(n + A, -ALPHA);
 501                 float c = start_c * pow(n, -GAMMA);
 502
 503                 // find a random perturbation
 504                 float p[NUM_FILTER_COEFF];
 505                 float filter1[NUM_FILTER_COEFF], filter2[NUM_FILTER_COEFF];
 506                 for (int i = 0; i < NUM_FILTER_COEFF; ++i) {
 507                         p[i] = (rand() % 2) ? 1.0 : -1.0;
 508                         filter1[i] = std::max(std::min(filter[i] - c * p[i], 1.0f), -1.0f);
 509                         filter2[i] = std::max(std::min(filter[i] + c * p[i], 1.0f), -1.0f);
 510                 }
 511
 512                 std::vector<pulse> pulses1 = detect_pulses(do_fir_filter(pcm, filter1), sample_rate);
 513                 std::vector<pulse> pulses2 = detect_pulses(do_fir_filter(pcm, filter2), sample_rate);
 514                 float badness1 = eval_badness(pulses1, 1.0);
 515                 float badness2 = eval_badness(pulses2, 1.0);
 516
 517                 // Find the gradient estimator
 518                 float g[NUM_FILTER_COEFF];
 519                 for (int i = 0; i < NUM_FILTER_COEFF; ++i) {
 520                         g[i] = (badness2 - badness1) / (2.0 * c * p[i]);
 521                         filter[i] -= a * g[i];
 522                         filter[i] = std::max(std::min(filter[i], 1.0f), -1.0f);
 523                 }
 524                 if (badness2 < badness1) {
 525                         std::swap(badness1, badness2);
 526                         std::swap(filter1, filter2);
 527                         std::swap(pulses1, pulses2);
 528                 }
 529                 if (badness1 < best_badness) {
 530                         printf("\nNew best filter (badness=%f):", badness1);
 531                         for (int i = 0; i < NUM_FILTER_COEFF; ++i) {
 532                                 printf(" %.5f", filter1[i]);
 533                         }
 534                         best_badness = badness1;
 535                         printf("\n");
 536
 537                         find_kmeans(pulses1, 1.0, train_snap_points);
 538
 539                         if (output_cycles_plot) {
 540                                 output_cycle_plot(pulses1, 1.0);
 541                         }
 542                 }
 543                 printf("%d ", n);
 544                 fflush(stdout);
 545         }
 546 }
 547
 548 int main(int argc, char **argv)
 549 {
 550         parse_options(argc, argv);
 551
 552         make_lanczos_weight_table();
 553         std::vector<float> pcm;
 554         int sample_rate;
 555         if (!read_audio_file(argv[optind], &pcm, &sample_rate)) {
 556                 exit(1);
 557         }
 558
 559         if (do_crop) {
 560                 pcm = crop(pcm, crop_start, crop_end, sample_rate);
 561         }
 562
 563         if (use_fir_filter) {
 564                 pcm = do_fir_filter(pcm, filter_coeff);
 565         }
 566
 567         if (use_rc_filter) {
 568                 pcm = do_rc_filter(pcm, rc_filter_freq, sample_rate);
 569         }
 570
 571         if (do_auto_level) {
 572                 pcm = level_samples(pcm, min_level, auto_level_freq, sample_rate);
 573                 if (output_leveled) {
 574                         FILE *fp = fopen("leveled.raw", "wb");
 575                         fwrite(pcm.data(), pcm.size() * sizeof(pcm[0]), 1, fp);
 576                         fclose(fp);
 577                 }
 578         }
 579
 580 #if 0
 581         for (int i = 0; i < LEN; ++i) {
 582                 in[i] += rand() % 10000;
 583         }
 584 #endif
 585
 586 #if 0
 587         for (int i = 0; i < LEN; ++i) {
 588                 printf("%d\n", in[i]);
 589         }
 590 #endif
 591
 592         if (do_train) {
 593                 spsa_train(pcm, sample_rate);
 594                 exit(0);
 595         }
 596
 597         std::vector<pulse> pulses = detect_pulses(pcm, sample_rate);
 598
 599         double calibration_factor = 1.0;
 600         if (do_calibrate) {
 601                 calibration_factor = calibrate(pulses);
 602         }
 603
 604         if (output_cycles_plot) {
 605                 output_cycle_plot(pulses, calibration_factor);
 606         }
 607
 608         output_tap(pulses, calibration_factor);
 609 }