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 #ifdef __AVX__
  11 #include <immintrin.h>
  12 #endif
  13 #include <vector>
  14 #include <algorithm>
  15
  16 #include "audioreader.h"
  17 #include "interpolate.h"
  18 #include "level.h"
  19 #include "tap.h"
  20 #include "filter.h"
  21
  22 #define BUFSIZE 4096
  23 #define C64_FREQUENCY 985248
  24 #define SYNC_PULSE_START 1000
  25 #define SYNC_PULSE_END 20000
  26 #define SYNC_PULSE_LENGTH 378.0
  27 #define SYNC_TEST_TOLERANCE 1.10
  28
  29 // SPSA options
  30 #define NUM_FILTER_COEFF 32
  31 #define NUM_SPSA_VALS (NUM_FILTER_COEFF + 2)
  32 #define NUM_ITER 5000
  33 #define A NUM_ITER/10  // approx
  34 #define INITIAL_A 0.005 // A bit of trial and error...
  35 #define INITIAL_C 0.02  // This too.
  36 #define GAMMA 0.166
  37 #define ALPHA 1.0
  38
  39 static float hysteresis_upper_limit = 0.1;
  40 static float hysteresis_lower_limit = -0.1;
  41 static bool do_calibrate = true;
  42 static bool output_cycles_plot = false;
  43 static bool do_crop = false;
  44 static float crop_start = 0.0f, crop_end = HUGE_VAL;
  45
  46 static bool use_fir_filter = false;
  47 static float filter_coeff[NUM_FILTER_COEFF] = { 1.0f };  // The rest is filled with 0.
  48 static bool use_rc_filter = false;
  49 static float rc_filter_freq;
  50 static bool output_filtered = false;
  51
  52 static bool quiet = false;
  53 static bool do_auto_level = false;
  54 static bool output_leveled = false;
  55 static std::vector<float> train_snap_points;
  56 static bool do_train = false;
  57
  58 // The frequency to filter on (for do_auto_level), in Hertz.
  59 // Larger values makes the compressor react faster, but if it is too large,
  60 // you'll ruin the waveforms themselves.
  61 static float auto_level_freq = 200.0;
  62
  63 // The minimum estimated sound level (for do_auto_level) at any given point.
  64 // If you decrease this, you'll be able to amplify really silent signals
  65 // by more, but you'll also increase the level of silent (ie. noise-only) segments,
  66 // possibly caused misdetected pulses in these segments.
  67 static float min_level = 0.05f;
  68
  69 // search for the value <limit> between [x,x+1]
  70 double find_crossing(const std::vector<float> &pcm, int x, float limit)
  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) > limit) {
  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         {"auto-level-freq",  required_argument, 0, 'b' },
 182         {"output-leveled",   0,                 0, 'A' },
 183         {"min-level",        required_argument, 0, 'm' },
 184         {"no-calibrate",     0,                 0, 's' },
 185         {"plot-cycles",      0,                 0, 'p' },
 186         {"hysteresis-limit", required_argument, 0, 'l' },
 187         {"filter",           required_argument, 0, 'f' },
 188         {"rc-filter",        required_argument, 0, 'r' },
 189         {"output-filtered",  0,                 0, 'F' },
 190         {"crop",             required_argument, 0, 'c' },
 191         {"quiet",            0,                 0, 'q' },
 192         {"help",             0,                 0, 'h' },
 193         {0,                  0,                 0, 0   }
 194 };
 195
 196 void help()
 197 {
 198         fprintf(stderr, "decode [OPTIONS] AUDIO-FILE > TAP-FILE\n");
 199         fprintf(stderr, "\n");
 200         fprintf(stderr, "  -a, --auto-level             automatically adjust amplitude levels throughout the file\n");
 201         fprintf(stderr, "  -b, --auto-level-freq        minimum frequency in Hertz of corrected level changes (default 200 Hz)\n");
 202         fprintf(stderr, "  -A, --output-leveled         output leveled waveform to leveled.raw\n");
 203         fprintf(stderr, "  -m, --min-level              minimum estimated sound level (0..1) for --auto-level\n");
 204         fprintf(stderr, "  -s, --no-calibrate           do not try to calibrate on sync pulse length\n");
 205         fprintf(stderr, "  -p, --plot-cycles            output debugging info to cycles.plot\n");
 206         fprintf(stderr, "  -l, --hysteresis-limit U[:L] change amplitude threshold for ignoring pulses (-1..1)\n");
 207         fprintf(stderr, "  -f, --filter C1:C2:C3:...    specify FIR filter (up to %d coefficients)\n", NUM_FILTER_COEFF);
 208         fprintf(stderr, "  -r, --rc-filter FREQ         send signal through a highpass RC filter with given frequency (in Hertz)\n");
 209         fprintf(stderr, "  -F, --output-filtered        output filtered waveform to filtered.raw\n");
 210         fprintf(stderr, "  -c, --crop START[:END]       use only the given part of the file\n");
 211         fprintf(stderr, "  -t, --train LEN1:LEN2:...    train a filter for detecting any of the given number of cycles\n");
 212         fprintf(stderr, "                               (implies --no-calibrate and --quiet unless overridden)\n");
 213         fprintf(stderr, "  -q, --quiet                  suppress some informational messages\n");
 214         fprintf(stderr, "  -h, --help                   display this help, then exit\n");
 215         exit(1);
 216 }
 217
 218 void parse_options(int argc, char **argv)
 219 {
 220         for ( ;; ) {
 221                 int option_index = 0;
 222                 int c = getopt_long(argc, argv, "ab:Am:spl:f:r:Fc:t:qh", long_options, &option_index);
 223                 if (c == -1)
 224                         break;
 225
 226                 switch (c) {
 227                 case 'a':
 228                         do_auto_level = true;
 229                         break;
 230
 231                 case 'b':
 232                         auto_level_freq = atof(optarg);
 233                         break;
 234
 235                 case 'A':
 236                         output_leveled = true;
 237                         break;
 238
 239                 case 'm':
 240                         min_level = atof(optarg);
 241                         break;
 242
 243                 case 's':
 244                         do_calibrate = false;
 245                         break;
 246
 247                 case 'p':
 248                         output_cycles_plot = true;
 249                         break;
 250
 251                 case 'l': {
 252                         const char *hyststr = strtok(optarg, ": ");
 253                         hysteresis_upper_limit = atof(hyststr);
 254                         hyststr = strtok(NULL, ": ");
 255                         if (hyststr == NULL) {
 256                                 hysteresis_lower_limit = -hysteresis_upper_limit;
 257                         } else {
 258                                 hysteresis_lower_limit = atof(hyststr);
 259                         }
 260                         break;
 261                 }
 262
 263                 case 'f': {
 264                         const char *coeffstr = strtok(optarg, ": ");
 265                         int coeff_index = 0;
 266                         while (coeff_index < NUM_FILTER_COEFF && coeffstr != NULL) {
 267                                 filter_coeff[coeff_index++] = atof(coeffstr);
 268                                 coeffstr = strtok(NULL, ": ");
 269                         }
 270                         use_fir_filter = true;
 271                         break;
 272                 }
 273
 274                 case 'r':
 275                         use_rc_filter = true;
 276                         rc_filter_freq = atof(optarg);
 277                         break;
 278
 279                 case 'F':
 280                         output_filtered = true;
 281                         break;
 282
 283                 case 'c': {
 284                         const char *cropstr = strtok(optarg, ":");
 285                         crop_start = atof(cropstr);
 286                         cropstr = strtok(NULL, ":");
 287                         if (cropstr == NULL) {
 288                                 crop_end = HUGE_VAL;
 289                         } else {
 290                                 crop_end = atof(cropstr);
 291                         }
 292                         do_crop = true;
 293                         break;
 294                 }
 295
 296                 case 't': {
 297                         const char *cyclestr = strtok(optarg, ":");
 298                         while (cyclestr != NULL) {
 299                                 train_snap_points.push_back(atof(cyclestr));
 300                                 cyclestr = strtok(NULL, ":");
 301                         }
 302                         do_train = true;
 303
 304                         // Set reasonable defaults (can be overridden later on the command line).
 305                         do_calibrate = false;
 306                         quiet = true;
 307                         break;
 308                 }
 309
 310                 case 'q':
 311                         quiet = true;
 312                         break;
 313
 314                 case 'h':
 315                 default:
 316                         help();
 317                         exit(1);
 318                 }
 319         }
 320 }
 321
 322 std::vector<float> crop(const std::vector<float>& pcm, float crop_start, float crop_end, int sample_rate)
 323 {
 324         size_t start_sample, end_sample;
 325         if (crop_start >= 0.0f) {
 326                 start_sample = std::min<size_t>(lrintf(crop_start * sample_rate), pcm.size());
 327         }
 328         if (crop_end >= 0.0f) {
 329                 end_sample = std::min<size_t>(lrintf(crop_end * sample_rate), pcm.size());
 330         }
 331         return std::vector<float>(pcm.begin() + start_sample, pcm.begin() + end_sample);
 332 }
 333
 334 std::vector<float> do_fir_filter(const std::vector<float>& pcm, const float* filter)
 335 {
 336         std::vector<float> filtered_pcm;
 337         filtered_pcm.resize(pcm.size());
 338         unsigned i = NUM_FILTER_COEFF;
 339 #ifdef __AVX__
 340         unsigned avx_end = i + ((pcm.size() - i) & ~7);
 341         for ( ; i < avx_end; i += 8) {
 342                 __m256 s = _mm256_setzero_ps();
 343                 for (int j = 0; j < NUM_FILTER_COEFF; ++j) {
 344                         __m256 f = _mm256_set1_ps(filter[j]);
 345                         s = _mm256_fmadd_ps(f, _mm256_load_ps(&pcm[i - j]), s);
 346                 }
 347                 _mm256_storeu_ps(&filtered_pcm[i], s);
 348         }
 349 #endif
 350         // Do what we couldn't do with AVX (which is everything for non-AVX machines)
 351         // as scalar code.
 352         for (; i < pcm.size(); ++i) {
 353                 float s = 0.0f;
 354                 for (int j = 0; j < NUM_FILTER_COEFF; ++j) {
 355                         s += filter[j] * pcm[i - j];
 356                 }
 357                 filtered_pcm[i] = s;
 358         }
 359
 360         if (output_filtered) {
 361                 FILE *fp = fopen("filtered.raw", "wb");
 362                 fwrite(filtered_pcm.data(), filtered_pcm.size() * sizeof(filtered_pcm[0]), 1, fp);
 363                 fclose(fp);
 364         }
 365
 366         return filtered_pcm;
 367 }
 368
 369 std::vector<float> do_rc_filter(const std::vector<float>& pcm, float freq, int sample_rate)
 370 {
 371         // This is only a 6 dB/oct filter, which seemingly works better
 372         // than the Filter class, which is a standard biquad (12 dB/oct).
 373         // The b/c calculations come from libnyquist (atone.c);
 374         // I haven't checked, but I suppose they fall out of the bilinear
 375         // transform of the transfer function H(s) = s/(s + w).
 376         std::vector<float> filtered_pcm;
 377         filtered_pcm.resize(pcm.size());
 378         const float b = 2.0f - cos(2.0 * M_PI * freq / sample_rate);
 379         const float c = b - sqrt(b * b - 1.0f);
 380         float prev_in = 0.0f;
 381         float prev_out = 0.0f;
 382         for (unsigned i = 0; i < pcm.size(); ++i) {
 383                 float in = pcm[i];
 384                 float out = c * (prev_out + in - prev_in);
 385                 filtered_pcm[i] = out;
 386                 prev_in = in;
 387                 prev_out = out;
 388         }
 389
 390         if (output_filtered) {
 391                 FILE *fp = fopen("filtered.raw", "wb");
 392                 fwrite(filtered_pcm.data(), filtered_pcm.size() * sizeof(filtered_pcm[0]), 1, fp);
 393                 fclose(fp);
 394         }
 395
 396         return filtered_pcm;
 397 }
 398
 399 std::vector<pulse> detect_pulses(const std::vector<float> &pcm, float hysteresis_upper_limit, float hysteresis_lower_limit, int sample_rate)
 400 {
 401         std::vector<pulse> pulses;
 402
 403         // Find the flanks.
 404         enum State { START, ABOVE, BELOW } state = START;
 405         double last_downflank = -1;
 406         for (unsigned i = 0; i < pcm.size(); ++i) {
 407                 if (pcm[i] > hysteresis_upper_limit) {
 408                         state = ABOVE;
 409                 } else if (pcm[i] < hysteresis_lower_limit) {
 410                         if (state == ABOVE) {
 411                                 // down-flank!
 412                                 double t = find_crossing(pcm, i - 1, hysteresis_lower_limit) * (1.0 / sample_rate) + crop_start;
 413                                 if (last_downflank > 0) {
 414                                         pulse p;
 415                                         p.time = t;
 416                                         p.len = t - last_downflank;
 417                                         pulses.push_back(p);
 418                                 }
 419                                 last_downflank = t;
 420                         }
 421                         state = BELOW;
 422                 }
 423         }
 424         return pulses;
 425 }
 426
 427 void output_cycle_plot(const std::vector<pulse> &pulses, double calibration_factor)
 428 {
 429         FILE *fp = fopen("cycles.plot", "w");
 430         for (unsigned i = 0; i < pulses.size(); ++i) {
 431                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 432                 fprintf(fp, "%f %f\n", pulses[i].time, cycles);
 433         }
 434         fclose(fp);
 435 }
 436
 437 std::pair<int, double> find_closest_point(double x, const std::vector<float> &points)
 438 {
 439         int best_point = 0;
 440         double best_dist = (x - points[0]) * (x - points[0]);
 441         for (unsigned j = 1; j < train_snap_points.size(); ++j) {
 442                 double dist = (x - points[j]) * (x - points[j]);
 443                 if (dist < best_dist) {
 444                         best_point = j;
 445                         best_dist = dist;
 446                 }
 447         }
 448         return std::make_pair(best_point, best_dist);
 449 }
 450
 451 float eval_badness(const std::vector<pulse>& pulses, double calibration_factor)
 452 {
 453         double sum_badness = 0.0;
 454         for (unsigned i = 0; i < pulses.size(); ++i) {
 455                 double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 456                 if (cycles > 2000.0) cycles = 2000.0;  // Don't make pauses arbitrarily bad.
 457                 std::pair<int, double> selected_point_and_sq_dist = find_closest_point(cycles, train_snap_points);
 458                 sum_badness += selected_point_and_sq_dist.second;
 459         }
 460         return sqrt(sum_badness / (pulses.size() - 1));
 461 }
 462
 463 void find_kmeans(const std::vector<pulse> &pulses, double calibration_factor, const std::vector<float> &initial_centers)
 464 {
 465         std::vector<float> last_centers = initial_centers;
 466         std::vector<float> sums;
 467         std::vector<float> num;
 468         sums.resize(initial_centers.size());
 469         num.resize(initial_centers.size());
 470         for ( ;; ) {
 471                 for (unsigned i = 0; i < initial_centers.size(); ++i) {
 472                         sums[i] = 0.0f;
 473                         num[i] = 0;
 474                 }
 475                 for (unsigned i = 0; i < pulses.size(); ++i) {
 476                         double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
 477                         // Ignore heavy outliers, which are almost always long pauses.
 478                         if (cycles > 2000.0) {
 479                                 continue;
 480                         }
 481                         std::pair<int, double> selected_point_and_sq_dist = find_closest_point(cycles, last_centers);
 482                         int p = selected_point_and_sq_dist.first;
 483                         sums[p] += cycles;
 484                         ++num[p];
 485                 }
 486                 bool any_moved = false;
 487                 for (unsigned i = 0; i < initial_centers.size(); ++i) {
 488                         if (num[i] == 0) {
 489                                 fprintf(stderr, "K-means broke down, can't output new reference training points\n");
 490                                 return;
 491                         }
 492                         float new_center = sums[i] / num[i];
 493                         if (fabs(new_center - last_centers[i]) > 1e-3) {
 494                                 any_moved = true;
 495                         }
 496                         last_centers[i] = new_center;
 497                 }
 498                 if (!any_moved) {
 499                         break;
 500                 }
 501         }
 502         fprintf(stderr, "New reference training points:");
 503         for (unsigned i = 0; i < last_centers.size(); ++i) {
 504                 fprintf(stderr, " %.3f", last_centers[i]);
 505         }
 506         fprintf(stderr, "\n");
 507 }
 508
 509 void spsa_train(const std::vector<float> &pcm, int sample_rate)
 510 {
 511         float vals[NUM_SPSA_VALS] = { hysteresis_upper_limit, hysteresis_lower_limit, 1.0f };  // The rest is filled with 0.
 512
 513         float start_c = INITIAL_C;
 514         double best_badness = HUGE_VAL;
 515
 516         for (int n = 1; n < NUM_ITER; ++n) {
 517                 float a = INITIAL_A * pow(n + A, -ALPHA);
 518                 float c = start_c * pow(n, -GAMMA);
 519
 520                 // find a random perturbation
 521                 float p[NUM_SPSA_VALS];
 522                 float vals1[NUM_SPSA_VALS], vals2[NUM_SPSA_VALS];
 523                 for (int i = 0; i < NUM_SPSA_VALS; ++i) {
 524                         p[i] = (rand() % 2) ? 1.0 : -1.0;
 525                         vals1[i] = std::max(std::min(vals[i] - c * p[i], 1.0f), -1.0f);
 526                         vals2[i] = std::max(std::min(vals[i] + c * p[i], 1.0f), -1.0f);
 527                 }
 528
 529                 std::vector<pulse> pulses1 = detect_pulses(do_fir_filter(pcm, vals1 + 2), vals1[0], vals1[1], sample_rate);
 530                 std::vector<pulse> pulses2 = detect_pulses(do_fir_filter(pcm, vals2 + 2), vals2[0], vals2[1], sample_rate);
 531                 float badness1 = eval_badness(pulses1, 1.0);
 532                 float badness2 = eval_badness(pulses2, 1.0);
 533
 534                 // Find the gradient estimator
 535                 float g[NUM_SPSA_VALS];
 536                 for (int i = 0; i < NUM_SPSA_VALS; ++i) {
 537                         g[i] = (badness2 - badness1) / (2.0 * c * p[i]);
 538                         vals[i] -= a * g[i];
 539                         vals[i] = std::max(std::min(vals[i], 1.0f), -1.0f);
 540                 }
 541                 if (badness2 < badness1) {
 542                         std::swap(badness1, badness2);
 543                         std::swap(vals1, vals2);
 544                         std::swap(pulses1, pulses2);
 545                 }
 546                 if (badness1 < best_badness) {
 547                         fprintf(stderr, "\nNew best filter (badness=%f):", badness1);
 548                         for (int i = 0; i < NUM_FILTER_COEFF; ++i) {
 549                                 fprintf(stderr, " %.5f", vals1[i + 2]);
 550                         }
 551                         fprintf(stderr, ", hysteresis limits = %f %f\n", vals1[0], vals1[1]);
 552                         best_badness = badness1;
 553
 554                         find_kmeans(pulses1, 1.0, train_snap_points);
 555
 556                         if (output_cycles_plot) {
 557                                 output_cycle_plot(pulses1, 1.0);
 558                         }
 559                 }
 560                 fprintf(stderr, "%d ", n);
 561                 fflush(stderr);
 562         }
 563 }
 564
 565 int main(int argc, char **argv)
 566 {
 567         parse_options(argc, argv);
 568
 569         make_lanczos_weight_table();
 570         std::vector<float> pcm;
 571         int sample_rate;
 572         if (!read_audio_file(argv[optind], &pcm, &sample_rate)) {
 573                 exit(1);
 574         }
 575
 576         if (do_crop) {
 577                 pcm = crop(pcm, crop_start, crop_end, sample_rate);
 578         }
 579
 580         if (use_fir_filter) {
 581                 pcm = do_fir_filter(pcm, filter_coeff);
 582         }
 583
 584         if (use_rc_filter) {
 585                 pcm = do_rc_filter(pcm, rc_filter_freq, sample_rate);
 586         }
 587
 588         if (do_auto_level) {
 589                 pcm = level_samples(pcm, min_level, auto_level_freq, sample_rate);
 590                 if (output_leveled) {
 591                         FILE *fp = fopen("leveled.raw", "wb");
 592                         fwrite(pcm.data(), pcm.size() * sizeof(pcm[0]), 1, fp);
 593                         fclose(fp);
 594                 }
 595         }
 596
 597 #if 0
 598         for (int i = 0; i < LEN; ++i) {
 599                 in[i] += rand() % 10000;
 600         }
 601 #endif
 602
 603 #if 0
 604         for (int i = 0; i < LEN; ++i) {
 605                 printf("%d\n", in[i]);
 606         }
 607 #endif
 608
 609         if (do_train) {
 610                 spsa_train(pcm, sample_rate);
 611                 exit(0);
 612         }
 613
 614         std::vector<pulse> pulses = detect_pulses(pcm, hysteresis_upper_limit, hysteresis_lower_limit, sample_rate);
 615
 616         double calibration_factor = 1.0;
 617         if (do_calibrate) {
 618                 calibration_factor = calibrate(pulses);
 619         }
 620
 621         if (output_cycles_plot) {
 622                 output_cycle_plot(pulses, calibration_factor);
 623         }
 624
 625         output_tap(pulses, calibration_factor);
 626 }