#include "audioreader.h"
#include "interpolate.h"
+#include "level.h"
#include "tap.h"
#define BUFSIZE 4096
#define SYNC_PULSE_LENGTH 378.0
#define SYNC_TEST_TOLERANCE 1.10
+// SPSA options
#define NUM_FILTER_COEFF 32
+#define NUM_ITER 5000
+#define A NUM_ITER/10 // approx
+#define INITIAL_A 0.005 // A bit of trial and error...
+#define INITIAL_C 0.02 // This too.
+#define GAMMA 0.166
+#define ALPHA 1.0
static float hysteresis_limit = 3000.0 / 32768.0;
static bool do_calibrate = true;
static bool output_cycles_plot = false;
static bool use_filter = false;
+static bool do_crop = false;
+static float crop_start = 0.0f, crop_end = HUGE_VAL;
static float filter_coeff[NUM_FILTER_COEFF] = { 1.0f }; // The rest is filled with 0.
static bool output_filtered = false;
static bool quiet = false;
+static bool do_auto_level = false;
+static bool output_leveled = false;
+static std::vector<float> train_snap_points;
+static bool do_train = false;
+
+// The minimum estimated sound level (for do_auto_level) at any given point.
+// If you decrease this, you'll be able to amplify really silent signals
+// by more, but you'll also increase the level of silent (ie. noise-only) segments,
+// possibly caused misdetected pulses in these segments.
+static float min_level = 0.05f;
// between [x,x+1]
double find_zerocrossing(const std::vector<float> &pcm, int x)
}
static struct option long_options[] = {
+ {"auto-level", 0, 0, 'a' },
+ {"output-leveled", 0, 0, 'A' },
{"no-calibrate", 0, 0, 's' },
{"plot-cycles", 0, 0, 'p' },
{"hysteresis-limit", required_argument, 0, 'l' },
{"filter", required_argument, 0, 'f' },
{"output-filtered", 0, 0, 'F' },
+ {"crop", required_argument, 0, 'c' },
{"quiet", 0, 0, 'q' },
{"help", 0, 0, 'h' },
{0, 0, 0, 0 }
{
fprintf(stderr, "decode [OPTIONS] AUDIO-FILE > TAP-FILE\n");
fprintf(stderr, "\n");
+ fprintf(stderr, " -a, --auto-level automatically adjust amplitude levels throughout the file\n");
+ fprintf(stderr, " -A, --output-leveled output leveled waveform to leveled.raw\n");
+ fprintf(stderr, " -m, --min-level minimum estimated sound level (0..32768) for --auto-level\n");
fprintf(stderr, " -s, --no-calibrate do not try to calibrate on sync pulse length\n");
fprintf(stderr, " -p, --plot-cycles output debugging info to cycles.plot\n");
fprintf(stderr, " -l, --hysteresis-limit VAL change amplitude threshold for ignoring pulses (0..32768)\n");
fprintf(stderr, " -f, --filter C1:C2:C3:... specify FIR filter (up to %d coefficients)\n", NUM_FILTER_COEFF);
fprintf(stderr, " -F, --output-filtered output filtered waveform to filtered.raw\n");
+ fprintf(stderr, " -c, --crop START[:END] use only the given part of the file\n");
+ fprintf(stderr, " -t, --train LEN1:LEN2:... train a filter for detecting any of the given number of cycles\n");
+ fprintf(stderr, " (implies --no-calibrate and --quiet unless overridden)\n");
fprintf(stderr, " -q, --quiet suppress some informational messages\n");
fprintf(stderr, " -h, --help display this help, then exit\n");
exit(1);
{
for ( ;; ) {
int option_index = 0;
- int c = getopt_long(argc, argv, "spl:f:Fqh", long_options, &option_index);
+ int c = getopt_long(argc, argv, "aAm:spl:f:Fc:t:qh", long_options, &option_index);
if (c == -1)
break;
switch (c) {
+ case 'a':
+ do_auto_level = true;
+ break;
+
+ case 'A':
+ output_leveled = true;
+ break;
+
+ case 'm':
+ min_level = atof(optarg) / 32768.0;
+ break;
+
case 's':
do_calibrate = false;
break;
break;
case 'f': {
- const char *coeffstr = strtok(optarg, ":");
+ const char *coeffstr = strtok(optarg, ": ");
int coeff_index = 0;
while (coeff_index < NUM_FILTER_COEFF && coeffstr != NULL) {
filter_coeff[coeff_index++] = atof(coeffstr);
- coeffstr = strtok(NULL, ":");
+ coeffstr = strtok(NULL, ": ");
}
use_filter = true;
break;
output_filtered = true;
break;
+ case 'c': {
+ const char *cropstr = strtok(optarg, ":");
+ crop_start = atof(cropstr);
+ cropstr = strtok(NULL, ":");
+ if (cropstr == NULL) {
+ crop_end = HUGE_VAL;
+ } else {
+ crop_end = atof(cropstr);
+ }
+ do_crop = true;
+ break;
+ }
+
+ case 't': {
+ const char *cyclestr = strtok(optarg, ":");
+ while (cyclestr != NULL) {
+ train_snap_points.push_back(atof(cyclestr));
+ cyclestr = strtok(NULL, ":");
+ }
+ do_train = true;
+
+ // Set reasonable defaults (can be overridden later on the command line).
+ do_calibrate = false;
+ quiet = true;
+ break;
+ }
+
case 'q':
quiet = true;
break;
}
}
+std::vector<float> crop(const std::vector<float>& pcm, float crop_start, float crop_end, int sample_rate)
+{
+ size_t start_sample, end_sample;
+ if (crop_start >= 0.0f) {
+ start_sample = std::min<size_t>(lrintf(crop_start * sample_rate), pcm.size());
+ }
+ if (crop_end >= 0.0f) {
+ end_sample = std::min<size_t>(lrintf(crop_end * sample_rate), pcm.size());
+ }
+ return std::vector<float>(pcm.begin() + start_sample, pcm.begin() + end_sample);
+}
+
// TODO: Support AVX here.
std::vector<float> do_filter(const std::vector<float>& pcm, const float* filter)
{
}
// down-flank!
- double t = find_zerocrossing(pcm, i - 1) * (1.0 / sample_rate);
+ double t = find_zerocrossing(pcm, i - 1) * (1.0 / sample_rate) + crop_start;
if (last_downflank > 0) {
pulse p;
p.time = t;
return pulses;
}
+void output_cycle_plot(const std::vector<pulse> &pulses, double calibration_factor)
+{
+ FILE *fp = fopen("cycles.plot", "w");
+ for (unsigned i = 0; i < pulses.size(); ++i) {
+ double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
+ fprintf(fp, "%f %f\n", pulses[i].time, cycles);
+ }
+ fclose(fp);
+}
+
+float eval_badness(const std::vector<pulse>& pulses, double calibration_factor)
+{
+ double sum_badness = 0.0;
+ for (unsigned i = 0; i < pulses.size(); ++i) {
+ double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
+ if (cycles > 2000.0) cycles = 2000.0; // Don't make pauses arbitrarily bad.
+ double badness = (cycles - train_snap_points[0]) * (cycles - train_snap_points[0]);
+ for (unsigned j = 1; j < train_snap_points.size(); ++j) {
+ badness = std::min(badness, (cycles - train_snap_points[j]) * (cycles - train_snap_points[j]));
+ }
+ sum_badness += badness;
+ }
+ return sqrt(sum_badness / (pulses.size() - 1));
+}
+
+void spsa_train(std::vector<float> &pcm, int sample_rate)
+{
+ // Train!
+ float filter[NUM_FILTER_COEFF] = { 1.0f }; // The rest is filled with 0.
+
+ float start_c = INITIAL_C;
+ double best_badness = HUGE_VAL;
+
+ for (int n = 1; n < NUM_ITER; ++n) {
+ float a = INITIAL_A * pow(n + A, -ALPHA);
+ float c = start_c * pow(n, -GAMMA);
+
+ // find a random perturbation
+ float p[NUM_FILTER_COEFF];
+ float filter1[NUM_FILTER_COEFF], filter2[NUM_FILTER_COEFF];
+ for (int i = 0; i < NUM_FILTER_COEFF; ++i) {
+ p[i] = (rand() % 2) ? 1.0 : -1.0;
+ filter1[i] = std::max(std::min(filter[i] - c * p[i], 1.0f), -1.0f);
+ filter2[i] = std::max(std::min(filter[i] + c * p[i], 1.0f), -1.0f);
+ }
+
+ std::vector<pulse> pulses1 = detect_pulses(do_filter(pcm, filter1), sample_rate);
+ std::vector<pulse> pulses2 = detect_pulses(do_filter(pcm, filter2), sample_rate);
+ float badness1 = eval_badness(pulses1, 1.0);
+ float badness2 = eval_badness(pulses2, 1.0);
+
+ // Find the gradient estimator
+ float g[NUM_FILTER_COEFF];
+ for (int i = 0; i < NUM_FILTER_COEFF; ++i) {
+ g[i] = (badness2 - badness1) / (2.0 * c * p[i]);
+ filter[i] -= a * g[i];
+ filter[i] = std::max(std::min(filter[i], 1.0f), -1.0f);
+ }
+ if (badness2 < badness1) {
+ std::swap(badness1, badness2);
+ std::swap(filter1, filter2);
+ std::swap(pulses1, pulses2);
+ }
+ if (badness1 < best_badness) {
+ printf("\nNew best filter (badness=%f):", badness1);
+ for (int i = 0; i < NUM_FILTER_COEFF; ++i) {
+ printf(" %.5f", filter1[i]);
+ }
+ best_badness = badness1;
+ printf("\n");
+
+ if (output_cycles_plot) {
+ output_cycle_plot(pulses1, 1.0);
+ }
+ }
+ printf("%d ", n);
+ fflush(stdout);
+ }
+}
+
int main(int argc, char **argv)
{
parse_options(argc, argv);
exit(1);
}
+ if (do_crop) {
+ pcm = crop(pcm, crop_start, crop_end, sample_rate);
+ }
+
if (use_filter) {
pcm = do_filter(pcm, filter_coeff);
}
+ if (do_auto_level) {
+ pcm = level_samples(pcm, min_level, sample_rate);
+ if (output_leveled) {
+ FILE *fp = fopen("leveled.raw", "wb");
+ fwrite(pcm.data(), pcm.size() * sizeof(pcm[0]), 1, fp);
+ fclose(fp);
+ }
+ }
+
#if 0
for (int i = 0; i < LEN; ++i) {
in[i] += rand() % 10000;
}
#endif
+ if (do_train) {
+ spsa_train(pcm, sample_rate);
+ exit(0);
+ }
+
std::vector<pulse> pulses = detect_pulses(pcm, sample_rate);
double calibration_factor = 1.0;
}
if (output_cycles_plot) {
- FILE *fp = fopen("cycles.plot", "w");
- for (unsigned i = 0; i < pulses.size(); ++i) {
- double cycles = pulses[i].len * calibration_factor * C64_FREQUENCY;
- fprintf(fp, "%f %f\n", pulses[i].time, cycles);
- }
- fclose(fp);
+ output_cycle_plot(pulses, calibration_factor);
}
output_tap(pulses, calibration_factor);
projects / c64tapwav / blobdiff