+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)
+{
+ 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);
+ }
+}
+