From: Francois Fleuret Date: Fri, 24 Aug 2012 04:07:14 +0000 (+0200) Subject: Cleaned up the ambiguous synthetic example. X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=commitdiff_plain;h=9adcc8e236c166890dbff01ba0f7d559e7f6299a;p=mtp.git Cleaned up the ambiguous synthetic example. --- diff --git a/mtp.cc b/mtp.cc index cd1290c..899c73d 100644 --- a/mtp.cc +++ b/mtp.cc @@ -27,17 +27,17 @@ using namespace std; ////////////////////////////////////////////////////////////////////// -scalar_t detection_score(int true_label, scalar_t flip_noise) { - if((true_label > 0) == (drand48() < flip_noise)) { - return 1.0 + 0.2 * (drand48() - 0.5); +scalar_t detection_score(scalar_t a, scalar_t b, scalar_t score_noise, scalar_t flip_noise) { + if(drand48() > flip_noise) { + return a + score_noise * (2.0 * drand48() - 1.0); } else { - return - 1.0 + 0.2 * (drand48() - 0.5); + return b + score_noise * (2.0 * drand48() - 1.0); } } int main(int argc, char **argv) { - int nb_locations = 6; - int nb_time_steps = 5; + int nb_locations = 7; + int nb_time_steps = 8; int motion_amplitude = 1; Tracker *tracker = new Tracker(nb_time_steps, nb_locations); @@ -55,34 +55,46 @@ int main(int argc, char **argv) { // We generate synthetic detection scores at location // nb_locations/2, with 5% false detection (FP or FN) + scalar_t flip_noise = 0.01; + scalar_t score_noise = 0.0; + for(int t = 0; t < nb_time_steps; t++) { for(int l = 0; l < nb_locations; l++) { - tracker->detection_score[t][l] = detection_score(-1, 0.95); + tracker->detection_score[t][l] = detection_score(-1.0, 1.0, score_noise, flip_noise); } } + // for(int t = 0; t < nb_time_steps; t++) { + // tracker->detection_score[t][nb_locations/2] = detection_score(1, score_noise, flip_noise); + // } + + // Puts two target with the typical local minimum + + int la, lb; + scalar_t sa, sb; for(int t = 0; t < nb_time_steps; t++) { - tracker->detection_score[t][nb_locations/2] = detection_score(1, 0.95); - } + // Target a moves from location 0 to the middle and comes back, + // and is strongly detected on the first half, target b moves from + // location nb_locations-1 to the middle and comes back, and is + // strongly detected on the second half + if(t < nb_time_steps/2) { + la = t; + lb = nb_locations - 1 - t; + sa = detection_score(10.0, -1.0, score_noise, flip_noise); + sb = detection_score( 1.0, -1.0, score_noise, flip_noise); + } else { + la = nb_time_steps - 1 - t; + lb = t - nb_time_steps + nb_locations; + sa = detection_score( 1.0, -1.0, score_noise, flip_noise); + sb = detection_score(10.0, -1.0, score_noise, flip_noise); + } - // Puts two target with the typical local minimum (i.e. the optimal - // single path would track the first target on the first half and - // the second on the second half, while the optimal two paths would - // each follow one of the target properly) + if(la > nb_locations/2 - 1) la = nb_locations/2 - 1; + if(lb < nb_locations/2 + 1) lb = nb_locations/2 + 1; - // for(int t = 0; t < nb_time_steps; t++) { - // int a = nb_time_steps/2 - abs(t - nb_time_steps/2); - // int b = nb_locations - 1 - a; - // if(a > nb_locations/2 - 1) a = nb_locations/2 - 1; - // if(b < nb_locations/2 + 1) b = nb_locations/2 + 1; - // if(t < nb_time_steps/2) { - // tracker->detection_score[t][a] = 10.0; - // tracker->detection_score[t][b] = 1.0; - // } else { - // tracker->detection_score[t][a] = 1.0; - // tracker->detection_score[t][b] = 10.0; - // } - // } + tracker->detection_score[t][la] = sa; + tracker->detection_score[t][lb] = sb; + } tracker->track();