Cleaned up the ambiguous synthetic example.

diff --git a/mtp.cc b/mtp.cc
index cd1290c..899c73d 100644 (file)
--- 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();