X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;ds=sidebyside;f=mtp.cc;fp=mtp.cc;h=7f55e0a8a060cafb96d0e961dbeb1ec7dd5e5fc0;hb=4d9b58034ce82094c233b61da247e11a584ec0bd;hp=c1387d94d28674c91b029435b94231ba15013e8b;hpb=852417aae1e0f64716fa49499176e300ab84d66f;p=mtp.git

diff --git a/mtp.cc b/mtp.cc
index c1387d9..7f55e0a 100644
--- a/mtp.cc
+++ b/mtp.cc
@@ -42,6 +42,14 @@ int main(int argc, char **argv) {
 
   Tracker *tracker = new Tracker(nb_time_steps, nb_locations);
 
+  // We define the spatial structures by stating what are the possible
+  // motions of targets, and what are the entrances and the
+  // exits.
+
+  // Here our example is a 1D space with motions from any location to
+  // any location less than motion_amplitude away, entrance at
+  // location 0 and exit at location nb_locations-1.
+
   for(int l = 0; l < nb_locations; l++) {
     for(int k = 0; k < nb_locations; k++) {
       tracker->allowed_motion[l][k] = abs(l - k) <= motion_amplitude;
@@ -50,33 +58,38 @@ int main(int argc, char **argv) {
     tracker->exits[nb_locations - 1] = 1;
   }
 
+  // We construct the graph corresponding to this structure
+
   tracker->build_graph();
 
-  // We generate synthetic detection scores at location
-  // nb_locations/2, with 5% false detection (FP or FN)
+  // Then, we specify for every location and time step what is the
+  // detection score there.
 
   scalar_t flip_noise = 0.05;
   scalar_t score_noise = 0.0;
 
+  // We first put a background noise, with negative scores at every
+  // location.
+
   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, 1.0, score_noise, flip_noise);
+      tracker->detection_scores[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;
+  // Then we two targets with the typical local minimum:
+  //
+  // * Target A moves from location 0 to the middle, stays there for a
+  //   while, and comes back, and is strongly detected on the first
+  //   half
+  //
+  // * Target B moves from location nb_locations-1 to the middle, stay
+  //   there for a while, and comes back, and is strongly detected on
+  //   the second half
+
+  int la, lb; // Target locations
+  scalar_t sa, sb; // Target detection scores
   for(int t = 0; t < nb_time_steps; t++) {
-    // 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;
@@ -92,12 +105,16 @@ int main(int argc, char **argv) {
     if(la > nb_locations/2 - 1) la = nb_locations/2 - 1;
     if(lb < nb_locations/2 + 1) lb = nb_locations/2 + 1;
 
-    tracker->detection_score[t][la] = sa;
-    tracker->detection_score[t][lb] = sb;
+    tracker->detection_scores[t][la] = sa;
+    tracker->detection_scores[t][lb] = sb;
   }
 
+  // Does the tracking per se
+
   tracker->track();
 
+  // Prints the detected trajectories
+
   for(int t = 0; t < tracker->nb_trajectories(); t++) {
     cout << "TRAJECTORY "
          << t
@@ -109,6 +126,9 @@ int main(int argc, char **argv) {
     cout << endl;
   }
 
+  // Save the underlying graph in the dot format, with occupied edges
+  // marked in bold.
+
   {
     ofstream dot("graph.dot");
     tracker->print_graph_dot(&dot);