X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=blobdiff_plain;f=mtp.cc;h=4ba31d9c9f5d35271f7767de9cc525898d0b3f63;hb=72a428f6024a6a3f84526020f28cfa3a200d0f24;hp=59e950a0da1ebd5d2564977de6f5fcb56c7de22d;hpb=3070f21d61377aff06255fa5cfe92d0111d70117;p=mtp.git

diff --git a/mtp.cc b/mtp.cc
index 59e950a..4ba31d9 100644
--- a/mtp.cc
+++ b/mtp.cc
@@ -18,10 +18,6 @@
 
 // Multi-Tracked Path
 
-// Takes the graph description file as input and produces a dot file.
-
-// EXAMPLE: ./mtp ./graph2.txt  | dot -T pdf -o- | xpdf -
-
 #include <iostream>
 #include <fstream>
 #include <stdlib.h>
@@ -32,8 +28,8 @@ using namespace std;
 
 //////////////////////////////////////////////////////////////////////
 
-scalar_t detection_score(int true_label) {
-  if((true_label > 0) == (drand48() < 0.9)) {
+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);
   } else {
     return - 1.0 + 0.2 * (drand48() - 0.5);
@@ -41,8 +37,8 @@ scalar_t detection_score(int true_label) {
 }
 
 int main(int argc, char **argv) {
-  int nb_locations = 5;
-  int nb_time_steps = 20;
+  int nb_locations = 1000;
+  int nb_time_steps = 1000;
   int motion_amplitude = 1;
 
   Tracker *tracker = new Tracker(nb_time_steps, nb_locations);
@@ -51,23 +47,26 @@ int main(int argc, char **argv) {
     for(int k = 0; k < nb_locations; k++) {
       tracker->set_allowed_motion(l, k, abs(l - k) <= motion_amplitude);
     }
-    tracker->set_as_exit(0, 1);
     tracker->set_as_entrance(0, 1);
+    tracker->set_as_exit(nb_locations - 1, 1);
   }
 
   tracker->build_graph();
 
-  for(int r = 0; r < 10; r++) {
+  // We repeat several times the same tracking to check how stable it
+  // is
+
+  for(int r = 0; r < 1; r++) {
     cout << "* ROUND " << r << endl;
 
-    // We generate synthetic detection scores, all in the center
-    // location, with 10% false detection (FP or FN)
+    // We generate synthetic detection scores at location
+    // nb_locations/2, with 10% false detection (FP or FN)
 
     for(int t = 0; t < nb_time_steps; t++) {
       for(int l = 0; l < nb_locations; l++) {
-        tracker->set_detection_score(t, l, detection_score(-1));
+        tracker->set_detection_score(t, l, detection_score(-1, 0.95));
       }
-      tracker->set_detection_score(t, nb_locations/2, detection_score(1));
+      tracker->set_detection_score(t, nb_locations/2, detection_score(1, 0.95));
     }
 
     tracker->track();