# HG changeset patch
# User Nicolas Saunier <nicolas.saunier@polymtl.ca>
# Date 1373515667 14400
# Node ID e5fe0e6d48a154c24bc3547b7f13a6355fd61f13
# Parent  15fac9c45feb7cab432fb53ff224e1e9ddc1debe
corrected bug computing TTC (resp. pPET) if there is no collision point (resp. crossing zone)

diff -r 15fac9c45feb -r e5fe0e6d48a1 python/events.py
--- a/python/events.py	Wed Jul 10 18:22:45 2013 -0400
+++ b/python/events.py	Thu Jul 11 00:07:47 2013 -0400
@@ -118,15 +118,17 @@
             commonTimeInterval = self.timeInterval
         for i in list(commonTimeInterval)[:-1]: # do not look at the 1 last position/velocities, often with errors
             self.collisionPoints[i], self.crossingZones[i] = prediction.computeCrossingsCollisionsAtInstant(i, self.roadUser1, self.roadUser2, predictionParameters, collisionDistanceThreshold, timeHorizon, computeCZ, debug)
-            TTCs[i] = prediction.computeExpectedIndicator(self.collisionPoints[i])
+            if len(self.collisionPoints[i]) > 0:
+                TTCs[i] = prediction.computeExpectedIndicator(self.collisionPoints[i])
         # add probability of collision, and probability of successful evasive action
         self.addIndicator(indicators.SeverityIndicator('TTC', TTCs))
         
         if computeCZ:
             pPETs = {}
             for i in list(commonTimeInterval)[:-1]:
-                pPETs[i] = prediction.computeExpectedIndicator(self.crossingZones[i])
-                self.addIndicator(indicators.SeverityIndicator('pPET', pPETs))
+                if len(self.crossingZones[i]) > 0:
+                    pPETs[i] = prediction.computeExpectedIndicator(self.crossingZones[i])
+            self.addIndicator(indicators.SeverityIndicator('pPET', pPETs))
 
     def addVideoFilename(self,videoFilename):
         self.videoFilename= videoFilename	
diff -r 15fac9c45feb -r e5fe0e6d48a1 python/moving.py
--- a/python/moving.py	Wed Jul 10 18:22:45 2013 -0400
+++ b/python/moving.py	Thu Jul 11 00:07:47 2013 -0400
@@ -238,9 +238,9 @@
         return (p1-p2).norm2()
 
     @staticmethod
-    def plotAll(points, color='r'):
+    def plotAll(points, **kwargs):
         from matplotlib.pyplot import scatter
-        scatter([p.x for p in points],[p.y for p in points], c=color)
+        scatter([p.x for p in points],[p.y for p in points], **kwargs)
 
 class NormAngle(object):
     '''Alternate encoding of a point, by its norm and orientation'''
diff -r 15fac9c45feb -r e5fe0e6d48a1 python/prediction.py
--- a/python/prediction.py	Wed Jul 10 18:22:45 2013 -0400
+++ b/python/prediction.py	Thu Jul 11 00:07:47 2013 -0400
@@ -306,6 +306,13 @@
 
     return collisionProbabilities
 
+####
+# Other Methods
+####
+
+
+
+
 
 if __name__ == "__main__":
     import doctest
diff -r 15fac9c45feb -r e5fe0e6d48a1 scripts/safety-analysis.py
--- a/scripts/safety-analysis.py	Wed Jul 10 18:22:45 2013 -0400
+++ b/scripts/safety-analysis.py	Thu Jul 11 00:07:47 2013 -0400
@@ -1,15 +1,19 @@
 #! /usr/bin/env python
 
-import utils, storage, prediction, events
+import utils, storage, prediction, events, moving
 
 import sys, argparse
 
 import matplotlib.pyplot as plt
 import numpy as np
 
+# todo: very slow if too many predicted trajectories
+# add computation of probality of unsucessful evasive action
+
 parser = argparse.ArgumentParser(description='The program processes indicators for all pairs of road users in the scene')
 parser.add_argument('--cfg', dest = 'configFilename', help = 'name of the configuration file')
 parser.add_argument('--prediction-method', dest = 'predictionMethod', help = 'prediction method (constant velocity, normal adaptation, point set prediction)', choices = ['cv', 'na', 'ps'])
+parser.add_argument('--display-cp', dest = 'displayCollisionPoints', help = 'display collision points')
 args = parser.parse_args()
 
 params = utils.TrackingParameters()
@@ -50,17 +54,18 @@
         obj.setFeatures(features)
 
 interactions = events.createInteractions(objects)
-for inter in interactions[:1]:
+for inter in interactions:
     inter.computeIndicators()
     inter.computeCrossingsCollisions(predictionParameters, params.collisionDistance, params.predictionTimeHorizon, params.crossingZones)
 
 storage.saveIndicators(params.databaseFilename, interactions)
 
-if False:
+if args.displayCollisionPoints:
     plt.figure()
-    plt.axis('equal')
+    allCollisionPoints = []
     for inter in interactions:
         for collisionPoints in inter.collisionPoints.values():
-            for cp in collisionPoints:
-                plt.plot([cp.x], [cp.y], 'x')
+            allCollisionPoints += collisionPoints
+    moving.Point.plotAll(allCollisionPoints)
+    plt.axis('equal')