--- a/python/events.py	Mon Nov 24 13:02:10 2014 -0500
+++ b/python/events.py	Tue Nov 25 22:49:47 2014 -0500
@@ -8,8 +8,10 @@
 import multiprocessing
 import itertools
 
+import sys
 import moving, prediction, indicators, utils
-
+sys.path.append("D:/behaviourAnalysis/libs")
+import trajLearning
 __metaclass__ = type
 
 class Interaction(moving.STObject):
@@ -147,6 +149,67 @@
                     pPETs[i] = prediction.SafetyPoint.computeExpectedIndicator(self.crossingZones[i])
             self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[9], pPETs))
 
+    def computeCrosssingCollisionsPrototypeAtInstant(self, instant,route1,route2,predictionParameters, collisionDistanceThreshold, timeHorizon, prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity=0.1,mostMatched=None, computeCZ = False, debug = False,useDestination=True,useSpeedPrototype=True):
+        inter1=moving.Interval(self.roadUser1.timeInterval.first,instant)
+        inter2=moving.Interval(self.roadUser2.timeInterval.first,instant)
+        partialObjPositions1= self.roadUser1.getObjectInTimeInterval(inter1).positions
+        partialObjPositions2= self.roadUser2.getObjectInTimeInterval(inter2).positions
+        if useSpeedPrototype:
+            prototypeTrajectories1=trajLearning.findPrototypesSpeed(prototypes,secondStepPrototypes,nMatching,objects,route1,partialObjPositions1,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination)
+            prototypeTrajectories2=trajLearning.findPrototypesSpeed(prototypes,secondStepPrototypes,nMatching,objects,route2,partialObjPositions2,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination)
+        else:
+            prototypeTrajectories1=trajLearning.findPrototypes(prototypes,nMatching,objects,route1,partialObjPositions1,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched)
+            prototypeTrajectories2=trajLearning.findPrototypes(prototypes,nMatching,objects,route2,partialObjPositions2,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched)
+        if prototypeTrajectories1=={}:
+            print self.roadUser1.num, 'is abnormal at instant', str(instant)
+            return [],[]
+        elif prototypeTrajectories2=={}:
+            print self.roadUser2.num, 'is abnormal at instant', str(instant)
+            return [],[]
+        else:
+            currentInstant,collisionPoints, crossingZones = predictionParameters.computeCrossingsCollisionsAtInstant(instant, self.roadUser1, self.roadUser2, collisionDistanceThreshold, timeHorizon, computeCZ, debug,prototypeTrajectories1,prototypeTrajectories2)
+            return collisionPoints,crossingZones
+
+    def computeCrossingsCollisionsPrototype2stages(self, predictionParameters, collisionDistanceThreshold, timeHorizon, prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,step=10,minSimilarity=0.1,mostMatched=None, computeCZ = False, debug = False, timeInterval = None,acceptPartialLength=30,useDestination=True,useSpeedPrototype=True):
+        '''Computes all crossing and collision points at each common instant for two road users. '''
+        self.collisionPoints={}
+        self.crossingZones={}
+        TTCs = {}
+        route1=(self.roadUser1.startRouteID,self.roadUser1.endRouteID)
+        route2=(self.roadUser2.startRouteID,self.roadUser2.endRouteID)
+        if useDestination:
+            if route1 not in prototypes.keys():
+                route1= trajLearning.findRoute(prototypes,objects,route1,self.roadUser1.num,noiseEntryNums,noiseExitNums)
+            if route2 not in prototypes.keys():
+                route2= trajLearning.findRoute(prototypes,objects,route2,self.roadUser2.num,noiseEntryNums,noiseExitNums)
+				
+        if timeInterval:
+            commonTimeInterval = timeInterval
+        else:
+            commonTimeInterval = self.timeInterval
+        reCompute=False
+        for i in xrange(commonTimeInterval.first,commonTimeInterval.last,step): # incremental calculation of CP,CZ to save time
+            if  i-self.roadUser1.timeInterval.first >= acceptPartialLength and i-self.roadUser2.timeInterval.first >= acceptPartialLength:
+				self.collisionPoints[i], self.crossingZones[i] = self.computeCrosssingCollisionsPrototypeAtInstant(i,route1,route2,predictionParameters, collisionDistanceThreshold, timeHorizon, prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched, computeCZ, debug,useDestination,useSpeedPrototype)
+				if len(self.collisionPoints[i]) >0 or len(self.crossingZones[i])>0:
+					reCompute=True
+					break
+        if reCompute:
+            for i in list(commonTimeInterval)[:-1]: # do not look at the 1 last position/velocities, often with errors
+				if  i-self.roadUser1.timeInterval.first >= acceptPartialLength and i-self.roadUser2.timeInterval.first >= acceptPartialLength:
+					self.collisionPoints[i], self.crossingZones[i] = self.computeCrosssingCollisionsPrototypeAtInstant(i,route1,route2,predictionParameters, collisionDistanceThreshold, timeHorizon, prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched, computeCZ, debug,useDestination,useSpeedPrototype)		
+					if len(self.collisionPoints[i]) > 0:
+						TTCs[i] = prediction.SafetyPoint.computeExpectedIndicator(self.collisionPoints[i])
+        # add probability of collision, and probability of successful evasive action
+        self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[7], TTCs))
+        
+        if computeCZ:
+            pPETs = {}
+            for i in list(commonTimeInterval)[:-1]:
+                if i in self.crossingZones.keys() and len(self.crossingZones[i]) > 0:
+                    pPETs[i] = prediction.SafetyPoint.computeExpectedIndicator(self.crossingZones[i])
+            self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[9], pPETs))
+			
     def addVideoFilename(self,videoFilename):
         self.videoFilename= videoFilename