--- a/python/events.py	Tue Nov 25 22:49:47 2014 -0500
+++ b/python/events.py	Wed Dec 03 22:57:08 2014 -0500
@@ -8,12 +8,17 @@
 import multiprocessing
 import itertools
 
-import sys
 import moving, prediction, indicators, utils
-sys.path.append("D:/behaviourAnalysis/libs")
 import trajLearning
 __metaclass__ = type
 
+def getRoute(obj,prototypes,objects,noiseEntryNums,noiseExitNums,useDestination=True):
+    route=(obj.startRouteID,obj.endRouteID)
+    if useDestination:
+        if route not in prototypes.keys():
+            route= trajLearning.findRoute(prototypes,objects,route,obj.getNum(),noiseEntryNums,noiseExitNums)
+    return route
+
 class Interaction(moving.STObject):
     '''Class for an interaction between two road users 
     or a road user and an obstacle
@@ -126,17 +131,20 @@
                 minDistance[instant] = moving.MovingObject.minDistance(self.roadUser1, self.roadUser2, instant)
             self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[3], minDistance))
 
-    def computeCrossingsCollisions(self, predictionParameters, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None, nProcesses = 1):
+    def computeCrossingsCollisions(self, predictionParameters, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None, nProcesses = 1,usePrototypes=True,route1= (-1,-1),route2=(-1,-1),prototypes={},secondStepPrototypes={},nMatching={},objects=[],noiseEntryNums=[],noiseExitNums=[],minSimilarity=0.1,mostMatched=None,useDestination=True,useSpeedPrototype=True,acceptPartialLength=30, step=1):
         '''Computes all crossing and collision points at each common instant for two road users. '''
         self.collisionPoints={}
         self.crossingZones={}
         TTCs = {}
+        if usePrototypes:
+            route1= getRoute(self.roadUser1,prototypes,objects,noiseEntryNums,noiseExitNums,useDestination)
+            route2= getRoute(self.roadUser2,prototypes,objects,noiseEntryNums,noiseExitNums,useDestination)
 
         if timeInterval:
             commonTimeInterval = timeInterval
         else:
             commonTimeInterval = self.timeInterval
-        self.collisionPoints, self.crossingZones = prediction.computeCrossingsCollisions(predictionParameters, self.roadUser1, self.roadUser2, collisionDistanceThreshold, timeHorizon, computeCZ, debug, commonTimeInterval, nProcesses)
+        self.collisionPoints, self.crossingZones = prediction.computeCrossingsCollisions(predictionParameters, self.roadUser1, self.roadUser2, collisionDistanceThreshold, timeHorizon, computeCZ, debug, commonTimeInterval, nProcesses,usePrototypes,route1,route2,prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination,useSpeedPrototype,acceptPartialLength, step)
         for i, cp in self.collisionPoints.iteritems():
             TTCs[i] = prediction.SafetyPoint.computeExpectedIndicator(cp)
         # add probability of collision, and probability of successful evasive action
@@ -144,70 +152,8 @@
         
         if computeCZ:
             pPETs = {}
-            for i in list(commonTimeInterval)[:-1]:
-                if len(self.crossingZones[i]) > 0:
-                    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])
+            for i, cz in self.crossingZones.iteritems():
+                pPETs[i] = prediction.SafetyPoint.computeExpectedIndicator(cz)
             self.addIndicator(indicators.SeverityIndicator(Interaction.indicatorNames[9], pPETs))
 			
     def addVideoFilename(self,videoFilename):