--- a/python/moving.py	Tue Nov 25 22:49:47 2014 -0500
+++ b/python/moving.py	Wed Nov 26 19:49:13 2014 +0000
@@ -5,7 +5,7 @@
 import cvutils
 
 from math import sqrt
-from numpy import median,percentile
+from numpy import median
 
 try:
     from shapely.geometry import Polygon, Point as shapelyPoint
@@ -790,7 +790,7 @@
         return False
 
     def wiggliness(self):
-        return self.computeCumulativeDistances()/float(Point.distanceNorm2(self.__getitem__(0),self.__getitem__(self.length()-1)))
+        return self.getCumulativeDistance(self.length()-1)/float(Point.distanceNorm2(self.__getitem__(0),self.__getitem__(self.length()-1)))
 
     def getIntersections(self, p1, p2):
         '''Returns a list of the indices at which the trajectory 
@@ -1156,16 +1156,18 @@
     ###
     # User Type Classification
     ###
-    def classifyUserTypeSpeedMotorized(self, threshold, percentileFactor=95, ignoreNInstantsAtEnds = 0):
+    def classifyUserTypeSpeedMotorized(self, threshold, aggregationFunc = median, ignoreNInstantsAtEnds = 0):
         '''Classifies slow and fast road users
         slow: non-motorized -> pedestrians
         fast: motorized -> cars
-        The percentile function is the same as the median if percentileFactor=50, the same as the minimum if percentileFactor=0 and the same as the maximum if percentileFactor=100.'''
+        
+        aggregationFunc can be any function that can be applied to a vector of speeds, including percentile:
+        aggregationFunc = lambda x: percentile(x, percentileFactor) # where percentileFactor is 85 for 85th percentile'''
         if ignoreNInstantsAtEnds > 0:
             speeds = self.getSpeeds()[ignoreNInstantsAtEnds:-ignoreNInstantsAtEnds]
         else:
             speeds = self.getSpeeds()
-        if percentile(speeds,percentileFactor) >= threshold:
+        if aggregationFunc(speeds) >= threshold:
             self.setUserType(userType2Num['car'])
         else:
             self.setUserType(userType2Num['pedestrian'])