--- a/python/moving.py	Wed Jun 18 23:40:47 2014 -0400
+++ b/python/moving.py	Thu Jun 19 13:31:00 2014 -0400
@@ -821,7 +821,7 @@
     ###
     # User Type Classification
     ###
-    def classifyUserTypeSpeedPedstrianCar(self, threshold, aggregationFunc = median, ignoreNInstantsAtEnds = 0):
+    def classifyUserTypeSpeedMotorized(self, threshold, aggregationFunc = median, ignoreNInstantsAtEnds = 0):
         '''Classifies slow and fast road users
         slow: non-motorized -> pedestrians
         fast: motorized -> cars'''
@@ -834,7 +834,7 @@
         else:
             self.setUserType(userType2Num['pedestrian'])
 
-    def classifyUserTypeSpeed(self, aggregationFunc = median, speedProbabilities):
+    def classifyUserTypeSpeed(self, speedProbabilities, aggregationFunc = median):
         '''Classifies road user per road user type
         speedProbabilities are functions return P(speed|class)
         in a dictionary indexed by user type names
@@ -876,7 +876,7 @@
         else:
             self.userTypes[instant] = userType2Num['unknown']
 
-    def classifyUserTypeHoGSVM(self, images, pedBikeCarSVM, homography, width, height, bikeCarSVM = None, pedBikeSpeedTreshold = float('Inf'), bikeCarSpeedThreshold = float('Inf'), aggregationFunc = median, speedProbabilities = None, px = 0.2, py = 0.2, pixelThreshold = 800):
+    def classifyUserTypeHoGSVM(self, images, pedBikeCarSVM, homography, width, height, bikeCarSVM = None, pedBikeSpeedTreshold = float('Inf'), bikeCarSpeedThreshold = float('Inf'), speedProbabilities = None, aggregationFunc = median, px = 0.2, py = 0.2, pixelThreshold = 800):
         '''Agregates SVM detections in each image and returns probability
         (proportion of instants with classification in each category)
 
@@ -892,7 +892,7 @@
                 if t not in self.userTypes:
                     self.classifyUserTypeHoGSVMAtInstant(images[t], pedBikeCarSVM, t, homography, width, height, bikeCarSVM, pedBikeSpeedTreshold, bikeCarSpeedThreshold, px, py, pixelThreshold)
         # compute P(Speed|Class)
-        if speedProbabilities = None: # equiprobable information from speed
+        if speedProbabilities == None: # equiprobable information from speed
             userTypeProbabilities = {userType2Num['car']: 1., userType2Num['pedestrian']: 1., userType2Num['bicycle']: 1.}
         else:
             userTypeProbabilities = {userType2Num[userTypename]: speedProbabilities[userTypename](self.aggregatedSpeed) for userTypename in speedProbabilities}