--- a/python/moving.py	Thu Aug 28 17:42:32 2014 -0400
+++ b/python/moving.py	Thu Aug 28 23:50:30 2014 -0400
@@ -379,9 +379,7 @@
     return Point(X,Y)
 
 def getSYfromXY(p, splines, goodEnoughSplineDistance = 0.5):
-    ''' Snap a point p to it's nearest subsegment of it's nearest spline (from the list splines).
-        
-        To force snapping to a single spline, pass the spline alone through splines (e.g. splines=[splines[splineNum]]).
+    ''' Snap a point p to it's nearest subsegment of it's nearest spline (from the list splines). A spline is a list of points (class Point), most likely a trajectory. 
         
         Output:
         =======
@@ -1084,12 +1082,7 @@
             Input:
             ======
             alignments   = a list of alignments, where each alignment is a list of
-                           points, where each point is a list of coordinates, e.g.
-                           alignments[alpha][1][x] is coordinate x for point number
-                           1 of the spline that represents alignment alpha.
-                           alignments can also be a compatible object that mimics a
-                           3-dimensional list using the __getitem__() method as is
-                           the case in the PVAT specification.
+                           points (class Point).
             ln_mv_av_win = moving average window (in points) in which to smooth
                            lane changes. As per tools_math.cat_mvgavg(), this term
                            is a search *radius* around the center of the window.
@@ -1099,12 +1092,12 @@
         self.curvilinearPositions = CurvilinearTrajectory()
 
         #For each point
-        for p in self.getPositions():#xrange(int(self.length())):
-            result = getSYfromXY(p, alignments)
+        for i in xrange(int(self.length())):
+            result = getSYfromXY(self.getPositionAt(i), alignments)
 
             # Error handling
             if(result == None):
-                print('Warning: trajectory {} at point {} has alignment errors (spline snapping)\nCurvilinear trajectory could not be computed'.format(self.getNum(), p))
+                print('Warning: trajectory {} at point {} {} has alignment errors (spline snapping)\nCurvilinear trajectory could not be computed'.format(self.getNum(), i, self.getPositionAt(i)))
             else:
                 [align, alignPoint, snappedPoint, subsegmentDistance, S, Y] = result
                 self.curvilinearPositions.addPositionSYL(S, Y, align)
@@ -1115,7 +1108,7 @@
         ## Recalculate projected point to new lane
         lanes = self.curvilinearPositions.getLanes()
         if(lanes != smoothed_lanes):
-            for i in range(int(self.length())):
+            for i in xrange(len(lanes)):
                 if(lanes[i] != smoothed_lanes[i]):
                     result = getSYfromXY(self.getPositionAt(i),[alignments[smoothed_lanes[i]]])
 
@@ -1124,19 +1117,9 @@
                         ## This can be triggered by tracking errors when the trajectory jumps around passed another alignment.
                         print('    Warning: trajectory {} at point {} {} has alignment errors during trajectory smoothing and will not be corrected.'.format(self.getNum(), i, self.getPositionAt(i)))
                     else:
-                        [align, alignPoint, snapped_x, snapped_y, subsegmentDistance, S, Y] = result
+                        [align, alignPoint, snappedPoint, subsegmentDistance, S, Y] = result
                         self.curvilinearPositions.setPosition(i, S, Y, align)
 
-        #Resize objects
-        # if(len(dropped_traj) > 0):
-        #     objects = filter(None, objects)    
-        #     if(verbose >= 2): print('    Filtering report: Trajectories dropped: '+str(len(dropped_traj))) 
-        #if(verbose >= 2): print('    Filtering report: Lane observation corrections per object: '+str(lane_readjustments/original_object_length))   
-
-        #if(reset_objects and len(objects) > 0): return objects[0], dropped_traj
-    #else:                                   return objects, dropped_traj
-
-
     def computeSmoothTrajectory(self, minCommonIntervalLength):
         '''Computes the trajectory as the mean of all features
         if a feature exists, its position is