--- a/python/moving.py	Fri Dec 05 17:50:16 2014 -0500
+++ b/python/moving.py	Sat Dec 06 22:15:56 2014 -0500
@@ -1339,6 +1339,59 @@
                     matchTable.append([t, a.getNum(), matchingObject.getNum(), minDist])
     return matchTable
 
+def computeClearMOT(matchTable, nTrackFrames):
+    '''Computes the MOTA/MOTP measures from the matching statistics 
+    between ground truth and tracker output 
+    computed by matchingGroundTruthToTracker
+
+    nTrackFrames is the sum of the number of frames of existence of all tracker output
+
+    Adapted from Dariush Ettehadieh's thesis work'''
+    #Calculate MOTP
+    dist = 0. # total distance between GT and tracker output
+    nAssociatedGTFrames = 0
+    mt = 0 # number of missed GT frames (sum of the number of GT not detected in each frame)
+    for mtab in matchTable:
+        if mtab[2] != None:
+            dist += float(mtab[3])#/T
+            nAssociatedGTFrames += 1
+        else:
+            mt += 1
+    if nAssociatedGTFrames != 0:
+        motp = dist/nAssociatedGTFrames
+    else:
+        return 0,0,0,0,0,0
+
+    #Calculate MOTA
+    gt = len(matchTable) # sum of the number of GT in each frame, or sum of the length of existence of each GT
+    #for sgt in sorted_gt_positions:
+    #    gt += (len(sgt)-1)
+
+    #total_traces = len(object_positions)
+    fpt = nTrackFrames - nAssociatedGTFrames
+
+    # gtobj = 0
+    mme = 0
+    # while gtobj <= n_gt_objects:
+    #     prev = [0,0,-1,0]
+    #     new_match = 0
+    #     for mtab in matchTable:
+    #         if mtab[1] == gtobj:
+    #             if new_match == 0:
+    #                 new_match = 1
+    #                 mme = mme - 1
+    #                 if mtab[2] != prev[2]:
+    #                     mme += 1
+    #                     prev = mtab
+    #                     gtobj += 1
+
+    mota = 1-(float(mt+fpt+mme)/gt)
+
+    print 'MOTP: ' + str(motp)
+    print 'MOTA: ' + str(mota)
+    return motp, mota, dist, mt, mme, fpt
+
+
 def plotRoadUsers(objects, colors):
     '''Colors is a PlottingPropertyValues instance'''
     from matplotlib.pyplot import figure, axis