--- a/trafficintelligence/processing.py	Wed Jul 04 17:39:39 2018 -0400
+++ b/trafficintelligence/processing.py	Thu Jul 05 17:06:40 2018 -0400
@@ -3,7 +3,7 @@
 
 import numpy as np
 
-from trafficintelligence import moving
+from trafficintelligence import ml
 
 def extractSpeeds(objects, zone):
     speeds = {}
@@ -17,3 +17,31 @@
         else:
             objectsNotInZone.append(o)
     return speeds, objectsNotInZone
+
+def learnAssignMotionPatterns(learn, assign, objects, similarities, minSimilarity, similarityFunc, minClusterSize = 0, optimizeCentroid = False, randomInitialization = False, removePrototypesAfterAssignment = False, initialPrototypes = []):
+    '''Learns motion patterns
+
+    During assignments, if using minClusterSize > 0, prototypes can change (be removed)
+    The argument removePrototypesAfterAssignment indicates whether the prototypes are removed or not'''
+    if len(initialPrototypes) > 0:
+        initialPrototypeIndices = list(range(len(initialPrototypes)))
+        trajectories = [p.getMovingObject().getPositions().asArray().T for p in initialPrototypes]
+    else:
+        initialPrototypeIndices = None
+        trajectories = []
+    trajectories.extend([o.getPositions().asArray().T for o in objects])
+
+    if learn:
+        prototypeIndices = ml.prototypeCluster(trajectories, similarities, minSimilarity, similarityFunc, optimizeCentroid, randomInitialization, initialPrototypeIndices)
+    else:
+        prototypeIndices = initialPrototypeIndices
+
+    if assign:
+        assignedPrototypeIndices, labels = ml.assignToPrototypeClusters(trajectories, prototypeIndices, similarities, minSimilarity, similarityFunc, minClusterSize)
+        if minClusterSize > 0 and removePrototypesAfterAssignment: # use prototypeIndices anyway
+            prototypeIndices = assignedPrototypeIndices
+    else:
+        labels = None    
+
+    return prototypeIndices, labels
+