--- a/scripts/process.py	Fri Jul 06 11:13:10 2018 -0400
+++ b/scripts/process.py	Fri Jul 06 15:58:45 2018 -0400
@@ -168,7 +168,7 @@
         lcss = utils.LCSS(metric = args.metric, epsilon = args.epsilon)
         similarityFunc = lambda x,y : lcss.computeNormalized(x, y)
         trainingObjects = [o for tmpobjects in objects.values() for o in tmpobjects]
-        if args.nMPObjects is not None:
+        if args.nMPObjects is not None and args.nMPObjects < len(trainingObjects):
             m = int(np.floor(float(len(trainingObjects))/args.nMPObjects))
             trainingObjects = trainingObjects[::m]
         similarities = -np.ones((len(trainingObjects), len(trainingObjects)))
@@ -179,7 +179,6 @@
             outputPrototypeDatabaseFilename = args.outputPrototypeDatabaseFilename
         # TODO maintain mapping from object prototype to db filename + compute nmatchings before
         clusterSizes = ml.computeClusterSizes(labels, prototypeIndices, -1)
-        #print([clusterSizes[i] for i in prototypeIndices])
         storage.savePrototypesToSqlite(str(parentPath/site.getPath()/outputPrototypeDatabaseFilename), [moving.Prototype(object2VideoSequences[trainingObjects[i]].getDatabaseFilename(False), trainingObjects[i].getNum(), prototypeType, clusterSizes[i]) for i in prototypeIndices])