--- a/scripts/learn-motion-patterns.py	Wed Jul 05 13:16:47 2017 -0400
+++ b/scripts/learn-motion-patterns.py	Wed Jul 05 16:30:04 2017 -0400
@@ -10,8 +10,9 @@
 parser = argparse.ArgumentParser(description='The program learns prototypes for the motion patterns') #, epilog = ''
 #parser.add_argument('--cfg', dest = 'configFilename', help = 'name of the configuration file')
 parser.add_argument('-d', dest = 'databaseFilename', help = 'name of the Sqlite database file', required = True)
+parser.add_argument('-r', dest = 'initialPrototypeDatabaseFilename', help = 'name of the Sqlite database file for prototypes to start the algorithm with')
 parser.add_argument('-t', dest = 'trajectoryType', help = 'type of trajectories to learn from', choices = ['objectfeatures', 'feature', 'object'], default = 'objectfeatures')
-parser.add_argument('--max-nobjectfeatures', dest = 'maxNObjectFeatures', help = 'maximum number of features per object to load', type = int, default = 3)
+parser.add_argument('--max-nobjectfeatures', dest = 'maxNObjectFeatures', help = 'maximum number of features per object to load', type = int, default = 1)
 parser.add_argument('-n', dest = 'nTrajectories', help = 'number of the object or feature trajectories to load', type = int, default = None)
 parser.add_argument('-e', dest = 'epsilon', help = 'distance for the similarity of trajectory points', type = float, required = True)
 parser.add_argument('--metric', dest = 'metric', help = 'metric for the similarity of trajectory points', default = 'cityblock') # default is manhattan distance
@@ -30,13 +31,11 @@
 # 1. learn proto from one file, save in same or another (with traj)
 # 2. load proto, load objects, update proto, save proto
 # 3. assign objects from one db to proto
-# 4. load objects from several files, save in another
+# 4. load objects from several files, save in another -> see metadata: site with view and times
 # 5. keep prototypes, with positions/velocities, in separate db (keep link to original data through filename, type and index)
 
 # TODO add possibility to cluter with velocities
 # TODO add possibility to start with saved prototypes so that one can incrementally learn from several databases
-# save prototypes with database name, add option to keep trajectory along: if saved in same db, no need
-# load proto must load the movingobject
 # save the objects that match the prototypes
 # write an assignment function for objects
 
@@ -68,7 +67,7 @@
 print(clusterSizes)
 
 prototypes = [objects[i] for i in prototypeIndices]
-storage.savePrototypesToSqlite(args.databaseFilename, [p.getNum() for p in prototypes], prototypeType, prototypes, [clusterSizes[i] for i in prototypeIndices]) # if saving filenames, add for example [objects[i].dbFilename for i in prototypeIndices]
+storage.savePrototypesToSqlite(args.databaseFilename, [p.getNum() for p in prototypes], prototypeType, [clusterSizes[i] for i in prototypeIndices]) # if saving filenames, add for example [objects[i].dbFilename for i in prototypeIndices]
 
 if args.saveSimilarities:
     np.savetxt(utils.removeExtension(args.databaseFilename)+'-prototype-similarities.txt.gz', similarities, '%.4f')