--- a/python/storage.py	Wed Jul 05 13:16:47 2017 -0400
+++ b/python/storage.py	Wed Jul 05 16:30:04 2017 -0400
@@ -54,7 +54,7 @@
         elif dataType == 'pois':
             dropTables(connection, ['gaussians2d', 'objects_pois'])
         elif dataType == 'prototype':
-            dropTables(connection, ['prototypes', 'prototype_positions', 'prototype_velocities'])
+            dropTables(connection, ['prototypes'])
         else:
             print('Unknown data type {} to delete from database'.format(dataType))
         connection.close()
@@ -592,7 +592,7 @@
 # saving and loading for scene interpretation: POIs and Prototypes
 #########################
 
-def savePrototypesToSqlite(filename, prototypeIndices, trajectoryType, objects = None, nMatchings = None, dbFilenames = None):
+def savePrototypesToSqlite(filename, prototypeIndices, trajectoryType, nMatchings = None, dbFilenames = None):
     '''save the prototype indices
     if objects is not None, the trajectories are also saved in prototype_positions and _velocities
     (prototypeIndices have to be in objects
@@ -604,7 +604,7 @@
     connection = sqlite3.connect(filename)
     cursor = connection.cursor()
     try:
-        cursor.execute('CREATE TABLE IF NOT EXISTS prototypes (id INTEGER, dbfilename VARCHAR, trajectory_type VARCHAR CHECK (trajectory_type IN (\"feature\", \"object\")), nmatchings INTEGER, positions_id INTEGER, PRIMARY KEY (id, dbfilename))')
+        cursor.execute('CREATE TABLE IF NOT EXISTS prototypes (id INTEGER, dbfilename VARCHAR, trajectory_type VARCHAR CHECK (trajectory_type IN (\"feature\", \"object\")), nmatchings INTEGER, PRIMARY KEY (id, dbfilename))')
         for i, protoId in enumerate(prototypeIndices):
             if nMatchings is not None:
                 n = nMatchings[i]
@@ -614,14 +614,7 @@
                 dbfn = dbFilenames[i]
             else:
                 dbfn = filename
-            cursor.execute('INSERT INTO prototypes (id, dbfilename, trajectory_type, nmatchings, positions_id) VALUES ({},\"{}\",\"{}\",{}, {})'.format(protoId, dbfn, trajectoryType, n, i))
-        if objects is not None: # save positions and velocities
-            features = []
-            for i, o in enumerate(objects):
-                f = copy(o)
-                f.num = i
-                features.append(f)
-            saveTrajectoriesToTable(connection, features, 'feature', 'prototype')
+            cursor.execute('INSERT INTO prototypes (id, dbfilename, trajectory_type, nmatchings) VALUES (?,?,?,?)', (protoId, dbfn, trajectoryType, n))
     except sqlite3.OperationalError as error:
         printDBError(error)
     connection.commit()
@@ -630,7 +623,7 @@
 def savePrototypeAssignments(filename, objects):
     pass
 
-def loadPrototypesFromSqlite(filename):
+def loadPrototypesFromSqlite(filename, withTrajectories = True):
     'Loads prototype ids and matchings (if stored)'
     connection = sqlite3.connect(filename)
     cursor = connection.cursor()
@@ -638,7 +631,7 @@
     dbFilenames = []
     trajectoryTypes = []
     nMatchings = []
-    trajectoryNumbers = []
+    objects = []
     try:
         cursor.execute('SELECT * FROM prototypes')
         for row in cursor:
@@ -647,12 +640,15 @@
             trajectoryTypes.append(row[2])
             if row[3] is not None:
                 nMatchings.append(row[3])
-            if row[4] is not None:
-                trajectoryNumbers.append(row[4])
-        if tableExists(connection, 'prototype_positions'): # load prototypes trajectories
-            objects = loadTrajectoriesFromSqlite(filename, 'feature', trajectoryNumbers, tablePrefix = 'prototype')
-        else:
-            objects = None
+        if withTrajectories:
+            loadingInformation = {}
+            for dbfn, trajType, protoId in zip(dbFilenames, trajectoryTypes, prototypeIndices):
+                if (dbfn, trajType) in loadingInformation:
+                    loadingInformation[(dbfn, trajType)].append(protoId)
+                else:
+                    loadingInformation[(dbfn, trajType)] = [protoId]
+            for k, v in loadingInformation.iteritems():
+                objects += loadTrajectoriesFromSqlite(k[0], k[1], v)
     except sqlite3.OperationalError as error:
         printDBError(error)
     connection.close()

--- 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')