--- a/python/storage.py	Mon Jul 10 18:04:41 2017 -0400
+++ b/python/storage.py	Tue Jul 11 17:56:23 2017 -0400
@@ -54,7 +54,7 @@
         elif dataType == 'pois':
             dropTables(connection, ['gaussians2d', 'objects_pois'])
         elif dataType == 'prototype':
-            dropTables(connection, ['prototypes'])
+            dropTables(connection, ['prototypes', 'objects_prototypes'])
         else:
             print('Unknown data type {} to delete from database'.format(dataType))
         connection.close()
@@ -100,13 +100,13 @@
     cursor.execute('CREATE TABLE IF NOT EXISTS indicators (interaction_id INTEGER, indicator_type INTEGER, frame_number INTEGER, value REAL, FOREIGN KEY(interaction_id) REFERENCES interactions(id), PRIMARY KEY(interaction_id, indicator_type, frame_number))')
 
 def insertTrajectoryQuery(tableName):
-    return "INSERT INTO "+tableName+" (trajectory_id, frame_number, x_coordinate, y_coordinate) VALUES (?,?,?,?)"
+    return "INSERT INTO "+tableName+" VALUES (?,?,?,?)"
 
 def insertObjectQuery():
-    return "INSERT INTO objects (object_id, road_user_type, n_objects) VALUES (?,?,?)"
+    return "INSERT INTO objects VALUES (?,?,?)"
 
 def insertObjectFeatureQuery():
-    return "INSERT INTO objects_features (object_id, trajectory_id) VALUES (?,?)"
+    return "INSERT INTO objects_features VALUES (?,?)"
 
 def createIndex(connection, tableName, columnName, unique = False):
     '''Creates an index for the column in the table
@@ -152,28 +152,6 @@
     except sqlite3.OperationalError as error:
         printDBError(error)
 
-def loadPrototypeMatchIndexesFromSqlite(filename):
-    """
-    This function loads the prototypes table in the database of name <filename>.
-    It returns a list of tuples representing matching ids : [(prototype_id, matched_trajectory_id),...]
-    """
-    matched_indexes = []
-
-    connection = sqlite3.connect(filename)
-    cursor = connection.cursor()
-
-    try:
-        cursor.execute('SELECT * from prototypes order by prototype_id, trajectory_id_matched')
-    except sqlite3.OperationalError as error:
-        printDBError(error)
-        return []
-
-    for row in cursor:
-        matched_indexes.append((row[0],row[1]))
-
-    connection.close()
-    return matched_indexes
-
 def getObjectCriteria(objectNumbers):
     if objectNumbers is None:
         query = ''
@@ -432,7 +410,7 @@
     # Parse curvilinear position structure
     elif(trajectoryType == 'curvilinear'):
         createCurvilinearTrajectoryTable(cursor)
-        curvilinearQuery = "insert into curvilinear_positions (trajectory_id, frame_number, s_coordinate, y_coordinate, lane) values (?,?,?,?,?)"
+        curvilinearQuery = "INSERT INTO curvilinear_positions VALUES (?,?,?,?,?)"
         for obj in objects:
             num = obj.getNum()
             frameNum = obj.getFirstInstant()
@@ -485,7 +463,7 @@
     roadUserNumbers = list(interaction.getRoadUserNumbers())
     cursor.execute('INSERT INTO interactions VALUES({}, {}, {}, {}, {})'.format(interaction.getNum(), roadUserNumbers[0], roadUserNumbers[1], interaction.getFirstInstant(), interaction.getLastInstant()))
 
-def saveInteractions(filename, interactions):
+def saveInteractionsToSqlite(filename, interactions):
     'Saves the interactions in the table'
     connection = sqlite3.connect(filename)
     cursor = connection.cursor()
@@ -503,7 +481,7 @@
         if indicator[instant]:
             cursor.execute('INSERT INTO indicators VALUES({}, {}, {}, {})'.format(interactionNum, events.Interaction.indicatorNameToIndices[indicator.getName()], instant, indicator[instant]))
 
-def saveIndicators(filename, interactions, indicatorNames = events.Interaction.indicatorNames):
+def saveIndicatorsToSqlite(filename, interactions, indicatorNames = events.Interaction.indicatorNames):
     'Saves the indicator values in the table'
     connection = sqlite3.connect(filename)
     cursor = connection.cursor()
@@ -521,7 +499,7 @@
     connection.commit()
     connection.close()
 
-def loadInteractions(filename):
+def loadInteractionsFromSqlite(filename):
     '''Loads interaction and their indicators
     
     TODO choose the interactions to load'''
@@ -529,7 +507,7 @@
     connection = sqlite3.connect(filename)
     cursor = connection.cursor()
     try:
-        cursor.execute('select INT.id, INT.object_id1, INT.object_id2, INT.first_frame_number, INT.last_frame_number, IND.indicator_type, IND.frame_number, IND.value from interactions INT, indicators IND WHERE INT.id = IND.interaction_id ORDER BY INT.id, IND.indicator_type, IND.frame_number')
+        cursor.execute('SELECT INT.id, INT.object_id1, INT.object_id2, INT.first_frame_number, INT.last_frame_number, IND.indicator_type, IND.frame_number, IND.value from interactions INT, indicators IND WHERE INT.id = IND.interaction_id ORDER BY INT.id, IND.indicator_type, IND.frame_number')
         interactionNum = -1
         indicatorTypeNum = -1
         tmpIndicators = {}
@@ -597,16 +575,26 @@
     connection = sqlite3.connect(filename)
     cursor = connection.cursor()
     try:
-        cursor.execute('CREATE TABLE IF NOT EXISTS prototypes (filename VARCHAR, id INTEGER, trajectory_type VARCHAR CHECK (trajectory_type IN (\"feature\", \"object\")), nmatchings INTEGER, PRIMARY KEY (filename, id))')
+        cursor.execute('CREATE TABLE IF NOT EXISTS prototypes (prototype_filename VARCHAR, prototype_id INTEGER, trajectory_type VARCHAR CHECK (trajectory_type IN (\"feature\", \"object\")), nmatchings INTEGER, PRIMARY KEY (prototype_filename, prototype_id, trajectory_type))')
         for p in prototypes:
-            cursor.execute('INSERT INTO prototypes (filename, id, trajectory_type, nmatchings) VALUES (?,?,?,?)', (p.getFilename(), p.getNum(), p.getTrajectoryType(), p.getNMatchings()))
+            cursor.execute('INSERT INTO prototypes VALUES(?,?,?,?)', (p.getFilename(), p.getNum(), p.getTrajectoryType(), p.getNMatchings()))
     except sqlite3.OperationalError as error:
         printDBError(error)
     connection.commit()
     connection.close()
 
-def savePrototypeAssignments(filename, objects):
-    pass
+def savePrototypeAssignmentsToSqlite(filename, objects, labels, prototypes):
+    connection = sqlite3.connect(filename)
+    cursor = connection.cursor()
+    try:
+        cursor.execute('CREATE TABLE IF NOT EXISTS objects_prototypes (object_id INTEGER, prototype_filename VARCHAR, prototype_id INTEGER, trajectory_type VARCHAR CHECK (trajectory_type IN (\"feature\", \"object\")), PRIMARY KEY(object_id, prototype_filename, prototype_id, trajectory_type))')
+        for obj, label in zip(objects, labels):
+            proto = prototypes[label]
+            cursor.execute('INSERT INTO objects_prototypes VALUES(?,?,?,?)', (obj.getNum(), proto.getFilename(), proto.getNum(), proto.getTrajectoryType()))
+    except sqlite3.OperationalError as error:
+        printDBError(error)
+    connection.commit()
+    connection.close()
 
 def loadPrototypesFromSqlite(filename, withTrajectories = True):
     'Loads prototype ids and matchings (if stored)'
@@ -638,7 +626,7 @@
         print('Different types of prototypes in database ({}).'.format(set([p.getTrajectoryType() for p in prototypes])))
     return prototypes
 
-def savePOIs(filename, gmm, gmmType, gmmId):
+def savePOIsToSqlite(filename, gmm, gmmType, gmmId):
     '''Saves a Gaussian mixture model (of class sklearn.mixture.GaussianMixture)
     gmmType is a type of GaussianMixture, learnt either from beginnings or ends of trajectories'''
     connection = sqlite3.connect(filename)
@@ -650,26 +638,26 @@
     try:
         cursor.execute('CREATE TABLE IF NOT EXISTS gaussians2d (poi_id INTEGER, id INTEGER, type VARCHAR, x_center REAL, y_center REAL, covariance VARCHAR, covariance_type VARCHAR, weight, precisions_cholesky VARCHAR, PRIMARY KEY(poi_id, id))')
         for i in xrange(gmm.n_components):
-            cursor.execute('INSERT INTO gaussians2d VALUES({}, {}, \'{}\', {}, {}, \'{}\', \'{}\', {}, \'{}\')'.format(gmmId, i, gmmType, gmm.means_[i][0], gmm.means_[i][1], str(gmm.covariances_[i].tolist()), gmm.covariance_type, gmm.weights_[i], str(gmm.precisions_cholesky_[i].tolist())))
+            cursor.execute('INSERT INTO gaussians2d VALUES(?,?,?,?,?,?,?,?,?)', (gmmId, i, gmmType, gmm.means_[i][0], gmm.means_[i][1], str(gmm.covariances_[i].tolist()), gmm.covariance_type, gmm.weights_[i], str(gmm.precisions_cholesky_[i].tolist())))
         connection.commit()
     except sqlite3.OperationalError as error:
         printDBError(error)
     connection.close()
 
-def savePOIAssignments(filename, objects):
+def savePOIAssignmentsToSqlite(filename, objects):
     'save the od fields of objects'
     connection = sqlite3.connect(filename)
     cursor = connection.cursor()
     try:
         cursor.execute('CREATE TABLE IF NOT EXISTS objects_pois (object_id INTEGER, origin_poi_id INTEGER, destination_poi_id INTEGER, PRIMARY KEY(object_id))')
         for o in objects:
-            cursor.execute('INSERT INTO objects_pois VALUES({},{},{})'.format(o.getNum(), o.od[0], o.od[1]))
+            cursor.execute('INSERT INTO objects_pois VALUES(?,?,?)', (o.getNum(), o.od[0], o.od[1]))
         connection.commit()
     except sqlite3.OperationalError as error:
         printDBError(error)
     connection.close()
     
-def loadPOIs(filename):
+def loadPOIsFromSqlite(filename):
     'Loads all 2D Gaussians in the database'
     from sklearn import mixture # todo if not avalaible, load data in duck-typed class with same fields
     from ast import literal_eval

--- a/python/tests/storage.txt	Mon Jul 10 18:04:41 2017 -0400
+++ b/python/tests/storage.txt	Tue Jul 11 17:56:23 2017 -0400
@@ -6,9 +6,6 @@
 File non_existant_file.txt could not be opened.
 
 >>> nonexistentFilename = "nonexistent"
->>> loadPrototypeMatchIndexesFromSqlite(nonexistentFilename)
-DB Error: no such table: prototypes
-[]
 >>> loadTrajectoriesFromSqlite(nonexistentFilename, 'feature')
 DB Error: no such table: positions
 DB Error: no such table: velocities
@@ -122,8 +119,8 @@
 >>> gmm = GaussianMixture(4, covariance_type = 'full')
 >>> tmp = gmm.fit(points)
 >>> gmmId = 0
->>> savePOIs('pois-tmp.sqlite', gmm, 'end', gmmId)
->>> reloadedGmm = loadPOIs('pois-tmp.sqlite')
+>>> savePOIsToSqlite('pois-tmp.sqlite', gmm, 'end', gmmId)
+>>> reloadedGmm = loadPOIsFromSqlite('pois-tmp.sqlite')
 >>> sum(gmm.predict(points) == reloadedGmm[gmmId].predict(points)) == nPoints
 True
 >>> reloadedGmm[gmmId].gmmTypes[0] == 'end'

--- a/scripts/learn-motion-patterns.py	Mon Jul 10 18:04:41 2017 -0400
+++ b/scripts/learn-motion-patterns.py	Tue Jul 11 17:56:23 2017 -0400
@@ -24,7 +24,8 @@
 parser.add_argument('--subsample', dest = 'positionSubsamplingRate', help = 'rate of position subsampling (1 every n positions)', type = int)
 parser.add_argument('--display', dest = 'display', help = 'display trajectories', action = 'store_true')
 parser.add_argument('--save-similarities', dest = 'saveSimilarities', help = 'save computed similarities (in addition to prototypes)', action = 'store_true')
-#parser.add_argument('--save-matches', dest = 'saveMatches', help = 'save the matched prototype information', action = 'store_true')
+parser.add_argument('--save-matches', dest = 'saveMatches', help = 'saves the assignments of the objects (not for features) to the prototypes', action = 'store_true')
+#parser.add_argument('--assign', dest = 'assign', help = 'saves the assignments of the objects (not for features) to the prototypes', action = 'store_true') # default is train, but one could want only to assign the objects to the loaded prototypes without learning
 
 args = parser.parse_args()
 
@@ -70,7 +71,6 @@
 clusterSizes = ml.computeClusterSizes(labels, prototypeIndices, -1)
 print(clusterSizes)
 
-
 prototypes = [moving.Prototype(args.databaseFilename, objects[i].getNum(), prototypeType, clusterSizes[i]) for i in prototypeIndices]
 if args.outputPrototypeDatabaseFilename is None:
     outputPrototypeDatabaseFilename = args.databaseFilename
@@ -81,10 +81,11 @@
 if args.saveSimilarities:
     np.savetxt(utils.removeExtension(args.databaseFilename)+'-prototype-similarities.txt.gz', similarities, '%.4f')
 
-# if args.saveMatches:
-#     out = storage.openCheck(utils.removeExtension(args.databaseFilename)+'prototypes-matches.csv', 'w')
-#     for o in ojbects:
-#         out.write('')
+labelsToProtoIndices = {protoId: i for i, protoId in enumerate(prototypeIndices)}
+if args.saveMatches: # or args.assign
+# save in the db that contained originally the data
+    # retirer les assignations anterieures?
+    storage.savePrototypeAssignmentsToSqlite(args.databaseFilename, objects, [labelsToProtoIndices[l] for l in labels], prototypes)
 
 if args.display:
     from matplotlib.pyplot import figure, show, axis

--- a/scripts/learn-poi.py	Mon Jul 10 18:04:41 2017 -0400
+++ b/scripts/learn-poi.py	Tue Jul 11 17:56:23 2017 -0400
@@ -65,7 +65,7 @@
         plt.title(gmmType)
         print(gmmType+' Clusters:\n{}'.format(ml.computeClusterSizes(labels, range(models[gmmType].n_components))))
     # save
-    storage.savePOIs(args.databaseFilename, models[gmmType], gmmType, gmmId)
+    storage.savePOIsToSqlite(args.databaseFilename, models[gmmType], gmmType, gmmId)
     # save assignments
     if args.assign:
         for o, l in zip(objects, labels):