--- a/python/display-trajectories.py	Mon Jul 09 00:46:04 2012 -0400
+++ b/python/display-trajectories.py	Wed Jul 11 16:30:23 2012 -0400
@@ -6,7 +6,7 @@
 import cvutils
 
 from numpy.linalg.linalg import inv
-from numpy.lib.npyio import loadtxt
+from numpy import loadtxt
 
 options, args = getopt.getopt(sys.argv[1:], 'hi:d:t:o:f:',['help']) 
 # alternative long names are a pain to support ,'video-filename=','database-filename=', 'type='

--- a/python/storage.py	Mon Jul 09 00:46:04 2012 -0400
+++ b/python/storage.py	Wed Jul 11 16:30:23 2012 -0400
@@ -66,39 +66,36 @@
     connection.close()
     return matched_indexes
 
-def loadTrajectoriesFromSqlite(filename, trajectoryType, objectNumbers = -1):
-    '''Loads nObjects or the indices in objectNumbers from the database 
-    TODO: load velocities (replace table name 'positions' by 'velocities'
-    TODO: load features as well, other ways of averaging trajectories
-    '''
-    import sqlite3
-    
-    connection = sqlite3.connect(filename) # add test if it open
+def loadTrajectoriesFromTable(connection, tableName, trajectoryType, objectNumbers = -1):
+    '''Loads trajectories (in the general sense) from the given table
+    can be positions or velocities
+
+    returns a moving object'''
     cursor = connection.cursor()
 
     try:
         if trajectoryType == 'feature':
             if type(objectNumbers) == int:
                 if objectNumbers == -1:
-                    cursor.execute('SELECT * from positions order by trajectory_id, frame_number')
+                    cursor.execute('SELECT * from '+tableName+' order by trajectory_id, frame_number')
                 else:
-                    cursor.execute('SELECT * from positions where trajectory_id between 0 and {0} order by trajectory_id, frame_number'.format(objectNumbers))
+                    cursor.execute('SELECT * from {0} where trajectory_id between 0 and {1} order by trajectory_id, frame_number'.format(tableName, objectNumbers))
             elif type(objectNumbers) == list:
-                cursor.execute('SELECT * from positions where trajectory_id in ('+', '.join([str(n) for n in objectNumbers])+') order by trajectory_id, frame_number')
+                cursor.execute('SELECT * from '+tableName+' where trajectory_id in ('+', '.join([str(n) for n in objectNumbers])+') order by trajectory_id, frame_number')
         elif trajectoryType == 'object':
             if type(objectNumbers) == int:
                 if objectNumbers == -1:
-                    cursor.execute('SELECT OF.object_id, P.frame_number, avg(P.x_coordinate), avg(P.y_coordinate) from positions P, objects_features OF where P.trajectory_id = OF.trajectory_id group by object_id, frame_number')
+                    cursor.execute('SELECT OF.object_id, P.frame_number, avg(P.x_coordinate), avg(P.y_coordinate) from '+tableName+' P, objects_features OF where P.trajectory_id = OF.trajectory_id group by object_id, frame_number')
                 else:
-                    cursor.execute('SELECT OF.object_id, P.frame_number, avg(P.x_coordinate), avg(P.y_coordinate) from positions P, objects_features OF where P.trajectory_id = OF.trajectory_id and OF.object_id between 0 and {0} group by object_id, frame_number'.format(objectNumbers))
+                    cursor.execute('SELECT OF.object_id, P.frame_number, avg(P.x_coordinate), avg(P.y_coordinate) from {0} P, objects_features OF where P.trajectory_id = OF.trajectory_id and OF.object_id between 0 and {1} group by object_id, frame_number'.format(tableName, objectNumbers))
             elif type(objectNumbers) == list:
-                cursor.execute('SELECT OF.object_id, P.frame_number, avg(P.x_coordinate), avg(P.y_coordinate) from positions P, objects_features OF where P.trajectory_id = OF.trajectory_id and OF.object_id in ('+', '.join([str(n) for n in objectNumbers])+') group by object_id, frame_number')
+                cursor.execute('SELECT OF.object_id, P.frame_number, avg(P.x_coordinate), avg(P.y_coordinate) from '+tableName+' P, objects_features OF where P.trajectory_id = OF.trajectory_id and OF.object_id in ('+', '.join([str(n) for n in objectNumbers])+') group by object_id, frame_number')
         else:
             print('no trajectory type was chosen')
     except sqlite3.OperationalError as err:
         print('DB Error: {0}'.format(err))
         return []
-    
+
     objId = -1
     obj = None
     objects = []
@@ -115,6 +112,27 @@
     if obj:
         objects.append(obj)
 
+    return objects
+
+def loadTrajectoriesFromSqlite(filename, trajectoryType, objectNumbers = -1):
+    '''Loads nObjects or the indices in objectNumbers from the database 
+    TODO: load feature numbers and not average feature trajectories
+    TODO: other ways of averaging trajectories (load all points, sorted by frame_number and leave the agregation to be done in python)
+    '''
+    import sqlite3
+    
+    connection = sqlite3.connect(filename) # add test if it open
+
+    objects = loadTrajectoriesFromTable(connection, 'positions', trajectoryType, objectNumbers)
+    objectVelocities = loadTrajectoriesFromTable(connection, 'velocities', trajectoryType, objectNumbers)
+
+    if len(objectVelocities) > 0:
+        for o,v in zip(objects, objectVelocities):
+            if o.num == v.num:
+                o.velocities = v.positions
+            else:
+                print('Could not match positions {0} with velocities {1}'.format(o.num, v.num))
+
     connection.close()
     return objects