def test_empty_list(self):
# print(len(self.tripA.segments[0].points))
def expected(track):
# print(len(track.segments[0].points))
self.assertTrue(True)
learn_trip.learn_trip(self.tripA, [], expected, self.fail)
def test_empty_list(self):
# print(len(self.tripA.segments[0].points))
def expected(track):
# print(len(track.segments[0].points))
self.assertTrue(True)
learn_trip.learn_trip(self.tripA, [], expected, self.fail)
def test_matching_track(self):
def expected(track):
self.assertTrue(True)
learn_trip.learn_trip(self.tripA, [self.tripB], self.fail, expected)
def test_matching_track(self):
def expected(track):
self.assertTrue(True)
learn_trip.learn_trip(self.tripA, [self.tripB], self.fail, expected)
def annotate_to_next(self, track, life):
""" Stores the track and dequeues another track to be
processed.
Moves the current GPX file from the input path to the
backup path, creates a LIFE file in the life path
and creates a trip entry in the database. Finally the
trip is exported as a GPX file to the output path.
Args:
track (:obj:tracktotrip.Track`)
changes (:obj:`list` of :obj:`dict`): Details of, user made, changes
"""
if not track.name or len(track.name) == 0:
track.name = track.generate_name(self.config['trip_name_format'])
# Export trip to GPX
if self.config['output_path']:
save_to_file(join(expanduser(self.config['output_path']), track.name), track.to_gpx())
# if not self.is_bulk_processing:
# apply_transportation_mode_to(track, life, set(self.clf.labels.classes_))
# learn_transportation_mode(track, self.clf)
# with open(self.config['transportation']['classifier_path'], 'w') as classifier_file:
# self.clf.save_to_file(classifier_file)
# To LIFE
if self.config['life_path']:
name = '.'.join(track.name.split('.')[:-1])
save_to_file(join(expanduser(self.config['life_path']), name), life)
if self.config['life_all']:
life_all_file = expanduser(self.config['life_all'])
else:
life_all_file = join(expanduser(self.config['life_path']), 'all.life')
save_to_file(life_all_file, "\n\n%s" % life, mode='a+')
conn, cur = self.db_connect()
if conn and cur:
db.load_from_segments_annotated(
cur,
self.current_track(),
life,
self.config['location']['max_distance'],
self.config['location']['min_samples']
)
def insert_can_trip(can_trip, mother_trip_id):
""" Insert a cannonical trip into the database
See `db.insert_canonical_trip`
Args:
can_trip (:obj:`tracktotrip.Segment`): Canonical trip
mother_trip_id (int): Id of the trip that originated the canonical
representation
Returns:
int: Canonical trip id
"""
return db.insert_canonical_trip(cur, can_trip, mother_trip_id)
def update_can_trip(can_id, trip, mother_trip_id):
""" Updates a cannonical trip on the database
See `db.update_canonical_trip`
Args:
can_id (int): Canonical trip id
trip (:obj:`tracktotrip.Segment`): Canonical trip
mother_trip_id (int): Id of the trip that originated the canonical
representation
"""
db.update_canonical_trip(cur, can_id, trip, mother_trip_id)
trips_ids = []
for trip in track.segments:
# To database
trip_id = db.insert_segment(
cur,
trip,
self.config['location']['max_distance'],
self.config['location']['min_samples']
)
trips_ids.append(trip_id)
d_latlon = estimate_meters_to_deg(self.config['location']['max_distance'])
# Build/learn canonical trip
canonical_trips = db.match_canonical_trip(cur, trip, d_latlon)
print "canonical_trips # = %d" % len(canonical_trips)
learn_trip(
trip,
trip_id,
canonical_trips,
insert_can_trip,
update_can_trip,
self.config['simplification']['eps'],
d_latlon
)
# db.insertStays(cur, trip, trips_ids, life)
db.dispose(conn, cur)
# Backup
if self.config['backup_path']:
for gpx in self.queue[self.current_day]:
from_path = gpx['path']
to_path = join(expanduser(self.config['backup_path']), gpx['name'])
rename(from_path, to_path)
self.next_day()
self.current_step = Step.preview
return self.current_track()
