def can_drop(p0, p1, p2): if p2[2] - p0[2] > 15: return False if geo.dist_meters(p0, p2, geo.NEW_YORK) > 25: return False if geo.dist_meters(p0, p1, geo.NEW_YORK) < 10 or \ geo.dist_meters(p1, p2, geo.NEW_YORK) < 10: return True if geo.angle(p0, p1, p2, geo.NEW_YORK) > 15: return False return True
def pipeline(track, db):
if not isinstance(track, dict):
track = db.tracks.find_one({'_id': bson.objectid.ObjectId(track)})
assert track is not None
print "Processing track", track['_id']
gpx_path = 'data/gpx/%s.gpx' % track['_id']
json_path = 'data/json/%s.json' % track['_id']
sparse_path = 'data/json-sparse/%s.json' % track['_id']
parse_gpx.gpx_to_json(gpx_path, json_path)
track_compress.compress_track_file(json_path, sparse_path)
track_data = json.load(open(json_path))
start_time = track_data[0][2]
duration = track_data[-1][2] - start_time
distance = sum(geo.dist_meters(track_data[i-1], track_data[i], geo.NEW_YORK) for i in xrange(1, len(track_data)))
db.tracks.update({'_id': track['_id']}, {'$set': {'start_time': start_time, 'distance': distance, 'duration': duration}})
return {'duration': duration} # return any/all data that could be useful for incremental updates
