def mapTrajectory(self, tspots, **param): # Creating an update of all the parameters, if necessary. full_params = dict(self.default_params.items()+param.items()) c_tspots = completeTSpots (tspots, self.network) seqs = [detect_stops.detect_mode(c_tspot, self.network, **full_params) for c_tspot in c_tspots] return [model.toTrajectoryObservation(seq) for seq in seqs if seq is not None]
def mapTrajectory(self, tspots, **param): groups = seqGroupBy(tspots, keyf=lambda tsp:tsp.spot.linkId) ttob_seqs = completeGroups(groups, self.network) seqs = [[(ttob.linkId, self.learned_mixtures[ttob.linkId].assignment(ttob.tt), float(ttob.tt)) for ttob in ttob_seq] for ttob_seq in ttob_seqs] return [model.toTrajectoryObservation(seq) for seq in seqs]
def ttObservationToTrajObservation(self, ttob_seq): # pylint:disable=E1101 seq = [(ttob.linkId, self.learned_mixtures[ttob.linkId].assignment(ttob.tt), float(ttob.tt)) for ttob in ttob_seq] return simple_model.toTrajectoryObservation(seq)