diff options
| -rw-r--r-- | config/simple_mlp_2_cswdt.py | 25 | ||||
| -rw-r--r-- | config/simple_mlp_tgtcls_1_cswdt.py | 5 | ||||
| -rw-r--r-- | config/simple_mlp_tgtcls_1_cswdtx.py | 30 | ||||
| -rw-r--r-- | data.py | 20 | ||||
| -rw-r--r-- | transformers.py | 4 |
5 files changed, 75 insertions, 9 deletions
diff --git a/config/simple_mlp_2_cswdt.py b/config/simple_mlp_2_cswdt.py new file mode 100644 index 0000000..05c9450 --- /dev/null +++ b/config/simple_mlp_2_cswdt.py @@ -0,0 +1,25 @@ +import model.simple_mlp as model + +import data + +n_begin_end_pts = 5 # how many points we consider at the beginning and end of the known trajectory +n_end_pts = 5 + +n_valid = 1000 + +dim_embeddings = [ + ('origin_call', data.n_train_clients+1, 10), + ('origin_stand', data.n_stands+1, 10), + ('week_of_year', 52, 10), + ('day_of_week', 7, 10), + ('qhour_of_day', 24 * 4, 10), + ('day_type', 3, 10), +] + +dim_input = n_begin_end_pts * 2 * 2 + sum(x for (_, _, x) in dim_embeddings) +dim_hidden = [200, 100] +dim_output = 2 + +learning_rate = 0.0001 +momentum = 0.99 +batch_size = 32 diff --git a/config/simple_mlp_tgtcls_1_cswdt.py b/config/simple_mlp_tgtcls_1_cswdt.py index 9261635..45bd39e 100644 --- a/config/simple_mlp_tgtcls_1_cswdt.py +++ b/config/simple_mlp_tgtcls_1_cswdt.py @@ -14,9 +14,10 @@ with open(data.DATA_PATH + "/arrival-clusters.pkl") as f: tgtcls = cPickle.load( dim_embeddings = [ ('origin_call', data.n_train_clients+1, 10), ('origin_stand', data.n_stands+1, 10), - ('week_of_year', 53, 10), + ('week_of_year', 52, 10), ('day_of_week', 7, 10), - ('qhour_of_day', 24 * 4, 10) + ('qhour_of_day', 24 * 4, 10), + ('day_type', 3, 10), ] dim_input = n_begin_end_pts * 2 * 2 + sum(x for (_, _, x) in dim_embeddings) diff --git a/config/simple_mlp_tgtcls_1_cswdtx.py b/config/simple_mlp_tgtcls_1_cswdtx.py new file mode 100644 index 0000000..d51ddde --- /dev/null +++ b/config/simple_mlp_tgtcls_1_cswdtx.py @@ -0,0 +1,30 @@ +import cPickle + +import data + +import model.simple_mlp_tgtcls as model + +n_begin_end_pts = 5 # how many points we consider at the beginning and end of the known trajectory +n_end_pts = 5 + +n_valid = 1000 + +with open(data.DATA_PATH + "/arrival-clusters.pkl") as f: tgtcls = cPickle.load(f) + +dim_embeddings = [ + ('origin_call', data.n_train_clients+1, 10), + ('origin_stand', data.n_stands+1, 10), + ('week_of_year', 52, 10), + ('day_of_week', 7, 10), + ('qhour_of_day', 24 * 4, 10), + ('day_type', 3, 10), + ('taxi_id', 448, 10), +] + +dim_input = n_begin_end_pts * 2 * 2 + sum(x for (_, _, x) in dim_embeddings) +dim_hidden = [500] +dim_output = tgtcls.shape[0] + +learning_rate = 0.0001 +momentum = 0.99 +batch_size = 32 @@ -30,9 +30,7 @@ dataset_size = 1710670 def make_client_ids(): f = h5py.File(H5DATA_PATH, "r") l = f['unique_origin_call'] - r = {} - for i in range(l.shape[0]): - r[l[i]] = i + r = {l[i]: i for i in range(l.shape[0])} return r client_ids = make_client_ids() @@ -43,6 +41,18 @@ def get_client_id(n): else: return 0 +# ---- Read taxi IDs and create reverse dictionnary + +def make_taxi_ids(): + f = h5py.File(H5DATA_PATH, "r") + l = f['unique_taxi_id'] + r = {l[i]: i for i in range(l.shape[0])} + return r + +taxi_ids = make_taxi_ids() + +# ---- Enum types + class CallType(Enum): CENTRAL = 0 STAND = 1 @@ -154,9 +164,9 @@ taxi_columns = [ ("call_type", lambda l: CallType.from_data(l[1])), ("origin_call", lambda l: 0 if l[2] == '' or l[2] == 'NA' else get_client_id(int(l[2]))), ("origin_stand", lambda l: 0 if l[3] == '' or l[3] == 'NA' else int(l[3])), - ("taxi_id", lambda l: int(l[4])), + ("taxi_id", lambda l: taxi_ids[int(l[4])]), ("timestamp", lambda l: int(l[5])), - ("day_type", lambda l: DayType.from_data(l[6])), + ("day_type", lambda l: ord(l[6])-ord('A')), ("missing_data", lambda l: l[7][0] == 'T'), ("polyline", lambda l: map(tuple, ast.literal_eval(l[8]))), ("longitude", lambda l: map(lambda p: p[0], ast.literal_eval(l[8]))), diff --git a/transformers.py b/transformers.py index d6ed611..6ee0df1 100644 --- a/transformers.py +++ b/transformers.py @@ -107,7 +107,8 @@ class TaxiAddDateTime(Transformer): data = next(self.child_epoch_iterator) ts = data[self.id_timestamp] date = datetime.datetime.utcfromtimestamp(ts) - info = (date.isocalendar()[1] - 1, date.weekday(), date.hour * 4 + date.minute / 15) + yearweek = date.isocalendar()[1] - 1 + info = ((51 if yearweek == 52 else yearweek), date.weekday(), date.hour * 4 + date.minute / 15) return data + info class TaxiExcludeTrips(Transformer): @@ -122,4 +123,3 @@ class TaxiExcludeTrips(Transformer): if not data[self.id_trip_id] in self.exclude: break return data - |