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import ast, csv
import socket
import fuel
from enum import Enum
from fuel.datasets import Dataset
from fuel.streams import DataStream
from fuel.iterator import DataIterator
if socket.gethostname() == "adeb.laptop":
DATA_PATH = "/Users/adeb/data/taxi"
else:
DATA_PATH="/data/lisatmp3/auvolat/taxikaggle"
client_ids = {int(x): y+1 for y, x in enumerate(open(DATA_PATH+"/client_ids.txt"))}
class CallType(Enum):
CENTRAL = 0
STAND = 1
STREET = 2
@classmethod
def from_data(cls, val):
if val=='A':
return cls.CENTRAL
elif val=='B':
return cls.STAND
elif val=='C':
return cls.STREET
@classmethod
def to_data(cls, val):
if val==cls.CENTRAL:
return 'A'
elif val==cls.STAND:
return 'B'
elif val==cls.STREET:
return 'C'
class DayType(Enum):
NORMAL = 0
HOLIDAY = 1
HOLIDAY_EVE = 2
@classmethod
def from_data(cls, val):
if val=='A':
return cls.NORMAL
elif val=='B':
return cls.HOLIDAY
elif val=='C':
return cls.HOLIDAY_EVE
@classmethod
def to_data(cls, val):
if val==cls.NORMAL:
return 'A'
elif val==cls.HOLIDAY:
return 'B'
elif val==cls.HOLIDAY_EVE:
return 'C'
class TaxiData(Dataset):
example_iteration_scheme=None
class State:
__slots__ = ('file', 'index', 'reader')
def __init__(self, pathes, columns, has_header=False):
if not isinstance(pathes, list):
pathes=[pathes]
assert len(pathes)>0
self.columns=columns
self.provides_sources = tuple(map(lambda x: x[0], columns))
self.pathes=pathes
self.has_header=has_header
super(TaxiData, self).__init__()
def open(self):
state=self.State()
state.file=open(self.pathes[0])
state.index=0
state.reader=csv.reader(state.file)
if self.has_header:
state.reader.next()
return state
def close(self, state):
state.file.close()
def reset(self, state):
if state.index==0:
state.file.seek(0)
else:
state.index=0
state.file.close()
state.file=open(self.pathes[0])
state.reader=csv.reader(state.file)
return state
def get_data(self, state, request=None):
if request is not None:
raise ValueError
try:
line=state.reader.next()
except (ValueError, StopIteration):
# print state.index
state.file.close()
state.index+=1
if state.index>=len(self.pathes):
raise StopIteration
state.file=open(self.pathes[state.index])
state.reader=csv.reader(state.file)
if self.has_header:
state.reader.next()
return self.get_data(state)
values = []
for idx, (_, constructor) in enumerate(self.columns):
values.append(constructor(line[idx]))
return tuple(values)
taxi_columns = [
("trip_id", lambda x: x),
("call_type", CallType.from_data),
("origin_call", lambda x: 0 if x == '' or x == 'NA' else client_ids[int(x)]),
("origin_stand", lambda x: 0 if x == '' or x == 'NA' else int(x)),
("taxi_id", int),
("timestamp", int),
("day_type", DayType.from_data),
("missing_data", lambda x: x[0] == 'T'),
("polyline", lambda x: map(tuple, ast.literal_eval(x))),
]
taxi_columns_valid = taxi_columns + [
("destination_x", float),
("destination_y", float),
("time", int),
]
train_files=["%s/split/train-%02d.csv" % (DATA_PATH, i) for i in range(100)]
valid_files=["%s/split/valid.csv" % (DATA_PATH,)]
train_data=TaxiData(train_files, taxi_columns)
valid_data=TaxiData(valid_files, taxi_columns_valid)
def train_it():
return DataIterator(DataStream(train_data))
def test_it():
return DataIterator(DataStream(valid_data))
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