def load_speeds_for_year(self, year, directory, recalc_field_lengths=False):
if self._verbose:
print "Loading speeds for station ", self.id
current_day = date(year, 1, 1)
last_day = date(year, 12, 31)
one_day = timedelta(days=1)
n_days = (last_day - current_day).days
# initialize empty 2D array to hold speeds
# dimensions: date (n_days), timeslot (288 5-min slots)
self.speeds = empty((n_days, 288), dtype=object)
for day in range(n_days):
if self._verbose:
print " Loading speeds for ", current_day
# If there are no detectors, there are no valid speeds
if self.detector_list == []:
day_speeds = [None] * 288
# Otherwise, load speeds from each detector
else:
try:
traffic_file = self.traffic_filename_from_date(current_day)
tr = TrafficReader(path.join(directory, traffic_file))
# average 1min speeds across detectors
day_speeds = impute.average_multilist(
[detector.load_speeds(tr, recalc_field_lengths)
for detector in self.detector_list])
# "short duration temporal linear regression" = impute gaps
# up to 3 slots long use adjacent values
day_speeds = impute.impute_range(day_speeds,
impute_length=3,
input_length=3)
# average 1min speeds to 5min speeds
day_speeds = impute.average_list(day_speeds, 5)
# "short duration temporal linear regression" again
day_speeds = impute.impute_range(day_speeds,
impute_length=3,
input_length=3)
# remove any single missing values by averaging adjacent
# values
day_speeds = impute.impute1(day_speeds)
except IOError:
# If there is no file for the given day, add a list of
# invalid speeds
day_speeds = [None] * 288
self.speeds[day,:] = day_speeds
current_day = current_day + one_day
return self.speeds
def long_temporal_impute(self):
# if there are no staions in this corridor don't do anything
if len(self.station_list) == 0:
return
# speed array dimensions: station, day, time
speeds = self.speeds
for station in range(speeds.shape[0]):
for day in range(speeds.shape[1]):
speeds[station, day, :] = impute.impute_range(list(speeds[station, day, :]),
impute_length=6,
input_length=6)
def load_speeds(self, traffic_reader, recalc_field_lengths=False):
# if there are no detectors for this station, give it a speed list of all invalid speeds
if self.detector_list == []:
self.speeds = [None] * 288
# otherwise, load the speeds from the detectors
else:
for detector in self.detectors():
detector.load_speeds(traffic_reader, recalc_field_lengths)
speeds = impute.average_multilist([detector.load_speeds(traffic_reader) for detector in self.detector_list])
speeds = impute.impute_range(speeds, impute_length=3, input_length=3)
speeds = impute.average_list(speeds, 5)
self.speed_list = impute.impute1(speeds)
def spatial_impute(self):
# if there are no stations in this corridor, don't do anything
if len(self.station_list) == 0:
return
# dimension 1 of speeds array is day
speeds = self.speeds
for day in range(speeds.shape[1]):
# dimension 2 of speeds array is timeslot
for timeslot in range(speeds.shape[2]):
# impute values along the spatial axis (dimension 0)
speeds[:, day, timeslot] = impute.impute_range(list(speeds[:, day, timeslot]),
impute_length=4,
input_length=1)
def weekly_impute(self):
# if there are no station in this corridor, don't do anytihng
if len(self.station_list) == 0:
return
# dimension 1 is day
# using the first 7 days as starting points, impute over station and time slot for every seventh day
speeds = self.speeds
for start_day in range(7):
# dimension 0 is station
for station in range(speeds.shape[0]):
# dimension 2 is timeslot
for timeslot in range(speeds.shape[2]):
speeds[station, start_day::7, timeslot] = impute.impute_range(list(speeds[station, start_day::7, timeslot]),
impute_length=3,
input_length=2)
