def ERA_pick_times_in_order(self, row, midnight, cutoff):
"""
When the ERA is missing go through an list of alternatives:
"""
# Check for the ERA
if pd.notnull(row['ERA_most_recent_minutes_after_midnight']):
return row['ERA_most_recent_minutes_after_midnight']
# Check for the actual runway departure and air time
# and if both exist: add the two together.
# scheduled_air_time == estimated time from dep runway to arr runway
elif pd.notnull(row['actual_runway_departure_minutes_after_midnight'])\
and pd.notnull(row['scheduled_air_time']):
return row['actual_runway_departure_minutes_after_midnight'] + \
row['scheduled_air_time']
# Else us the gate arrival time and subtract the average time to
# reach the gate for the given airport and airline
elif pd.notnull(row['EGA_most_recent_minutes_after_midnight']) and \
pd.notnull(row['gate_delay_seconds']):
return row['EGA_most_recent_minutes_after_midnight'] - \
row['gate_delay_seconds'] / float(60)
# Else use the scheduled time
elif pd.notnull(
row['scheduled_runway_arrival_minutes_after_midnight']):
return row['scheduled_runway_arrival_minutes_after_midnight']
# Else use the published arrival time
elif pd.notnull(row['published_arrival_minutes_after_midnight']):
return row['published_arrival_minutes_after_midnight']
# Else use the cutoff time as the estimate
elif cutoff:
return dut.minutes_difference(cutoff, midnight)
# Otherwise there's a problem
else:
print row
print "NO TIME TO USE"
def create_data(day):
day.flight_history['departure_airport_timezone_offset'] = \
day.flight_history['departure_airport_timezone_offset'].apply(tfu.offset_func)
day.flight_history['arrival_airport_timezone_offset'] = \
day.flight_history['arrival_airport_timezone_offset'].apply(tfu.offset_func)
grouped = day.flight_history_events.groupby('flight_history_id')
reduced_fhe = grouped.apply(fhe.reduce_fhe_group_to_one_row)
reduced_fhe = reduced_fhe.reset_index()
print "\tCreating file: all"
joined = pd.DataFrame(None)
joined = pd.merge(left=day.flight_history, right=reduced_fhe, on='flight_history_id', how='left', sort=False)
joined = joined.replace("", np.nan)
days_to_parse_arr = ['AGA_most_recent', 'ARA_most_recent', 'EGA_most_recent',
'ERA_most_recent']
days_to_parse_dep = ['AGD_most_recent', 'ARD_most_recent']
days_to_parse = ['AGA_most_recent', 'ARA_most_recent', 'EGA_most_recent',
'ERA_most_recent', 'AGD_most_recent', 'ARD_most_recent']
for d in days_to_parse_arr:
joined[d] = joined[d] + joined['arrival_airport_timezone_offset']
for d in days_to_parse_dep:
joined[d] = joined[d] + joined['departure_airport_timezone_offset']
for d in days_to_parse:
joined[d] = joined[d].apply(dut.parse_to_utc)
for c in date_columns():
joined[c + '_minutes_after_midnight'] = \
joined[c].apply(lambda x: float(dut.minutes_difference(x, day.midnight_time)))
for d in unneces_cols():
del joined[d]
joined = joined.replace("", np.nan)
joined.to_csv('output_csv/parsed_fhe_' + day.folder_name + '_' + "all" + '_filtered_with_dates.csv',
index=False, na_rep="MISSING")
joined_test = pd.merge(left=day.test_data[['flight_history_id']], right=joined,
on='flight_history_id', how='left', sort=False)
joined_test.to_csv('output_csv/parsed_fhe_' + day.folder_name + '_' + "test" + '_filtered_with_dates.csv',
index=False, na_rep="MISSING")
def add_column_asdi_time_est(self, day, data):
date_columns = ['estimatedarrivalutc']
for c in date_columns:
day.asdi_flight_plan[c + '_minutes_after_midnight'] = \
day.asdi_flight_plan[c].apply(lambda x: float(dut.minutes_difference(x, day.midnight_time)))
data_with_asdi_est = pd.merge(left=data, right=day.asdi_flight_plan, on='flight_history_id',
how='left', sort=False)
return data_with_asdi_est
def add_column_position_groundspeed_received(self, day, data):
day.asdi_position.rename(
columns={"latitudedegrees": "curr_latitude",
"longitudedegrees": "curr_longitude"},
inplace=True)
day.asdi_position['received_minutes_after_midnight'] = \
day.asdi_position['received'].apply(lambda x: float(dut.minutes_difference(x, day.midnight_time)))
data_with_curr_pos = pd.merge(left=data, right=day.asdi_position, on='flight_history_id',
how='left', sort=False)
return data_with_curr_pos
def add_column_asdi_time_est(self, day, data):
date_columns = ['estimatedarrivalutc']
for c in date_columns:
day.asdi_flight_plan[c + '_minutes_after_midnight'] = \
day.asdi_flight_plan[c].apply(lambda x: float(dut.minutes_difference(x, day.midnight_time)))
data_with_asdi_est = pd.merge(left=data,
right=day.asdi_flight_plan,
on='flight_history_id',
how='left',
sort=False)
return data_with_asdi_est
def add_column_position_groundspeed_received(self, day, data):
day.asdi_position.rename(columns={
"latitudedegrees": "curr_latitude",
"longitudedegrees": "curr_longitude"
},
inplace=True)
day.asdi_position['received_minutes_after_midnight'] = \
day.asdi_position['received'].apply(lambda x: float(dut.minutes_difference(x, day.midnight_time)))
data_with_curr_pos = pd.merge(left=data,
right=day.asdi_position,
on='flight_history_id',
how='left',
sort=False)
return data_with_curr_pos
