def test_interpolator(stop_times, calendar):
df = network._interpolate_stop_times(stop_times, calendar, day='monday')
# unique_trip_id should be generated
assert df.loc[1, 'unique_trip_id'] == 'a_citytrains'
# trip 'a' should be interpolated fully
assert df.loc[df.trip_id == 'a',
'departure_time_sec_interpolate'].tolist() == [
1, 2, 3, 4, 5
]
# trip 'b' should be skipped because it has only one null value
# but its null value should be removed
assert df.loc[df.trip_id == 'b',
'departure_time_sec_interpolate'].tolist() == [1, 2, 3, 4]
# trip 'c' should be interpolated
# no starting value, so first two times removed
# NaN values should be removed from start and end
assert df.loc[df.trip_id == 'c',
'departure_time_sec_interpolate'].tolist() == [3, 4]
# trip 'd' should be removed because it's not in the calendar df
assert len(df.loc[df.trip_id == 'd']) == 0
# trip 'e' should interpolate the second row but leave off the trailing NA
assert df.loc[df.trip_id == 'e',
'departure_time_sec_interpolate'].tolist() == [1, 2, 3, 4]
def test_skip_interpolator(stop_times, calendar):
series = pd.Series(data=[
1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4,
5
],
index=range(25),
name='departure_time_sec')
stop_times['departure_time_sec'] = series
df = network._interpolate_stop_times(stop_times, calendar, day='monday')
# everything should be the same,
# with one row dropped for calendar day filter
assert df.departure_time_sec_interpolate.tolist() == [
1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5
]