[Python] Pandas interpolate 'time' vs 'linear' for equally-spaced times

In Pandas interpolate function, is method='time' equivalent to method='linear' when the time index is equally spaced?

A basic example suggests this is the case:

even_index = pd.date_range(
'2019-02-20 10:00 am',
'2019-02-20 2:00 pm',
freq='1 h')
values = [10, np.nan, 30, np.nan, 50]
df_even = pd.DataFrame(values, index=even_index)


>>> df_even.interpolate(method='time')
0
2019-02-20 10:00:00 10.0
2019-02-20 11:00:00 20.0
2019-02-20 12:00:00 30.0
2019-02-20 13:00:00 40.0
2019-02-20 14:00:00 50.0

>>> df_even.interpolate(method='linear')
0
2019-02-20 10:00:00 10.0
2019-02-20 11:00:00 20.0
2019-02-20 12:00:00 30.0
2019-02-20 13:00:00 40.0
2019-02-20 14:00:00 50.0


A difference between 'time' and 'linear' only seems to occur if the time index is not equally spaced:

uneven_index = pd.to_datetime([
'2019-02-20 10:00 am',
'2019-02-20 10:30 am',
'2019-02-20 12:30 pm',
'2019-02-20 1:30 pm',
'2019-02-20 2:00 pm'])
df_uneven = pd.DataFrame(values, index=uneven_index)


>>> df_uneven.interpolate(method='time')
0
2019-02-20 10:00:00 10.000000
2019-02-20 10:30:00 14.000000
2019-02-20 12:30:00 30.000000
2019-02-20 13:30:00 43.333333
2019-02-20 14:00:00 50.000000

>>> df_uneven.interpolate(method='linear')
0
2019-02-20 10:00:00 10.0
2019-02-20 10:30:00 20.0
2019-02-20 12:30:00 30.0
2019-02-20 13:30:00 40.0
2019-02-20 14:00:00 50.0


My question is whether this always holds. Can it be assumed with an equally spaced time index, method='time' will always perform linear interpolation?

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