Feature Request: linear interpolation for mean

[Inspirateur]

So I recently discovered this nice library and decided to try it since I got unevenly spaced data,
however I found out today that the .mean() wasn't doing linear interpolation as I thought it would be:

>>> from traces import TimeSeries
>>> t = TimeSeries()
>>> t[0] = 0
>>> t[1] = 0
>>> t[3] = 20
>>> t.mean(0, 2)
0.0

With linear interpolation between 2 points we would find that t[2] = 10 and doing the average from 0 to 2 would give us 3.333 in this example.
A simple optional argument in mean() to choose the interpolation method would be fantastic, and I really think that it would be useful to many users who are not using traces exclusively for binary data (where linear interpolation would make no sense).
I know that we can re-sample the TimeSeries but I think a shortcut like this would be really neat since this library is designed with ease of use in mind.

Thanks for reading and have a nice day 👋

[stringertheory]

@Inspirateur thanks for the suggestion! I agree this would be useful. To double check I'm understanding, in the example you gave the mean between 0 and 2 should be 2.5, right? (and 3.333 if taken between 0 and 3?)

[stringertheory]

added this in 05a1460