interaction with timedelta64

[keewis]

Arrays with dtype timedelta64 are basically quantities with dimension [time], and they even have explicit units.

It would be really useful to be able to convert between those and pint quantities. The core logic should probably live in pint, but I think we should figure out a way to make the conversion easier:

arr = xr.Dataset(
    coords={
        "delta1": ("time", np.arange(100, dtype="timedelta64[s]")),
        "delta2": ("time", np.arange(100), {"units": "s"})
    }
).pint.quantify()
arr.pint.to({"delta1": "s", "delta2": "timedelta64[s]"})

(not sure if overloading .to would be worth it, but if not I'm sure we can come up with something better).

Similarly, I'd like to be able to infer the frequency of a datetime64 object and get the frequency (if any) as a quantity. It seems this works (found here):

from pandas.tseries.frequencies import to_offset

timedelta = to_offset(xr.infer_freq(time)).delta.to_numpy()

where the timedelta would then be converted to pint using the functionality described above.

[lumbric]

I had the same question and posted it here on stackoverflow.

[andrewgsavage]

The core logic should probably live in pint

Here's a PR for the pint logic
hgrecco/pint#1978