Support taking the mean over xarray(pint(numpy(uncertainties)))

[jsignell]

Demo

# /// script
# requires-python = ">=3.11"
# dependencies = [
#   "xarray[complete]@git+https://github.com/jsignell/xarray.git@uncertainties",
#   "uncertainties",
#   "pint",
# ]
# ///
#

from uncertainties import ufloat
import numpy as np
import pint
import xarray as xr

# create some uncertainties values
l1 = [ufloat(1, 0.1), ufloat(2, 0.2), ufloat(3, 0.3), ufloat(4, 0.4), ufloat(5, 0.5), ufloat(6, 0.6), ufloat(7, 0.7)]
l2 = [ufloat(10, 1.), ufloat(20, 2.), ufloat(30, 3.), ufloat(40, 4.), ufloat(50, 5.), ufloat(60, 6.), ufloat(70, 7.)]

# assemble a numpy array, we're at numpy(uncertainties)
numpy_array = np.array([l1, l2])

# attach a unit to it, we're at pint(numpy(uncertainties))
ureg = pint.UnitRegistry()
with_unit = numpy_array * ureg.second

# now assemble a DataArray, we're at xarray(pint(numpy(uncertainties)))
data_array = xr.DataArray(with_unit, dims=("a", "b"))

print(data_array.mean(dim="b"))

• Closes Taking a mean along some dimension with units fails. #10842
• Tests added -> still need to figure out how to test this without requiring the uncertainties library
• User visible changes (including notable bug fixes) are documented in whats-new.rst