issues: 1498255931

What is your issue?

Hey all, i have quick use case where i am unsure if that's related to xarray. I just want to do simple arithmetics with a cftime time axis, e.g.

python import xarray as xr import numpy as np time = xr.DataArray(xr.cftime_range(start="2000", periods=6, freq="1MS", calendar="noleap"), dims='time') and then, e.g., compute mid of those timesteps: python time[:-1] + 0.5 * time.diff('time') which results in ```

UFuncTypeError Traceback (most recent call last) Input In [72], in <cell line: 1>() ----> 1 time[1:] + 0.5 * time.diff('time')

File /work/ch0636/g300046/conda_envs/pyremo-dev/lib/python3.9/site-packages/xarray/core/_typed_ops.py:206, in DataArrayOpsMixin.add(self, other) 205 def add(self, other): --> 206 return self._binary_op(other, operator.add)

File /work/ch0636/g300046/conda_envs/pyremo-dev/lib/python3.9/site-packages/xarray/core/dataarray.py:3530, in DataArray._binary_op(self, other, f, reflexive) 3526 other_variable = getattr(other, "variable", other) 3527 other_coords = getattr(other, "coords", None) 3529 variable = ( -> 3530 f(self.variable, other_variable) 3531 if not reflexive 3532 else f(other_variable, self.variable) 3533 ) 3534 coords, indexes = self.coords._merge_raw(other_coords, reflexive) 3535 name = self._result_name(other)

File /work/ch0636/g300046/conda_envs/pyremo-dev/lib/python3.9/site-packages/xarray/core/_typed_ops.py:396, in VariableOpsMixin.add(self, other) 395 def add(self, other): --> 396 return self._binary_op(other, operator.add)

File /work/ch0636/g300046/conda_envs/pyremo-dev/lib/python3.9/site-packages/xarray/core/variable.py:2519, in Variable._binary_op(self, other, f, reflexive) 2516 attrs = self._attrs if keep_attrs else None 2517 with np.errstate(all="ignore"): 2518 new_data = ( -> 2519 f(self_data, other_data) if not reflexive else f(other_data, self_data) 2520 ) 2521 result = Variable(dims, new_data, attrs=attrs) 2522 return result

UFuncTypeError: ufunc 'add' cannot use operands with types dtype('O') and dtype('<m8[ns]') The problem is the differentiation results in `np.timedelta64` objects:python time.diff('time') ![grafik](https://user-images.githubusercontent.com/5659125/207844626-76adf571-92f7-4645-9e9d-5ba01d08afa3.png) with which the arithmetics are not implemented in `cftime`. However, differentiation with `datetime.timdelta` (which is wrapped by `np.timedelta64`) works in this case since it's implemented in cftime, e.g., when i do `np.diff`, it works:python time[:-1] + 0.5 * np.diff(time) ```

i get the expected result. I am not sure what to expect from xarray and if this might be an issue of cftime (e.g., implement differentiation with np.timedelta64). I was wondering why the differentiation with cftime objects results in np.timedelta64 and not datetime.timedelta objects (like in the pure numpy differentation).