.min() doesn't work on np.datetime64 with a chunked Dataset #5001
Description
Hi all,
if a xr.Dataset is chunked, i cannot do ds.time.min(), i get an error : ufunc 'add' cannot use operands with types dtype('<M8[ns]') and dtype('<M8[ns]'). I don't know if it is expected ?
Moreover, ds2.time.mean() works
Thanks
What happened:
raised an UFuncTypeError: ufunc 'add' cannot use operands with types dtype('<M8[ns]') and dtype('<M8[ns]')
What you expected to happen:
compute the min & max on a chunked datetime64 xarray.DataArray
Minimal Complete Verifiable Example:
import xarray as xr
import numpy as np
obs=200
t0 = np.datetime64("2010-01-01T00:00:00")
tn = t0 + np.timedelta64(123*4, "D")
ds2 = xr.Dataset(
{
"time": (["obs"], np.arange(t0, tn, (tn-t0)/obs)),
},
coords={
"obs": (["obs"], np.arange(obs)),
},
).chunk({"obs": 100})
ds2.time.min()Anything else we need to know?:
ds2.time.mean() works, max & min raise Exception
Environment:
Output of xr.show_versions()
INSTALLED VERSIONS
commit: None
python: 3.7.9 (default, Aug 31 2020, 12:42:55)
[GCC 7.3.0]
python-bits: 64
OS: Linux
OS-release: 4.15.0-133-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: fr_FR.UTF-8
LOCALE: fr_FR.UTF-8
libhdf5: 1.12.0
libnetcdf: 4.7.4
xarray: 0.16.2
pandas: 1.2.1
numpy: 1.19.5
scipy: 1.6.0
netCDF4: 1.5.5.1
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: 2.6.1
cftime: 1.3.1
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: 2021.01.1
distributed: 2021.01.1
matplotlib: 3.3.4
cartopy: None
seaborn: None
numbagg: None
pint: 0.16.1
setuptools: 52.0.0.post20210125
pip: 20.3.3
conda: None
pytest: 6.2.2
IPython: 7.20.0
sphinx: 3.5.0