issues: 811321550

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
811321550 MDU6SXNzdWU4MTEzMjE1NTA= 4922 Bottleneck and dask objects ignore `min_periods` on `rolling` 8881170 open 0     5 2021-02-18T17:43:50Z 2021-12-19T15:18:45Z   CONTRIBUTOR      

What happened:

When bottleneck is installed in an environment, it seems to ignore the min_periods kwarg on ds.rolling(...).

What you expected to happen:

When using ds.rolling(..., min_periods=1), it should be able to handle an array of length 1. Without bottleneck installed, it returns the original value of a length 1 array. With bottleneck installed, the error is:

python-traceback ValueError: Moving window (=2) must between 1 and 1, inclusive

Minimal Complete Verifiable Example:

With bottleneck installed to environment:

python import xarray as xr ds = xr.DataArray([1], dims='time') ds.rolling(time=2, center=True, min_periods=1).mean()

python-traceback ValueError: Moving window (=2) must between 1 and 1, inclusive

Without bottleneck installed to environment:

```python import xarray as xr ds = xr.DataArray([1], dims='time') ds.rolling(time=2, center=True, min_periods=1).mean()

<xarray.DataArray (time: 1)> array([1.]) Dimensions without coordinates: time ```

Anything else we need to know?:

In an applied case, this came up while working on .groupby('time.dayofyear').map(_rolling), where we map a rolling mean function over a defined N days with min_periods=1. Some climatological days (like leap years) will not have the N day requirement, so the min_period catch handles that, but with bottleneck installed it breaks due to the above issue.

Environment:

Output of <tt>xr.show_versions()</tt> INSTALLED VERSIONS ------------------ commit: None python: 3.8.6 | packaged by conda-forge | (default, Jan 25 2021, 23:22:12) [Clang 11.0.1 ] python-bits: 64 OS: Darwin OS-release: 19.6.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: en_US.UTF-8 LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.6 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: 0.8.1 h5py: 3.1.0 Nio: None zarr: 2.6.1 cftime: 1.3.1 nc_time_axis: 1.2.0 PseudoNetCDF: None rasterio: 1.1.8 cfgrib: None iris: None bottleneck: 1.3.2 dask: 2021.01.1 distributed: 2021.01.1 matplotlib: 3.3.3 cartopy: 0.18.0 seaborn: 0.11.1 numbagg: None pint: 0.16.1 setuptools: 49.6.0.post20210108 pip: 21.0 conda: None pytest: 6.2.2 IPython: 7.18.1 sphinx: 3.4.3 
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     13221727 issue

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