Bottleneck and dask objects ignore `min_periods` on `rolling`

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:

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

Minimal Complete Verifiable Example:

With bottleneck installed to environment:

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

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

Without bottleneck installed to environment:

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:

Start by running the minimal xarray example with and without bottleneck, then trace the rolling implementation and its bottleneck execution path. Compare both results for a length-one array with window 2 and min_periods=1; done means the bottleneck path matches the non-bottleneck result without raising the window-size error.