Align with join='override' may update index coordinate metadata

[benbovy]

What happened?

It seems that align(*, join="override") may have affected and still may affect the metadata of index coordinate data in an incorrect way. See the MCV example below.

cf. @keewis' original https://github.com/pydata/xarray/pull/6857#discussion_r934425142.

What did you expect to happen?

Index coordinate metadata unaffected by alignment (i.e., metadata is passed through object -> aligned object for each object), like for align with other join methods.

Minimal Complete Verifiable Example

import xarray as xr


ds1 = xr.Dataset(coords={"x": ("x", [1, 2, 3], {"foo": 1})})
ds2 = xr.Dataset(coords={"x": ("x", [1, 2, 3], {"bar": 2})})


aligned1, aligned2 = xr.align(ds1, ds2, join="override")

aligned1.x.attrs
# v2022.03.0 -> {'foo': 1}
# v2022.06.0 -> {'foo': 1, 'bar': 2}
# PR #6857 -> {'foo': 1}
# expected -> {'foo': 1}

aligned2.x.attrs
# v2022.03.0 -> {}
# v2022.06.0 -> {'foo': 1, 'bar': 2}
# PR #6857 -> {'foo': 1, 'bar': 2}
# expected -> {'bar': 2}


aligned11, aligned22 = xr.align(ds1, ds2, join="inner")

aligned11.x.attrs
# {'foo': 1}

aligned22.x.attrs
# {'bar': 2}

MVCE confirmation

• [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• [X] Complete example — the example is self-contained, including all data and the text of any traceback.
• [X] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• [X] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

No response

Anything else we need to know?

No response

Environment

INSTALLED VERSIONS ------------------ commit: None python: 3.9.6 | packaged by conda-forge | (default, Jul 11 2021, 03:36:15) [Clang 11.1.0 ] python-bits: 64 OS: Darwin OS-release: 20.6.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: None LOCALE: (None, 'UTF-8') libhdf5: 1.12.1 libnetcdf: 4.8.1

xarray: 0.21.2.dev137+g30023a484 pandas: 1.4.0 numpy: 1.22.2 scipy: 1.7.1 netCDF4: 1.5.8 pydap: installed h5netcdf: 0.11.0 h5py: 3.4.0 Nio: None zarr: 2.6.1 cftime: 1.5.2 nc_time_axis: 1.2.0 PseudoNetCDF: installed rasterio: 1.2.10 cfgrib: 0.9.8.5 iris: 3.0.4 bottleneck: 1.3.2 dask: 2022.01.1 distributed: 2022.01.1 matplotlib: 3.4.3 cartopy: 0.20.1 seaborn: 0.11.1 numbagg: 0.2.1 fsspec: 0.8.5 cupy: None pint: 0.16.1 sparse: 0.13.0 flox: None numpy_groupies: None setuptools: 57.4.0 pip: 20.2.4 conda: None pytest: 6.2.5 IPython: 7.27.0 sphinx: 3.3.1