Description
What happened?
I tried a DataArray with more than one dimension coordinate. Unfortunately xr.align fails, which disallows any arithmetic operation - even when the coords are exactly the same.
What did you expect to happen?
No response
Minimal Complete Verifiable Example
import numpy as np
import xarray as xr
data = np.arange(12).reshape(3, 4)
y = [10, 20, 30]
s = ["a", "b", "c"]
x = [1, 2, 3, 4]
da = xr.DataArray(data, dims=("y", "x"), coords={"x": x, "y": y, "s": ("y", s)})
da = da.set_xindex("s")
xr.align(da, da.y) # errors
da + da # errors
da + da.x # errorsMVCE confirmation
- Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
- Complete example — the example is self-contained, including all data and the text of any traceback.
- Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
- New issue — a search of GitHub Issues suggests this is not a duplicate.
- Recent environment — the issue occurs with the latest version of xarray and its dependencies.
Relevant log output
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
/home/mathause/code/mesmer/devel/prepare_for_surfer.ipynb Cell 28 line 1
12 da = xr.DataArray(data, dims=("y", "x"), coords={"x": x, "y": y, "s": ("y", s)})
13 da = da.set_xindex("s")
---> 15 xr.align(da, da.y) # errors
17 da + da.x # errors
File ~/.conda/envs/mesmer_dev/lib/python3.9/site-packages/xarray/core/alignment.py:888, in align(join, copy, indexes, exclude, fill_value, *objects)
692 """
693 Given any number of Dataset and/or DataArray objects, returns new
694 objects with aligned indexes and dimension sizes.
ref='~/.conda/envs/mesmer_dev/lib/python3.9/site-packages/xarray/core/alignment.py:0'>0</a>;32m (...)
878
879 """
880 aligner = Aligner(
881 objects,
882 join=join,
ref='~/.conda/envs/mesmer_dev/lib/python3.9/site-packages/xarray/core/alignment.py:0'>0</a>;32m (...)
886 fill_value=fill_value,
887 )
--> 888 aligner.align()
889 return aligner.results
File ~/.conda/envs/mesmer_dev/lib/python3.9/site-packages/xarray/core/alignment.py:573, in Aligner.align(self)
571 self.find_matching_indexes()
572 self.find_matching_unindexed_dims()
--> 573 self.assert_no_index_conflict()
574 self.align_indexes()
575 self.assert_unindexed_dim_sizes_equal()
File ~/.conda/envs/mesmer_dev/lib/python3.9/site-packages/xarray/core/alignment.py:318, in Aligner.assert_no_index_conflict(self)
314 if dup:
315 items_msg = ", ".join(
316 f"{k!r} ({v} conflicting indexes)" for k, v in dup.items()
317 )
--> 318 raise ValueError(
319 "cannot re-index or align objects with conflicting indexes found for "
320 f"the following {msg}: {items_msg}\n"
321 "Conflicting indexes may occur when\n"
322 "- they relate to different sets of coordinate and/or dimension names\n"
323 "- they don't have the same type\n"
324 "- they may be used to reindex data along common dimensions"
325 )
ValueError: cannot re-index or align objects with conflicting indexes found for the following dimensions: 'y' (2 conflicting indexes)
Conflicting indexes may occur when
- they relate to different sets of coordinate and/or dimension names
- they don't have the same type
- they may be used to reindex data along common dimensionsAnything else we need to know?
No response
Environment
INSTALLED VERSIONS
commit: feba698
python: 3.10.12 | packaged by conda-forge | (main, Jun 23 2023, 22:40:32) [GCC 12.3.0]
python-bits: 64
OS: Linux
OS-release: 6.2.0-36-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: 1.14.2
libnetcdf: 4.9.2
xarray: 2023.9.1.dev8+gf6d69a1f
pandas: 2.1.1
numpy: 1.24.4
scipy: 1.11.3
netCDF4: 1.6.4
pydap: installed
h5netcdf: 1.2.0
h5py: 3.9.0
Nio: None
zarr: 2.16.1
cftime: 1.6.2
nc_time_axis: 1.4.1
PseudoNetCDF: 3.2.2
iris: 3.7.0
bottleneck: 1.3.7
dask: 2023.9.2
distributed: None
matplotlib: 3.8.0
cartopy: 0.22.0
seaborn: 0.12.2
numbagg: 0.2.2
fsspec: 2023.9.2
cupy: None
pint: 0.20.1
sparse: 0.14.0
flox: 0.7.2
numpy_groupies: 0.10.1
setuptools: 68.2.2
pip: 23.2.1
conda: None
pytest: 7.4.2
mypy: 1.5.1
IPython: 8.15.0
sphinx: None