issues: 508743579

We have an application where we want to use apply_ufunc to apply a function that takes two 1-D arrays and returns a scalar value (basically a reduction over the only axis). We start with two DataArrays that share all the same dimensions - except for the lengths of the dimension we'll be reducing along (t in this case):

```python def diff_mean(X, y): ''' a function that only works on 1d arrays that are different lengths''' assert X.ndim == 1, X.ndim assert y.ndim == 1, y.ndim assert len(X) != len(y), X return X.mean() - y.mean()

X = np.random.random((10, 4, 5)) y = np.random.random((6, 4, 5))

Xda = xr.DataArray(X, dims=('t', 'x', 'y')).chunk({'t': -1, 'x': 2, 'y': 2}) yda = xr.DataArray(y, dims=('t', 'x', 'y')).chunk({'t': -1, 'x': 2, 'y': 2}) ```

Then, we'd like to use apply_ufunc to apply our function (e.g. diff_mean):

python out = xr.apply_ufunc( diff_mean, Xda, yda, vectorize=True, dask="parallelized", output_dtypes=[np.float], input_core_dims=[['t'], ['t']], )

This fails with an error when aligning the t dimensions:

```python-traceback

ValueError Traceback (most recent call last) <ipython-input-4-e90cf6fba482> in <module> 9 dask="parallelized", 10 output_dtypes=[np.float], ---> 11 input_core_dims=[['t'], ['t']], 12 )

~/miniconda3/envs/xarray-ml/lib/python3.7/site-packages/xarray/core/computation.py in apply_ufunc(func, input_core_dims, output_core_dims, exclude_dims, vectorize, join, dataset_join, dataset_fill_value, keep_attrs, kwargs, dask, output_dtypes, output_sizes, *args) 1042 join=join, 1043 exclude_dims=exclude_dims, -> 1044 keep_attrs=keep_attrs 1045 ) 1046 elif any(isinstance(a, Variable) for a in args):

~/miniconda3/envs/xarray-ml/lib/python3.7/site-packages/xarray/core/computation.py in apply_dataarray_vfunc(func, signature, join, exclude_dims, keep_attrs, *args) 222 if len(args) > 1: 223 args = deep_align( --> 224 args, join=join, copy=False, exclude=exclude_dims, raise_on_invalid=False 225 ) 226

~/miniconda3/envs/xarray-ml/lib/python3.7/site-packages/xarray/core/alignment.py in deep_align(objects, join, copy, indexes, exclude, raise_on_invalid, fill_value) 403 indexes=indexes, 404 exclude=exclude, --> 405 fill_value=fill_value 406 ) 407

~/miniconda3/envs/xarray-ml/lib/python3.7/site-packages/xarray/core/alignment.py in align(join, copy, indexes, exclude, fill_value, *objects) 321 "arguments without labels along dimension %r cannot be " 322 "aligned because they have different dimension sizes: %r" --> 323 % (dim, sizes) 324 ) 325

ValueError: arguments without labels along dimension 't' cannot be aligned because they have different dimension sizes: {10, 6}

```

https://nbviewer.jupyter.org/gist/jhamman/0e52d9bb29f679e26b0878c58bb813d2

I'm curious if this can be made to work with apply_ufunc or if we should pursue other options here. Advice and suggestions appreciated.

Output of xr.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.7.3 | packaged by conda-forge | (default, Jul 1 2019, 14:38:56) [Clang 4.0.1 (tags/RELEASE_401/final)] python-bits: 64 OS: Darwin OS-release: 18.7.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 libhdf5: None libnetcdf: None xarray: 0.14.0 pandas: 0.25.1 numpy: 1.17.1 scipy: 1.3.1 netCDF4: None pydap: None h5netcdf: None h5py: None Nio: None zarr: 2.3.2 cftime: None nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: 2.3.0 distributed: 2.3.2 matplotlib: 3.1.1 cartopy: None seaborn: None numbagg: None setuptools: 41.2.0 pip: 19.2.3 conda: None pytest: 5.0.1 IPython: 7.8.0 sphinx: 2.2.0