dask apply_gufunc in apply_ufunc

[ahuang11]

New xarray ver supports this keyword.

I think allow_rechunk might be good or expose this option to the call e.g. xr.rmse(dask_gufunc_kwargs={...})
http://xarray.pydata.org/en/stable/generated/xarray.apply_ufunc.html

dask_gufunc_kwargs (dict, optional) – Optional keyword arguments passed to dask.array.apply_gufunc if dask=’parallelized’. Possible keywords are output_sizes, allow_rechunk and meta.

[ahuang11]

This is the issue:

ValueError: dimension lat on 0th function argument to apply_ufunc with dask='parallelized' consists of multiple chunks, but is also a core dimension. To fix, either rechunk into a single dask array chunk along this dimension, i.e., ``.chunk(lat: -1)``, or pass ``allow_rechunk=True`` in ``dask_gufunc_kwargs`` but beware that this may significantly increase memory usage.

[raybellwaves]

Correct me if i'm wrong but is this issue same as #99 ?

[aaronspring]

same issue.

Again. I would suggest that we have xskillscore global options that can be accessed by yaml default or context manager as in xr.set_options.
args to set this way. example not proposal>

• dask: parallelized
• allow_rechunk : False
• more?

[bradyrx]

Yeah that would be great, same for climpred. Just need to figure out how xarray does it elegantly.