issue_comments: 629229610

This data as json

html_url issue_url id node_id user created_at updated_at author_association body reactions performed_via_github_app issue
https://github.com/pydata/xarray/pull/4060#issuecomment-629229610 https://api.github.com/repos/pydata/xarray/issues/4060 629229610 MDEyOklzc3VlQ29tbWVudDYyOTIyOTYxMA== 5821660 2020-05-15T13:15:19Z 2020-05-15T13:15:19Z MEMBER

Thanks @mathause for your comments and raising those questions. JFTR, I was taking the road from #1815, so my explicit use-case was the multiple (dask) outputs.

  • It might be good to add a test with a reduction and one with vectorize=True.

I'll try to add some tests for the multiple output using dask.

  • Would it be possible to replace the call to dask.array.blockwise (for one output variable) with dask.array.apply_gufunc? Do you know why blockwise is used further below and not dask.array.apply_gufunc? I assume it's due to historical reasons but I am not sure.

AFAIK, apply_gufunc wasn't available at the time these functions were introduced. Good chance, that apply_gufunc can be used for handling single output dask too.

  • dask.array.apply_gufunc does all sorts of stuff - e.g. infer meta. This could potentially solve #4015 (pull #4022) and simplify the call signature of apply_ufunc?

That's a good question. If you want me to go the long way, please be aware, that I'm a novice in xarray as well as in dask. A complete refactor of apply_ufunc would be quite some challenge.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   618081836