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/issues/3574#issuecomment-567082163,https://api.github.com/repos/pydata/xarray/issues/3574,567082163,MDEyOklzc3VlQ29tbWVudDU2NzA4MjE2Mw==,941907,2019-12-18T15:32:38Z,2019-12-18T15:32:38Z,NONE,">  `meta = np.ndarray if vectorize is True else None` if the user doesn't explicitly provide `meta`.

Yes, sorry, written this way I now see what you meant and that will likely work indeed.

","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,528701910
https://github.com/pydata/xarray/issues/3574#issuecomment-566938638,https://api.github.com/repos/pydata/xarray/issues/3574,566938638,MDEyOklzc3VlQ29tbWVudDU2NjkzODYzOA==,941907,2019-12-18T08:55:29Z,2019-12-18T08:55:29Z,NONE,"> `meta` should be passed to `blockwise` through `_apply_blockwise` with default `None` (I think) and `np.ndarray` if `vectorize is True`. You'll have to pass the `vectorize` kwarg down to this level I think.

I'm afraid that passing `meta=None` will not help as explained in 
https://github.com/dask/dask/issues/5642 and seen around [this line](https://github.com/dask/dask/blob/3960c6518318f2417658c2fc47cd5b5ece726f8b/dask/array/blockwise.py#L230) because in that case `compute_meta` will be called which might fail with a `np.vectorize`-wrapped function.
I belive a better solution would be to address https://github.com/dask/dask/issues/5642 so that meta isn't computed even though we already provide an output `dtype`.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,528701910
https://github.com/pydata/xarray/issues/3574#issuecomment-565186199,https://api.github.com/repos/pydata/xarray/issues/3574,565186199,MDEyOklzc3VlQ29tbWVudDU2NTE4NjE5OQ==,941907,2019-12-12T21:04:33Z,2019-12-12T21:04:33Z,NONE,"> The problem is that Dask, as of version 2.0, calls functions applied to dask arrays with size zero inputs, to figure out the output array type, e.g., is the output a dense numpy.ndarray or a sparse array?

Yes, now I recall that this was the issue, yeah. It doesn't even depend on your actual data really.

Possible option 3. is to address https://github.com/dask/dask/issues/5642 directly (haven't found time to do a PR yet). Essentially from the code described in that issue I have the feeling that if a `dtype` is passed (as `apply_ufunc` does), then `meta` should not need to be calculated.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,528701910
https://github.com/pydata/xarray/issues/3574#issuecomment-564934693,https://api.github.com/repos/pydata/xarray/issues/3574,564934693,MDEyOklzc3VlQ29tbWVudDU2NDkzNDY5Mw==,941907,2019-12-12T09:57:18Z,2019-12-12T09:57:28Z,NONE,Sounds similar. But I'm not sure why you get the 0d issue when even your chunks don't (from a quick reading) seem to have a 0 size in any of the dimensions.  Could you please show us what is the resulting chunk setup?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,528701910
https://github.com/pydata/xarray/issues/3574#issuecomment-558616375,https://api.github.com/repos/pydata/xarray/issues/3574,558616375,MDEyOklzc3VlQ29tbWVudDU1ODYxNjM3NQ==,941907,2019-11-26T12:56:47Z,2019-11-26T12:56:47Z,NONE,"Another approach would be to bypass `compute_meta` in `dask.blockwise` if `dtype` is provided which seems to be hinted at here 

https://github.com/dask/dask/blob/3960c6518318f2417658c2fc47cd5b5ece726f8b/dask/array/blockwise.py#L234

Perhaps this is an oversight in `dask`, what do you think?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,528701910