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/5179#issuecomment-844486483,https://api.github.com/repos/pydata/xarray/issues/5179,844486483,MDEyOklzc3VlQ29tbWVudDg0NDQ4NjQ4Mw==,1200058,2021-05-19T21:27:17Z,2021-05-19T21:27:17Z,NONE,"fyi, I updated the boolean indexing to support additional or missing dimensions:
https://gist.github.com/Hoeze/96616ef9d179180b0b7de97c97e00a27
I'm using this on a 4D-array with >300GB to flatten three of the four dimensions and it works, even on 64GB of RAM.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,860418546
https://github.com/pydata/xarray/issues/5179#issuecomment-824505721,https://api.github.com/repos/pydata/xarray/issues/5179,824505721,MDEyOklzc3VlQ29tbWVudDgyNDUwNTcyMQ==,1217238,2021-04-22T03:11:21Z,2021-04-22T03:11:21Z,MEMBER,"@max-sixty and I have been having some more discussion about whether this is what `ds[key]` should do for N-dimensional boolean indexing over in #1887.
But regardless of what we want boolean indexing with `[]` to do, this would certainly be welcome functionality and should exist in a dedicated method. `ds[key]` is already very heavily overloaded in Xarray, so a more explicit option is nice to have, e.g., for the benefit of readability and static type checking. For the same reason, I would rather not put it inside `isel()` which already integer based indexing with a different call signature. My tentative suggestion is to call this new method `sel_mask()`, since that's what it does -- selection like `sel`/`isel` except based on a mask.","{""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,860418546
https://github.com/pydata/xarray/issues/5179#issuecomment-823674011,https://api.github.com/repos/pydata/xarray/issues/5179,823674011,MDEyOklzc3VlQ29tbWVudDgyMzY3NDAxMQ==,1217238,2021-04-20T23:51:46Z,2021-04-20T23:51:46Z,MEMBER,I wonder if this is just a better proposal than making N-dimensional boolean indexing an alias for `where`: https://github.com/pydata/xarray/issues/1887#issuecomment-823673654,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,860418546
https://github.com/pydata/xarray/issues/5179#issuecomment-821888349,https://api.github.com/repos/pydata/xarray/issues/5179,821888349,MDEyOklzc3VlQ29tbWVudDgyMTg4ODM0OQ==,5635139,2021-04-17T21:12:11Z,2021-04-17T21:12:11Z,MEMBER,"Ah right, I see now, thanks for explaining.
Allowing pointwise indexing with bool indexes would also be welcome.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,860418546
https://github.com/pydata/xarray/issues/5179#issuecomment-821881984,https://api.github.com/repos/pydata/xarray/issues/5179,821881984,MDEyOklzc3VlQ29tbWVudDgyMTg4MTk4NA==,1200058,2021-04-17T20:22:13Z,2021-04-17T20:27:25Z,NONE,"@max-sixty The reason is that my method is basically a special case of point-wise indexing:
http://xarray.pydata.org/en/stable/indexing.html#more-advanced-indexing
You can get the same result by calling:
```python
core_dim_locs = {key: value for key, value in core_dim_locs_from_cond(mask, new_dim_name=""newdim"")}
# pointwise selection
data.sel(
dim_0=outliers_subset[""dim_0""],
dim_1=outliers_subset[""dim_1""],
dim_2=outliers_subset[""dim_2""]
)
```
(Note that you loose chunk information by this method, that's why it is less efficient)
When you want to select random items from a N-dimensional array, you can either model the result as some sparse array or by stacking the dimensions.
(OK, stacking the dimensions means also a sparse COO encoding...)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,860418546
https://github.com/pydata/xarray/issues/5179#issuecomment-821870239,https://api.github.com/repos/pydata/xarray/issues/5179,821870239,MDEyOklzc3VlQ29tbWVudDgyMTg3MDIzOQ==,5635139,2021-04-17T18:53:05Z,2021-04-17T18:53:05Z,MEMBER,"Thanks for the issue @Hoeze . Multi-dimensional bool indexing is definitely something we'd like to add.
How does your code differ from the proposals in https://github.com/pydata/xarray/issues/1887? In a brief look through the code — thanks for supplying it — I couldn't immediately see why we need a new dimension?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,860418546