issue_comments: 1246398771

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https://github.com/pydata/xarray/issues/7031#issuecomment-1246398771 https://api.github.com/repos/pydata/xarray/issues/7031 1246398771 IC_kwDOAMm_X85KSokz 4160723 2022-09-14T08:08:26Z 2022-09-14T08:08:26Z MEMBER

tl;dr: Xarray Index currently supports implementing periodic indexing for label-based indexing but not for location-based (integer) indexing.

There's a big difference now between isel and sel:

  • Dataset.isel() accepts dimension names only
  • Dataset.sel() accepts coordinate names (actually, it falls back to isel when giving dimension names with no coordinate, and I'm wondering if we shouldn't deprecate that?)

Index.isel() is convenient when the underlying index structure can be itself sliced (like pandas.Index objects), so that users don't need to do ds.isel(...).set_xindex(...) every time to explicitly rebuild an index after slicing the Dataset. For a kd-tree structure that may not be possible, i.e., KDTreeIndex.isel() would likely return None causing the index to be dropped in the result, so there would be no way around doing ds.isel(...).set_xindex(...).

Most coordinate and data variables are still sliced via Variable.isel(), which doesn't involve any index. That's why you get an IndexError in your example. (side note: the "index" / "indexing" terminology used everywhere, for both label and integer selection, is quite confusing but I'm not sure how this could be improved).

If we want to support periodic indexing with isel, we would have to implement that in Xarray itself. Alternatively, it might be possible to add some API in Index so that in the case of a periodic index it would return indxr % length from indxr, which Xarray will then pass to Variable.isel(). I'm not sure the latter is a good idea, though. Indexes may work with arbitrary coordinates and dimensions, which would make things too complex (handling conflicts, etc.). Also, I don't know if there's other potential use cases besides periodic indexing?

@TomNicholas your experiment makes it clear that the documentation on this part (#6975) should be improved. Thanks!

 
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