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| id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 868324949 | https://github.com/pydata/xarray/issues/1092#issuecomment-868324949 | https://api.github.com/repos/pydata/xarray/issues/1092 | MDEyOklzc3VlQ29tbWVudDg2ODMyNDk0OQ== | martinitus 7611856 | 2021-06-25T08:36:03Z | 2021-06-25T08:45:23Z | NONE | Hey Folks,
I stumbled over this discussion having a similar use case as described in some comments above: A However, one point I didn't see in the discussion is the following: Hierarchical structures often force a user to come up with some arbitrary order of hierarchy levels. The classical example is document filing: do you put your health insurance documents under One solution to that is a tagging of documents instead of putting them into a hierarchy. This would give the full flexibility to retrieve any flat Back to the above example, one could think of stuff like: ```python get a flat view (DataSet-like object) on all arrays of tagged that have the 'count' tagds: DataSet(View) = tagged.tag_select("count") bar1 = ds.mean(dim="foo") get a flat view (DataSet-like object) on all arrays of tagged that have the "train and "controlled" tagbar2 = tagged.tag_select("train", "controlled").mean(dim="foo") # order of arguments to Just wanted to add that aspect to the discussion even if it might collide with the hierarchical approach! One side note: If every array in the tagged container has exactly one tag, and tags do not repeat, then the whole thing should be semantically identical to a Regards, Martin |
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