Pass arbitrary options to sel()

Is your feature request related to a problem?

Currently .sel() accepts two options method and tolerance. These are relevant for default (pandas) indexes but not necessarily for other, custom indexes.

It would be also useful for custom indexes to expose their own selection options, e.g.,

• index query optimization like the dualtree flag of sklearn.neighbors.KDTree.query
• k-nearest neighbors selection with the creation of a new "k" dimension (+ coordinate / index) with user-defined name and size.

From #3223, it would be nice if we could also pass distinct options values per index.

What would be a good API for that?

Describe the solution you'd like

Some ideas:

A. Allow passing a tuple (labels, options_dict) as indexer value

ds.sel(x=([0, 2], {"method": "nearest"}), y=3)

B. Expose an options kwarg that would accept a nested dict

ds.sel(x=[0, 2], y=3, options={"x": {"method": "nearest"}})

Option A does not look very readable. Option B is slightly better, although the nested dictionary is not great.

Any other ideas? Some sort of context manager? Some Index specific API?

Describe alternatives you've considered

The API proposed in #3223 would look great if method and tolerance were the only accepted options, but less so for arbitrary options.

Additional context

No response

Start with the .sel() entry point and the custom Index API, then review issue #3223 for prior API constraints. Compare the proposed tuple and nested-options approaches, and define the accepted API and per-index behavior before implementation; done means the chosen design is documented and supports arbitrary custom-index options.