add MultiPandasIndex helper class #7182
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| return type(self)(new_indexes) | ||
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| def copy(self: T_MultiPandasIndex, deep: bool = True) -> T_MultiPandasIndex: |
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Needs to be updated following #7140.
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I wonder if it is possible to create a generic ds.set_xindex(
["a", "b"],
MultiIndex([("a", PandasIndex), ("b", PandasIndex), (["a", "b"], BallTreeIndex)),
)(but I'm sure we can find a better syntax... maybe create a hashable sequence that is not a tuple, since that is already taken? and change the list of tuples to a dict). For that concept to work, the return value of What do you think? |
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| seen = set() | ||
| dup_dims = [] | ||
| for d in dims: |
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Since dims is a dict, shouldn't the keys be unique? I don't think you will have repetitions here.
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Ah yes, sure 🙂. But we should probably check for duplicate dimensions so a dict is not what we want for dims.
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You could just do
dim_names = [idx.dim for idk in indexes]
if len(dim_names) != len(set(dim_names)): raise...
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| __slots__ = ("indexes", "dims") | ||
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| def __init__(self, indexes: Mapping[Hashable, PandasIndex]): |
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Always better to use Any for Mapping inputs, due to covariance.
Use Mapping[Any, PandasIndex]
| def _get_unmatched_names( | ||
| self: T_MultiPandasIndex, other: T_MultiPandasIndex | ||
| ) -> set: | ||
| return set(self.indexes).symmetric_difference(other.indexes) |
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I always find the operator notation easier to read: set(self.indexes) ^ set(other.indexes)
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| def _get_unmatched_names( | ||
| self: T_MultiPandasIndex, other: T_MultiPandasIndex | ||
| ) -> set: |
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| return type(self)(new_indexes) | ||
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| def copy(self: T_MultiPandasIndex, deep: bool = True) -> T_MultiPandasIndex: |
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Might as well implement the correct deep-copy behavior which passes the memo dict.
| else: | ||
| return type(self)(new_indexes) | ||
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| def sel(self, labels: dict[Any, Any], **kwargs) -> IndexSelResult: |
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This method should be called internally in Xarray (always with a dict), but maybe there are some cases where one wants to call it directly so Mapping[Any, Any] would be better..
Hmm that could be possible but it think there are just too many possible edge cases for something generic like that. In your specific example ds.set_xindex(
["a", "b"],
MultiIndex([("a", PandasIndex), ("b", PandasIndex), (["a", "b"], BallTreeIndex)),
)we could probably use the BallTreeIndex for point-wise indexing (i.e., with I guess your suggestion is a way around the constraint in the Xarray data model that a coordinate cannot have multiple indexes? I'm afraid there's no easy solution that is generic enough. Maybe some cache to avoid rebuilding the indexes? I.e., |
whats-new.rstapi.rstThis PR adds a
xarray.indexes.MultiPandasIndexhelper class for building custom, meta-indexes that encapsulate multiplePandasIndexinstances. UnlikePandasMultiIndex, the meta-index classes inheriting from this helper class may encapsulate loosely coupled (pandas) indexes, with coordinates of arbitrary dimensions (each coordinate must be 1-dimensional but an Xarray index may be created from coordinates with differing dimensions).Early prototype in this notebook
TODO / TO FIX:
__init__options in subclasses be passed to all thetype(self)(new_indexes)calls inside theMultiPandasIndex"base" class? This could be done via**kwargspassed through... However, mypy will certainly complain (Liskov Substitution Principle).MultiPandasIndexa good name for this helper class?