BLD: Fix IntervalTree build warnings #30560
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jschendel
added
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| elif dtype.startswith('uint'): | ||
| fused_prefix = 'uint_' | ||
| elif dtype.startswith('float'): | ||
| fused_prefix = '' |
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open to a better naming convention for the fused types to make this less gross
| self.root.query(result, target[i]) | ||
| try: | ||
| self.root.query(result, target[i]) | ||
| except OverflowError: |
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Need to add these as operations like IntervalTree[uint64].get_indexer([-1]) will raise an OverflowError. See the associated tests I added.
| int64_t | ||
| int32_t | ||
| float64_t | ||
| float32_t |
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I think we can drop support for float32 and int32 dtypes here, which should help reduce build time. There is no practical way to actually get an IntervalTree of these dtypes since IntervalIndex is backed by 2 indexes and we don't have a Float32Index or Int32Index. Will save this for a followup though.
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Soounds good.
im confused by the naming here: why are the float dtypes included in int_scalar_t/uint_scalar_t?
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Yeah, I couldn't think of a good way to name those. Idea is that int_scalar_t/uint_scalar_t are things that are comparable to int/uint, and we want to be able to compare against float in both cases to determine things like 0.5 being in the interval (0, 1).
I tried it without including floats and got "no matching type signature" errors when trying stuff like IntervalTree[int].get_indexer([0.5]).
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Wouldn’t comparisons to float be very inaccurate in the 2 ** 63 plus range where we get unsigned?
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Yes, comparisons will be inaccurate above 2**61, so the issue is also present on the upper/lower ends of the int64 range. Comparisons are still valid below this so probably something we'll have to live with, e.g. the same holds for comparisons against UInt64Index but the behavior is still allowed there.
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thanks @jschendel |
black pandasgit diff upstream/master -u -- "*.py" | flake8 --diffxref #30366
cc @WillAyd