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  • nbren12 · 3 ✖

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  • support for units · 3 ✖

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  • CONTRIBUTOR 3
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483807351 https://github.com/pydata/xarray/issues/525#issuecomment-483807351 https://api.github.com/repos/pydata/xarray/issues/525 MDEyOklzc3VlQ29tbWVudDQ4MzgwNzM1MQ== nbren12 1386642 2019-04-16T19:16:19Z 2019-04-16T19:16:19Z CONTRIBUTOR

Would __array_function__ solve the problem with operator precedence? I thought they are separate issues because __mul__ and __rmul__ need not call any numpy functions, and will therefore not necessary dispatch to __array_function__.

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  support for units 100295585
482643700 https://github.com/pydata/xarray/issues/525#issuecomment-482643700 https://api.github.com/repos/pydata/xarray/issues/525 MDEyOklzc3VlQ29tbWVudDQ4MjY0MzcwMA== nbren12 1386642 2019-04-12T16:45:17Z 2019-04-12T16:45:17Z CONTRIBUTOR

One additional issue. It seems like pint has some odd behavior with dask. Multiplication (and I assume addition) is not commutative: ``` In [42]: da.ones((10,)) * ureg.m Out[42]: dask.array<mul, shape=(10,), dtype=float64, chunksize=(10,)>

In [43]: ureg.m * da.ones((10,)) Out[43]: dask.array<mul, shape=(10,), dtype=float64, chunksize=(10,)> <Unit('meter')> ```

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  support for units 100295585
482639629 https://github.com/pydata/xarray/issues/525#issuecomment-482639629 https://api.github.com/repos/pydata/xarray/issues/525 MDEyOklzc3VlQ29tbWVudDQ4MjYzOTYyOQ== nbren12 1386642 2019-04-12T16:32:25Z 2019-04-12T16:32:25Z CONTRIBUTOR

@rabernat recent post inspired me to check out this issue. What would this issue entail now that __array_function__ is in numpy? Is there some reason this is more complicated than adding an appropriate __array_function__ to pint's quantity class?

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  support for units 100295585

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