BUG: Allow np.percentile to operate on float16 data #29105
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Could use a release note. |
I agree. Not sure how to phrase it though, suggestions are welcome. |
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Fixes #29003
The approach taken to address the issue is to perform index calculations with increased precision, but keep the behaviour that for
arrof dtypefloat16the outputnp.quantile(arr, q)is of the same type.The behaviour to have the same output type makes sense for float input, but cannot hold for integer input. E.g. we want
np.quantile([1, 2], 0.5, method='linear')to output 1.5. For that reason it might also be ok to just upcase the type to float64.There are also some corner cases. For example input (of either the array or the quantile) of type
Fraction. Possible output types could be eitherFractionorfloat64.