On Wed, 2022-06-01 at 18:37 -0500, Juan Nunez-Iglesias wrote: > > For example, in NumPy: > > > > np.median(np.float32([1, 2, 3, 4])) > > > > did return a float64 before and will now return a float32. I > > assume > > because somewhere we write: `(np.float64(3) + np.float32(2)) / 2`. > > Sorry, I missed this part of the discussion — I know the discussion > centered around Python literals being weak, but for NumPy dtypes, I > thought the larger dtype would always win?
Good reading carefully enough to notice :)!
Sorry... my bad, the float64 is a typo. That should have read:
(float32(3) + float32(2)) / 2
Which does show the change in behavior as described/discussed. If
there was a float64 involved, of course the result would be/remain
float64.
- Sebastian
>
> Indeed, reading the NEP I see:
>
> Expression: array([1.], float32) + array(1., float64)
> Old result: array([2.], float32)
> New result: array([2.], float64)
>
> which seems to contradict your statement above?
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