Hi,

thanks for this!  Overall I am happy to add this, my only recurring
thought is whether we can/should find a good new namespace.
But my main reason for hoping for a good namespace idea is to add other
functions more easily in the future (e.g. sincos or fused multiply-add
or so) since namespace bloat is a recurring cause of hesitation.

- Sebastian



On Tue, 2026-08-25 at 12:32 +0300, Iason Krommydas via NumPy-Discussion
wrote:
> Hi all,
> 
> I would like to let you know that in
> https://github.com/numpy/numpy/pull/32231, we are implementing a
> fused np.minmax implementation that uses the mechanism to register
> reduction loops to ufuncs added in
> https://github.com/numpy/numpy/pull/31816. The implementation
> includes optimizations such as loop unrolling and SIMD (similar to
> the ones np.min/max were already using). This obviously does not
> remove any actual computation as both min and max need to be computed
> but it does them in a single pass over the input array. We saw a
> 1.25x to a 2x improvement over consecutive min/max calls depending on
> the axis being reduced and the dtype (the 2x comes in the cases where
> the computation is mostly limited by reading from memory).
> 
> This is a long requested feature for NumPy (see
> https://github.com/numpy/numpy/issues/9836 and
> https://stackoverflow.com/questions/12200580/numpy-function-for-simultaneous-max-and-min
>  for example)
> 
> There are ~15 sites in NumPy and ~70 sites in SciPy where both min
> and max are computed consecutively and np.minmax can replace those.
> 
> I'm just sending this email out to inform the community and to also
> welcome feedback if people think this is a bad idea or have thoughts
> to share.
> 
> Cheers,
> Iason.
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