On 6/30/22, Ewout ter Hoeven <e.m.terhoeven@student.tudelft.nl> wrote:
A function to get the minimum and maximum values of an array simultaneously could be very useful, from both a convenience and performance point of view. Especially when arrays get larger the performance benefit could be significant, and even more if the array doesn't fit in L2/L3 cache or even memory.
There are many cases where not either the minimum or the maximum of an array is required, but both. Think of clipping an array, getting it's range, checking for outliers, normalizing, making a plot like a histogram, etc.
This function could be called aminmax() for example, and also be called like ndarray.minmax(). It should return a tuple (min, max) with the minimum and maximum values of the array, identical to calling (ndarray.min(), ndarray.max()).
With such a function, numpy.ptp() and the special cases of numpy.quantile(a, q=[0,1]) and numpy.percentile(a, q=[0,100]) could also potentially be speeded up, among others.
Potentially argmin and argmax could get the same treatment, being called argminmax().
There is also a very extensive post on Stack Overflow (a bit old already) with discussion and benchmarks: https://stackoverflow.com/questions/12200580/numpy-function-for-simultaneous...
FYI, I have a fairly simple gufunc implementation of `minmax` in ufunclab (https://github.com/WarrenWeckesser/ufunclab), along with `arg_minmax`, `min_argmin` and `max_argmax`. See README.md starting here: https://github.com/WarrenWeckesser/ufunclab#minmax For those familiar with C and gufunc implementation details, you can find the implementations in https://github.com/WarrenWeckesser/ufunclab/blob/main/src/minmax/minmax_gufu.... You'll see that, as far as gufuncs go, these are not very sophisticated. They do not include implementations for all the NumPy data types, and I haven't yet spent much time on optimization. Warren
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