On Thu, Jun 30, 2022 at 10:56 PM Warren Weckesser < warren.weckes...@gmail.com> wrote:
> On 6/30/22, Ewout ter Hoeven <e.m.terhoe...@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-max-and-min > > > 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_gufunc.c.src > . > 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. > Thanks for sharing Warren. While that is interesting code, for inclusion in NumPy purposes I'd much prefer to see something along the suggestions by Eric and Marten on https://github.com/numpy/numpy/issues/9836 about making it easier to combine existing ufuncs. Adding 500 LoC for a `minmax` (separate from the discussion on whether we want such fused operators) does not seem healthy. It's also a new potential source of bugs, because `minmax` isn't going to yield exactly the same numerical values as `min` and `max` used separately if you do it as a gufunc, and any bug fixes will need to be made in two places. Also, given that `min` and `max` use SIMD instructions, the gufunc `minmax` as you have it now is probably substantially slower - see benchmarks in https://github.com/numpy/numpy/pull/20131. Cheers, Ralf
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