Re: [Numpy-discussion] Question about optimizing random_standard_normal

[Kevin Sheppard]

That is good news indeed.  Seems like a good upgrade, especially given the breadth of application of normals and the multiple appearances within distributions.c (e.g., Cauchy). Is there a deprecation for a change like this? Or is it just a note and new random numbers in the next major?  I think this is the first time a substantially new algo has replaced an existing one.   Kevin     From: Robert Kern Sent: Monday, February 8, 2021 4:06 PM To: Discussion of Numerical Python Subject: Re: [Numpy-discussion] Question about optimizing random_standard_normal   On Mon, Feb 8, 2021 at 10:53 AM Kevin Sheppard <kevin.k.shepp...@gmail.com> wrote: My reading is that the first 4 are pure C, presumably using the standard practice of inclining so as to make the tightest loop possible, and to allow the compiler to make other optimizations.  The final line is what happens when you replace the existing ziggurat in NumPy with the new one. I read it this way since it has both “new” and “old” with numpy. If it isn’t this, then I’m unsure what “new” and “old” could mean in the context of this thread.   No, these are our benchmarks of `Generator`. `numpy` is testing `RandomState`, which wasn't touched by their contribution.     https://github.com/numpy/numpy/blob/master/benchmarks/benchmarks/bench_random.py#L93-L97   https://github.com/numpy/numpy/blob/master/benchmarks/benchmarks/bench_random.py#L123-L124   I suppose camel-cdr can clarify what was actually done.   But I did run the built-in benchmark: ./runtests.py --bench bench_random.RNG.time_normal_zig and the results are:   -- Robert Kern

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