Re: [Numpy-discussion] Using logfactorial instead of loggamma in random_poisson sampler
What do you think is the explanation for that? I had assumed that using a lookup table would be faster considering that the loggam implementation has loops and makes calls to elementary functions in it. -- Sent from: http://numpy-discussion.10968.n7.nabble.com/ ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Using logfactorial instead of loggamma in random_poisson sampler
I did a quick test and using random_loggam was about 6% faster than using logfactorial (on Windows). Kevin On Sun, Mar 7, 2021 at 2:40 AM Robert Kern wrote: > On Sat, Mar 6, 2021 at 1:45 PM Warren Weckesser < > warren.weckes...@gmail.com> wrote: > >> At the time, making that change was not a high priority, so I didn't >> pursue it. It does make sense to use the logfactorial function there, >> and I'd be happy to see it updated, but be aware that making the >> change is more work than changing just the function call. >> > > Does it make a big difference? Per NEP 19, even in `Generator`, we do > weigh the cost of changing the stream reasonably highly. Improved accuracy > is likely worthwhile, but a minor performance improvement is probably not. > > -- > Robert Kern > ___ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion > ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Using logfactorial instead of loggamma in random_poisson sampler
On Sat, Mar 6, 2021 at 1:45 PM Warren Weckesser wrote: > At the time, making that change was not a high priority, so I didn't > pursue it. It does make sense to use the logfactorial function there, > and I'd be happy to see it updated, but be aware that making the > change is more work than changing just the function call. > Does it make a big difference? Per NEP 19, even in `Generator`, we do weigh the cost of changing the stream reasonably highly. Improved accuracy is likely worthwhile, but a minor performance improvement is probably not. -- Robert Kern ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Using logfactorial instead of loggamma in random_poisson sampler
Ah, I had a suspicion that it was to preserve the random stream but wasn't too sure. Thanks for the clarification. -- Sent from: http://numpy-discussion.10968.n7.nabble.com/ ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Using logfactorial instead of loggamma in random_poisson sampler
On 3/6/21, zoj613 wrote: > Hi All, > > I noticed that the transformed rejection method for generating Poisson > random variables used in numpy makes use of the `random_loggam` function > which directly calculates the log-gamma function. It appears that a > log-factorial lookup table was added a few years back which could be used > in > place of random_loggam since the input is always an integer. Is there a > reason for not using this table instead? See link below for the line of > code: > > https://github.com/numpy/numpy/blob/6222e283fa0b8fb9ba562dabf6ca9ea7ed65be39/numpy/random/src/distributions/distributions.c#L572 > > Regards > Zolisa > Hi Zolisa, In the pull request where the C function logfactorial was added (https://github.com/numpy/numpy/pull/13761), I originally modified the Poisson code to use logfactorial as you suggest, but Kevin (@bashtage on github) pointed out that the change could potentially alter the random stream for the legacy version. Making the change requires creating separate C functions, one for the legacy code that remains unchanged, and one for the newer Generator class that would use logfactorial. You can see the comments here (click on "Show resolved"): https://github.com/numpy/numpy/pull/13761#pullrequestreview-249973405 At the time, making that change was not a high priority, so I didn't pursue it. It does make sense to use the logfactorial function there, and I'd be happy to see it updated, but be aware that making the change is more work than changing just the function call. Warren > > > -- > Sent from: http://numpy-discussion.10968.n7.nabble.com/ > ___ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion > ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Using logfactorial instead of loggamma in random_poisson sampler
Hi All, I noticed that the transformed rejection method for generating Poisson random variables used in numpy makes use of the `random_loggam` function which directly calculates the log-gamma function. It appears that a log-factorial lookup table was added a few years back which could be used in place of random_loggam since the input is always an integer. Is there a reason for not using this table instead? See link below for the line of code: https://github.com/numpy/numpy/blob/6222e283fa0b8fb9ba562dabf6ca9ea7ed65be39/numpy/random/src/distributions/distributions.c#L572 Regards Zolisa -- Sent from: http://numpy-discussion.10968.n7.nabble.com/ ___ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
