I think that (ice-9 random) has (random:normal). That would generate a Gaussian random variate with mean zero and standard deviation 1.
On Wed, May 27, 2026 at 7:12 AM Zelphir Kaltstahl < [email protected]> wrote: > On 5/27/26 7:19 AM, λx.x wrote: > > this is somewhat tangential; i am not necessarily talking of hashing, > but more > > cryptographic functions shipped with Guile as a whole. > > > > if Guile is going to ship with a cryptographic hash function, what about > other > > cryptographic functions? Are we satisfied with the RNG interfaces > provided in > > core and SRFI 27? whether they RNGs provided are cryptographically > secure > > does not seem to be documented in the manual, at least not explicitly. > > What I found lacking are functions normal/Gaussian distributed random > number > generation. Last time I checked there was no such thing. Generating a > normal > distribution from uniform distributions can be mathematically quite > challenging. > So many algorithms for approximation, and many of them requiring deep > mathematical understanding to understand when one such algorithm would > yield > good enough results and when not, and what parameters to tweak to make it > suitable and so on and on. Or blindly copying without understanding and > just > praying. Not very keen on having to improvise something like that, with > limited > mathematical understanding and Wikipedia being an impenetrable wall of > math for > such algorithms. > > I went as far as checking NumPy, how normal distributed random numbers are > generated there, but the code sucks so hard, it is also impenetrable for > someone > not knowing the mathematical formula it tried to express and understanding > that > in turn. One letter variables or abbreviations everywhere, that no one > other > than mathematicians will be able to interpret, with no regard for > readability at > all. Just like what one would expect a mathematician without any software > development experience to write : ) > > Having a good (and readable! perhaps with references!) algorithm for that > in the > standard library, or in a supported SRFI, or as an extension to a > supported > SRFI, would be great. And the docs should of course state what purposes it > is > useful for and whether it is cryptographically secure or not. > > Not that Python necessarily is the yardstick for all the things, but here > is its > standard library: > https://docs.python.org/3/library/random.html#random.gauss. > > Best regards, > Zelphir > > -- > repositories: https://codeberg.org/ZelphirKaltstahl > > >
