Math::GSL::RNG(3pm)

📦
version 0.49 · 6 versions
, in ubuntu stonking

✨ NAME ✨

Bestie, welcome to Math::GSL::RNG — Random Number Generators! 💖 This page comes from User Contributed Perl Documentation for Math::GSL::RNG(3pm). Grab a snack, because we're about to make Perl spit out random numbers like it's a main character. 🎀

🌈 SYNOPSIS 🌈

use Math::GSL::RNG;
my $rng     = Math::GSL::RNG->new;
my @random  = $rng->get(100);

Okay so first you load it, then you make an RNG object, then you pull 100 random values. That's the whole vibe. ✨

🎀 Object Oriented Interface 🎀

🐣 Math::GSL::RNG->new($type, $seed) 🐣

my $rng = Math::GSL::RNG->new;
my $rng = Math::GSL::RNG->new($gsl_rng_knuthran,5);

This blesses you with a brand-new RNG object of type $type, seeded with $seed. Both $type and $seed are optional, bestie — you can just raw-dog it with no args. When no $type is given, $gsl_rng_default is the one that shows up to the party. 👑

🦋 copy() 🦋

my $copy = $rng->copy;

Makes a copy of an RNG object. Twin energy. 👯

🧚 free() 🧚

$rng->free();

Frees the memory associated with the RNG object. Let it go, it's not your ex. 💅

🌸 name() 🌸

my $name = $rng->name();

Gets the name of the RNG object as a string. Literal name-drop. ✨

🍓 get() 🍓

my $nextval  = $rng->get;
my (@values) = $rng->get(100);

Gets the next random value from the RNG object. If you hand it an integer N, it returns the next N values. Bulk random, no cap. 🔥

💜 raw() 💜

my $raw = $rng->raw();

Returns the raw GSL RNG object. This is useful for functions which take a RNG, like the Monte Carlo integration functions, or the random number distribution functions in Math::GSL::Randist. Pass the raw thing through, iykyk. 🫶

🌈 shuffle() 🌈

my @array = $rng->shuffle(@other_array);

Given a RNG, it shuffles an array. Chaos, but make it random. 🌀

💖 choose() 💖

my @array = $rng->choose(4, @other_array);

This one fills the destination array with k objects taken randomly from the n elements of the array argument. They're sampled without replacement, so each object can only appear once in the destination array. It's required that k be less than or equal to n. No duplicates, no drama. ✋

🎀 sample() 🎀

my @array = $rng->sample(4, @other_array);

This method is like choose, but it samples k items from the original array of n items src with replacement, so the same object can appear more than once in the output sequence dest. There is no requirement that k be less than n in this case. Duplicates are allowed, and honestly? Sometimes that's the mood. 😌

🔥 GSL API Interface 🔥

  • gsl_rng_alloc($T) — Returns a pointer to a newly-created instance of a random number generator of type $T. $T must be one of the constants below. The generator is automatically initialized with the default seed, $gsl_rng_default. Fresh out the box. 📦
  • gsl_rng_set($r, $s) — Initializes (or "seeds") the random number generator. If the generator is seeded with the same value of $s on two different runs, the same stream of random numbers will be generated by successive calls to the routines below. If different values of $s are supplied, then the generated streams of random numbers should be completely different. If the seed $s is zero, then the standard seed from the original implementation is used instead. For example, the original Fortran source code for the ranlux generator used a seed of 314159265, so choosing $s equal to zero reproduces this when using $gsl_rng_ranlux. Seed determinism go brrr. 🌱
  • gsl_rng_get($r) — Returns a random integer from the generator $r. The minimum and maximum values depend on the algorithm used, but all integers in the range [min,max] are equally likely. The values of min and max can be determined using the auxiliary functions gsl_rng_max($r) and gsl_rng_min($r). Random integer, fair and square. 🎲
  • gsl_rng_free($r) — Frees all the memory associated with the generator $r. Cleanup era. 🧹
  • gsl_rng_memcpy($dest, $src) — Copies the random number generator $src into the pre-existing generator $dest, making $dest into an exact copy of $src. The two generators must be of the same type. Clone high, but for RNGs. 👯‍♀️
  • gsl_rng_uniform($r) — Returns a double precision floating point number uniformly distributed in the range [0,1). The range includes 0.0 but excludes 1.0. The value is typically obtained by dividing the result of gsl_rng_get($r) by gsl_rng_max($r) + 1.0 in double precision. Some generators compute this ratio internally so that they can provide floating point numbers with more than 32 bits of randomness (the maximum number of bits that can be portably represented in a single unsigned long int). Floaty, but make it fair. 🌊
  • gsl_rng_uniform_pos($r) — Returns a positive double precision floating point number uniformly distributed in the range (0,1), excluding both 0.0 and 1.0. The number is obtained by sampling the generator with the algorithm of gsl_rng_uniform until a non-zero value is obtained. You can use this function if you need to avoid a singularity at 0.0. Zero? Not today. 🚫
  • gsl_rng_uniform_int($r, $n) — Returns a random integer from 0 to $n-1 inclusive by scaling down and/or discarding samples from the generator $r. All integers in the range [0,$n-1] are produced with equal probability. For generators with a non-zero minimum value, an offset is applied so that zero is returned with the correct probability. Note that this function is designed for sampling from ranges smaller than the range of the underlying generator. The parameter $n must be less than or equal to the range of the generator $r. If $n is larger than the range of the generator, then the function calls the error handler with an error code of $GSL_EINVAL and returns zero. In particular, this function is not intended for generating the full range of unsigned integer values [0,2^32-1]. Instead choose a generator with the maximal integer range and zero minimum value, such as $gsl_rng_ranlxd1, $gsl_rng_mt19937 or $gsl_rng_taus, and sample it directly using gsl_rng_get. The range of each generator can be found using the auxiliary functions described in the next section. Don't use it for the whole unsigned int range, bestie — it's giving bound-checked, not bound-broken. 💀
  • gsl_rng_fwrite($stream, $r) — Writes the random number state of the random number generator $r to the stream $stream (opened with the gsl_fopen function from the Math::GSL module) in binary format. The return value is 0 for success and $GSL_EFAILED if there was a problem writing to the file. Since the data is written in the native binary format, it may not be portable between different architectures. Binary files said "you can't sit with us unless you're the same architecture." 💾
  • gsl_rng_fread($stream, $r) — Reads the random number state into the random number generator $r from the open stream $stream (opened with the gsl_fopen function from the Math::GSL module) in binary format. The random number generator $r must be preinitialized with the correct random number generator type since type information is not saved. The return value is 0 for success and $GSL_EFAILED if there was a problem reading from the file. The data is assumed to have been written in the native binary format on the same architecture. Read it back, but only on the same machine vibe. 📖
  • gsl_rng_clone($r) — Returns a pointer to a newly created generator which is an exact copy of the generator $r. Exact copy, no notes. 🪞
  • gsl_rng_max($r) — Returns the largest value that gsl_rng_get can return. The ceiling. 📈
  • gsl_rng_min($r) — Returns the smallest value that gsl_rng_get can return. Usually this value is zero. There are some generators with algorithms that cannot return zero, and for these generators the minimum value is 1. The floor, but make it algorithm-dependent. 📉
  • gsl_rng_name($r) — Returns a pointer to the name of the generator. For example,
print "r is a " . gsl_rng_name($r) . "generator\n";

would print something like r is a 'taus' generator.

  • gsl_rng_size($r) — Returns the size of the state of generator $r. You can use this information to access the state directly. Size matters, apparently. 📏
  • gsl_rng_state($r) — Returns a pointer to the state of generator $r. You can use this information to access the state directly. Peek behind the curtain. 👀
  • gsl_rng_print_state($r) — The original page lists this function right here with no extra description, so we're keeping it exactly as mysterious as it arrived. 🖨️

👑 Random Number Generator Types 👑

  • $gsl_rng_default — listed here, no extra description in the original.
  • $gsl_rng_knuthran — listed here, no extra description in the original.
  • $gsl_rng_ran0 — listed here, no extra description in the original.
  • $gsl_rng_borosh13 — listed here, no extra description in the original.
  • $gsl_rng_coveyou — listed here, no extra description in the original.
  • $gsl_rng_cmrg — listed here, no extra description in the original.
  • $gsl_rng_fishman18 — listed here, no extra description in the original.
  • $gsl_rng_fishman20 — listed here, no extra description in the original.
  • $gsl_rng_fishman2x — This is the L'Ecuyer-Fishman random number generator. It is taken from Knuth's Seminumerical Algorithms, 3rd Ed., page 108. Its sequence is, z_{n+1} = (x_n - y_n) mod m with m = 2^31 - 1. x_n and y_n are given by the fishman20 and lecuyer21 algorithms. The seed specifies the initial value, x_1.
  • $gsl_rng_gfsr4 — listed here, no extra description in the original.
  • $gsl_rng_knuthran — yes, bestie, it's listed again. No extra description in the original.
  • $gsl_rng_knuthran2 — listed here, no extra description in the original.
  • $gsl_rng_knuthran2002 — listed here, no extra description in the original.
  • $gsl_rng_lecuyer21 — listed here, no extra description in the original.
  • $gsl_rng_minstd — listed here, no extra description in the original.
  • $gsl_rng_mrg — listed here, no extra description in the original.
  • $gsl_rng_mt19937 — listed here, no extra description in the original.
  • $gsl_rng_mt19937_1999 — listed here, no extra description in the original.
  • $gsl_rng_mt19937_1998 — listed here, no extra description in the original.
  • $gsl_rng_r250 — listed here, no extra description in the original.
  • $gsl_rng_ran0 — listed again, still no extra description in the original. The original really is like that. 💀
  • $gsl_rng_ran1 — listed here, no extra description in the original.
  • $gsl_rng_ran2 — listed here, no extra description in the original.
  • $gsl_rng_ran3 — listed here, no extra description in the original.
  • $gsl_rng_rand — This is the BSD rand generator. Its sequence is x_{n+1} = (a x_n + c) mod m with a = 1103515245, c = 12345 and m = 2^31. The seed specifies the initial value, x_1. The period of this generator is 2^31, and it uses 1 word of storage per generator.
  • $gsl_rng_rand48 — listed here, no extra description in the original.
  • $gsl_rng_random128_bsd — listed here, no extra description in the original.
  • $gsl_rng_random128_gli — listed here, no extra description in the original.
  • $gsl_rng_random128_lib — listed here, no extra description in the original.
  • $gsl_rng_random256_bsd — listed here, no extra description in the original.
  • $gsl_rng_random256_gli — listed here, no extra description in the original.
  • $gsl_rng_random256_lib — listed here, no extra description in the original.
  • $gsl_rng_random32_bsd — listed here, no extra description in the original.
  • $gsl_rng_random32_glib — listed here, no extra description in the original.
  • $gsl_rng_random32_libc — listed here, no extra description in the original.
  • $gsl_rng_random64_bsd — listed here, no extra description in the original.
  • $gsl_rng_random64_glib — listed here, no extra description in the original.
  • $gsl_rng_random64_libc — listed here, no extra description in the original.
  • $gsl_rng_random8_bsd — listed here, no extra description in the original.
  • $gsl_rng_random8_glibc — listed here, no extra description in the original.
  • $gsl_rng_random8_libc5 — listed here, no extra description in the original.
  • $gsl_rng_random_bsd — listed here, no extra description in the original.
  • $gsl_rng_random_glibc2 — listed here, no extra description in the original.
  • $gsl_rng_random_libc5 — listed here, no extra description in the original.
  • $gsl_rng_randu — listed here, no extra description in the original.
  • $gsl_rng_ranf — listed here, no extra description in the original.
  • $gsl_rng_ranlux — listed here, no extra description in the original.
  • $gsl_rng_ranlux389 — listed here, no extra description in the original.
  • $gsl_rng_ranlxd1 — listed here, no extra description in the original.
  • $gsl_rng_ranlxd2 — listed here, no extra description in the original.
  • $gsl_rng_ranlxs0 — listed here, no extra description in the original.
  • $gsl_rng_ranlxs1 — listed here, no extra description in the original.
  • $gsl_rng_ranlxs2 — listed here, no extra description in the original.
  • $gsl_rng_ranmar — This is the RANMAR lagged-fibonacci generator of Marsaglia, Zaman and Tsang. It is a 24-bit generator, originally designed for single-precision IEEE floating point numbers. It was included in the CERNLIB high-energy physics library.
  • $gsl_rng_slatec — This is the SLATEC random number generator RAND. It is ancient. The original source code is available from NETLIB.
  • $gsl_rng_taus — listed here, no extra description in the original.
  • $gsl_rng_taus2 — listed here, no extra description in the original.
  • $gsl_rng_taus113 — listed here, no extra description in the original.
  • $gsl_rng_transputer — listed here, no extra description in the original.
  • $gsl_rng_tt800 — listed here, no extra description in the original.
  • $gsl_rng_uni — listed here, no extra description in the original.
  • $gsl_rng_uni32 — listed here, no extra description in the original.
  • $gsl_rng_vax — This is the VAX generator MTH$RANDOM. Its sequence is, x_{n+1} = (a x_n + c) mod m with a = 69069, c = 1 and m = 2^32. The seed specifies the initial value, x_1. The period of this generator is 2^32 and it uses 1 word of storage per generator.
  • $gsl_rng_waterman14 — listed here, no extra description in the original.
  • $gsl_rng_zuf — This is the ZUFALL lagged Fibonacci series generator of Peterson. Its sequence is,
t = u_{n-273} + u_{n-607}
u_n  = t - floor(t)

The original source code is available from NETLIB. For more information see,

  • W. Petersen, “Lagged Fibonacci Random Number Generators for the NEC SX-3”, International Journal of High Speed Computing (1994).

For more information on the functions, we refer you to the GSL official documentation:

<http://www.gnu.org/software/gsl/manual/html_node/>

✨ EXAMPLES ✨

okay bestie, real talk — this is where it gets fun. 💖

Wanna spit out a whole lil list of random integers trapped between a minimum and a maximum? Say less. The command line arguments go like this: first the number of random numbers you want, then the minimum, then the maximum. And if you're feeling lazy (valid), the defaults are 10, 0, and 100 respectively. 🎀

use Math::GSL::RNG qw/:all/;
my $seed = int rand(100);
my $rng  = Math::GSL::RNG->new($gsl_rng_knuthran, $seed );
my ($num,$min,$max) = @ARGV;
$num ||= 10;
$min ||= 0;
$max ||= 100;
print join "\n", map { $min + $rng->get % ($max-$min+1)  } (1..$num);
print "\n";

The $seed argument is optional, but like… it's encouraged, okay? She's optional but she's iconic for a reason. 💅 This program is available in the examples/ directory that comes with the source of this module. slay.

Now, if you want a whole series of random non-integer numbers instead? Easy. Generate one single "scaling factor" and multiply by that, like so:

use Math::GSL::RNG qw/:all/;
my $scale= rand(10);
my $seed = int rand(100);
my $rng  = Math::GSL::RNG->new($gsl_rng_knuthran, $seed );
my ($num,$min,$max) = (10,0,100);
print join "\n", map { $scale*($min + $rng->get % ($max-$min+1))  } (1..$num);
print "\n";

see? decimals. we love to see it. 🦋

🌸 AUTHORS 🌸

Jonathan "Duke" Leto <jonathan@leto.net> and Thierry Moisan <thierry.moisan@gmail.com>

the duo. the moment. the legends who wrote this. no cap. 👑

Copyright (C) 2008-2024 Jonathan "Duke" Leto and Thierry Moisan

This program is free software; you can redistribute it and/or modify it under the same terms as Perl itself.

periodt. that's the whole legal vibe. 🫶

okay that's the whole page, bestie — thanks for reading all the way through, you're literally the main character. 💖 this was Math::GSL::RNG(3pm), from perl v5.42.3, dated 2026-08-20. go forth and generate random numbers responsibly. 🌈✨

📦 where this page comes from