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Mersenne Twister. The Mersenne Twister is a general-purpose pseudorandom number generator (PRNG) developed in 1997 by Makoto Matsumoto (松本 眞) and Takuji Nishimura (西村 拓士). [1] [2] Its name derives from the choice of a Mersenne prime as its period length.
Default generator in R and the Python language starting from version 2.3. Xorshift: 2003 G. Marsaglia It is a very fast sub-type of LFSR generators. Marsaglia also suggested as an improvement the xorwow generator, in which the output of a xorshift generator is added with a Weyl sequence.
Jinja (template engine) Jinja is a web template engine for the Python programming language. It was created by Armin Ronacher and is licensed under a BSD License. Jinja is similar to the Django template engine but provides Python-like expressions while ensuring that the templates are evaluated in a sandbox. It is a text-based template language ...
Four letters, fifty letters apart, starting from the first taw on the first verse, form the word תורה ( Torah ). The Bible code ( Hebrew: הצופן התנ"כי, hatzofen hatanachi ), also known as the Torah code, is a purported set of encoded words within a Hebrew text of the Torah that, according to proponents, has predicted significant ...
The ACORN or ″ A dditive Co ngruential R andom N umber″ generators are a robust family of pseudorandom number generators (PRNGs) for sequences of uniformly distributed pseudo-random numbers, introduced in 1989 and still valid in 2019, thirty years later. Introduced by R.S.Wikramaratna, [1] ACORN was originally designed for use in ...
C/C++, C#, D, IDL, Fortran, Java, PHP, Python Any 1997/10/26 1.9.1 GPL Epydoc: Edward Loper Text Python Any 2002/01/— 3.0 (2008) MIT: fpdoc (Free Pascal Documentation Generator) Sebastian Guenther and Free Pascal Core Text (Object)Pascal/Delphi FPC tier 1 targets 2005 3.2.2 GPL reusable parts are GPL with static linking exception Haddock ...
Generator (computer programming) In computer science, a generator is a routine that can be used to control the iteration behaviour of a loop. All generators are also iterators. [1] A generator is very similar to a function that returns an array, in that a generator has parameters, can be called, and generates a sequence of values.
When read, the /dev/random device will only return random bytes within the estimated number of bits of noise in the entropy pool. When the entropy pool is empty, reads from /dev/random will block until additional environmental noise is gathered. [7] The intent is to serve as a cryptographically secure pseudorandom number generator, delivering ...