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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.
JSDoc differs from Javadoc, in that it is specialized to handle JavaScript's dynamic behaviour. [1] An early example using a Javadoc-like syntax to document JavaScript was released in 1999 with the Netscape/Mozilla project Rhino, a JavaScript run-time system written in Java. It included a toy "JSDoc" HTML generator, versioned up to 1.3, as an ...
The generator is not sensitive to the choice of c, as long as it is relatively prime to the modulus (e.g. if m is a power of 2, then c must be odd), so the value c=1 is commonly chosen. The sequence produced by other choices of c can be written as a simple function of the sequence when c=1.
An xorshift* generator applies an invertible multiplication (modulo the word size) as a non-linear transformation to the output of an xorshift generator, as suggested by Marsaglia. [1] All xorshift* generators emit a sequence of values that is equidistributed in the maximum possible dimension (except that they will never output zero for 16 ...
In Python 3.x the range() function [28] returns a generator which computes elements of the list on demand. Elements are only generated when they are needed (e.g., when print(r[3]) is evaluated in the following example), so this is an example of lazy or deferred evaluation: >>>
An example where convolutions of generating functions are useful allows us to solve for a specific closed-form function representing the ordinary generating function for the Catalan numbers, C n. In particular, this sequence has the combinatorial interpretation as being the number of ways to insert parentheses into the product x 0 · x 1 ·⋯ ...
It can be shown that if is a pseudo-random number generator for the uniform distribution on (,) and if is the CDF of some given probability distribution , then is a pseudo-random number generator for , where : (,) is the percentile of , i.e. ():= {: ()}. Intuitively, an arbitrary distribution can be simulated from a simulation of the standard ...
This is an accepted version of this page This is the latest accepted revision, reviewed on 18 January 2025. High-level programming language Not to be confused with Java (programming language), Javanese script, or ECMAScript. JavaScript Screenshot of JavaScript source code Paradigm Multi-paradigm: event-driven, functional, imperative, procedural, object-oriented Designed by Brendan Eich of ...