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  2. List of random number generators - Wikipedia

    en.wikipedia.org/wiki/List_of_random_number...

    Random number generators are important in many kinds of technical applications, including physics, engineering or mathematical computer studies (e.g., Monte Carlo simulations), cryptography and gambling (on game servers ). This list includes many common types, regardless of quality or applicability to a given use case.

  3. Linear congruential generator - Wikipedia

    en.wikipedia.org/wiki/Linear_congruential_generator

    Python code. The following is an implementation of an LCG in Python, in the form of a generator : from collections.abc import Generator def lcg(modulus: int, a: int, c: int, seed: int) -> Generator[int, None, None]: """Linear congruential generator.""" while True: seed = (a * seed + c) % modulus yield seed.

  4. Random seed - Wikipedia

    en.wikipedia.org/wiki/Random_seed

    A random seed (or seed state, or just seed) is a number (or vector) used to initialize a pseudorandom number generator . For a seed to be used in a pseudorandom number generator, it does not need to be random. Because of the nature of number generating algorithms, so long as the original seed is ignored, the rest of the values that the ...

  5. Pseudorandom number generator - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_number_generator

    A pseudorandom number generator (PRNG), also known as a deterministic random bit generator (DRBG), is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers.

  6. Generator (computer programming) - Wikipedia

    en.wikipedia.org/wiki/Generator_(computer...

    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.

  7. Permuted congruential generator - Wikipedia

    en.wikipedia.org/.../Permuted_Congruential_Generator

    A permuted congruential generator (PCG) is a pseudorandom number generation algorithm developed in 2014 by Dr. M.E. O'Neill which applies an output permutation function to improve the statistical properties of a modulo-2 n linear congruential generator.

  8. Lehmer random number generator - Wikipedia

    en.wikipedia.org/wiki/Lehmer_random_number_generator

    The Lehmer random number generator [1] (named after D. H. Lehmer ), sometimes also referred to as the Park–Miller random number generator (after Stephen K. Park and Keith W. Miller), is a type of linear congruential generator (LCG) that operates in multiplicative group of integers modulo n. The general formula is.

  9. Middle-square method - Wikipedia

    en.wikipedia.org/wiki/Middle-square_method

    To generate a sequence of n-digit pseudorandom numbers, an n-digit starting value is created and squared, producing a 2n-digit number. If the result has fewer than 2n digits, leading zeroes are added to compensate. The middle n digits of the result would be the next number in the sequence and returned as the result. This process is then ...

  10. Lagged Fibonacci generator - Wikipedia

    en.wikipedia.org/wiki/Lagged_Fibonacci_generator

    A Lagged Fibonacci generator ( LFG or sometimes LFib) is an example of a pseudorandom number generator. This class of random number generator is aimed at being an improvement on the 'standard' linear congruential generator. These are based on a generalisation of the Fibonacci sequence .

  11. Python syntax and semantics - Wikipedia

    en.wikipedia.org/wiki/Python_syntax_and_semantics

    def foo(x): if x == 0: bar() else: baz(x) foo(x - 1) and could be written like this in C with K&R indent style : void foo(int x) { if (x == 0) { bar(); } else { baz(x); foo(x - 1); } } Incorrectly indented code could be misread by a human reader differently than it would be interpreted by a compiler or interpreter.