From 46957091433bfa097d7ea19b177bf42a52412f2d Mon Sep 17 00:00:00 2001 From: Raymond Hettinger Date: Thu, 23 Mar 2023 12:10:12 -0500 Subject: [PATCH] Move binomialvariate() to a section for discrete distributions (GH-102955) --- Doc/library/random.rst | 6 +++--- Lib/random.py | 45 +++++++++++++++++++++++------------------- 2 files changed, 28 insertions(+), 23 deletions(-) diff --git a/Doc/library/random.rst b/Doc/library/random.rst index 098684d7270..c192919ac62 100644 --- a/Doc/library/random.rst +++ b/Doc/library/random.rst @@ -404,8 +404,8 @@ Alternative Generator Class that implements the default pseudo-random number generator used by the :mod:`random` module. - .. deprecated:: 3.9 - In the future, the *seed* must be one of the following types: + .. deprecated-removed:: 3.9 3.11 + Formerly the *seed* could be any hashable object. Now it is limited to: :class:`NoneType`, :class:`int`, :class:`float`, :class:`str`, :class:`bytes`, or :class:`bytearray`. @@ -423,7 +423,7 @@ Notes on Reproducibility ------------------------ Sometimes it is useful to be able to reproduce the sequences given by a -pseudo-random number generator. By re-using a seed value, the same sequence should be +pseudo-random number generator. By reusing a seed value, the same sequence should be reproducible from run to run as long as multiple threads are not running. Most of the random module's algorithms and seeding functions are subject to diff --git a/Lib/random.py b/Lib/random.py index 3c4291f6a65..586c3f7f9da 100644 --- a/Lib/random.py +++ b/Lib/random.py @@ -24,7 +24,6 @@ negative exponential gamma beta - binomial pareto Weibull @@ -33,6 +32,11 @@ circular uniform von Mises + discrete distributions + ---------------------- + binomial + + General notes on the underlying Mersenne Twister core generator: * The period is 2**19937-1. @@ -731,6 +735,26 @@ class Random(_random.Random): return y / (y + self.gammavariate(beta, 1.0)) return 0.0 + def paretovariate(self, alpha): + """Pareto distribution. alpha is the shape parameter.""" + # Jain, pg. 495 + + u = 1.0 - self.random() + return u ** (-1.0 / alpha) + + def weibullvariate(self, alpha, beta): + """Weibull distribution. + + alpha is the scale parameter and beta is the shape parameter. + + """ + # Jain, pg. 499; bug fix courtesy Bill Arms + + u = 1.0 - self.random() + return alpha * (-_log(u)) ** (1.0 / beta) + + + ## -------------------- discrete distributions --------------------- def binomialvariate(self, n=1, p=0.5): """Binomial random variable. @@ -816,25 +840,6 @@ class Random(_random.Random): return k - def paretovariate(self, alpha): - """Pareto distribution. alpha is the shape parameter.""" - # Jain, pg. 495 - - u = 1.0 - self.random() - return u ** (-1.0 / alpha) - - def weibullvariate(self, alpha, beta): - """Weibull distribution. - - alpha is the scale parameter and beta is the shape parameter. - - """ - # Jain, pg. 499; bug fix courtesy Bill Arms - - u = 1.0 - self.random() - return alpha * (-_log(u)) ** (1.0 / beta) - - ## ------------------------------------------------------------------ ## --------------- Operating System Random Source ------------------