From bcb526c3136dfd5b77a396b8e5040da884dd6628 Mon Sep 17 00:00:00 2001 From: David Worms Date: Mon, 11 Apr 2011 17:05:30 +0200 Subject: [PATCH] Add ziggurat and ratio methods to readme --- readme.md | 18 +++++++++++++++--- 1 file changed, 15 insertions(+), 3 deletions(-) diff --git a/readme.md b/readme.md index 7cf121b..fdf722d 100644 --- a/readme.md +++ b/readme.md @@ -33,7 +33,7 @@ Seed arguments are always optional and must be provided as unsigned integers. ### [Sampling](http://www.gnu.org/software/gsl/manual/html_node/Sampling-from-a-random-number-generator.html) -- *random.get()* +- *random.get([seed])* Returns a random integer. 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 determined using the auxiliary functions `random.min()` and `random.max()`. - *random.Get([seed])* @@ -47,7 +47,7 @@ Seed arguments are always optional and must be provided as unsigned integers. - *random.max()* Returns the largest value that `random.get()` can return -- *random.uniform()* +- *random.uniform([seed])* Returns a double precision floating point number uniformly distributed in the range [0,1). The range includes 0.0 but excludes 1.0. - *random.Uniform([seed])* @@ -66,7 +66,19 @@ Seed arguments are always optional and must be provided as unsigned integers. *random.Gaussian.next([deviation])* Same as `random.gaussian` but called from a `random.Gaussian` instance. *random.Gaussian.seed* - Returns the seed used by the iterator. + Returns the seed used by the iterator. + +- *random.gaussianZiggurat([seed], [deviation])* + Same as `random.gaussian` but using the alternative Marsaglia-Tsang ziggurat method. + +- *random.GaussianZiggurat([seed])* + Same as `random.Gaussian` but using the alternative Marsaglia-Tsang ziggurat method. + +- *random.gaussianRatioMethod([seed], [deviation])* + Same as `random.gaussian` but using the alternative Kinderman-Monahan-Leva ratio method. + +- *random.GaussianRatioMethod([seed])* + Same as `random.Gaussian` but using the alternative Kinderman-Monahan-Leva ratio method. Exemple