mwc-random

Fast, high quality pseudo random number generation https://github.com/bos/mwc-random

Version on this page:0.13.3.2
LTS Haskell 8.5:0.13.5.0
Stackage Nightly 2017-03-20:0.13.5.0
Latest on Hackage:0.13.5.0
BSD3 licensed and maintained by Bryan O'Sullivan

Module documentation for 0.13.3.2

There are no documented modules for this package.

Efficient, general purpose pseudo-random number generation

This package provides the System.Random.MWC module, a Haskell library for generating high-quality pseudo-random numbers in a space- and time-efficient way.

Get involved!

Please report bugs via the github issue tracker.

Master git git repository:

  • git clone git://github.com/bos/mwc-random.git

There's also a Mercurial mirror:

  • hg clone http://bitbucket.org/bos/mwc-random

(You can create and contribute changes using either Mercurial or git.)

Authors

This library is written and maintained by Bryan O'Sullivan, .

Changes

Changes in 0.13.5.0

  • logCategorical added

Changes in 0.13.4.0

  • withSystemRandom uses RtlGenRandom for seeding generator on windows

Changes in 0.13.3.1

  • primitive-0.6 compatibility

Changes in 0.13.3.0

  • Monadic variant of vector shuffle added: uniformShuffleM

  • Context on uniformShuffle loosened

Changes in 0.13.2.2

  • Fixed crash during gen. initialization on Windows when stderr is not available (#36).

Changes in 0.13.2.0

  • Generators for beta, Bernoully, Dirichlet and categorical distributions added.

  • Functions for generating random shuffles added.

Changes in 0.13.1.2

  • GHC 7.9 support

Changes in 0.13.1.1

  • Long standing performance problem in normal distribution fixed (#16)

Changes in 0.13.1.0

  • createSystemRandom added

Changes in 0.13.0.0

  • Workaround for GHC bug 8072 (bug 25). GHC 7.6 on 32-bit platrofms is affected.

  • Generators for truncated exponential and geometric distributions added.

Changes in 0.12.0.0

  • Fucntion asGenIO and asGenST added.

  • Generation of discrete random variates using condensed tables methed. Tables for Poisson and binomial distributions are provided.

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