The boltzmann-samplers package

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Warnings:

Random generators with a uniform distribution conditioned to a given size. See also testing-feat, which is currently a faster method with similar results.


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Properties

Versions0.1.0.0, 0.1.0.0
Change logNone available
Dependenciesad, base (>=4.9 && <5), containers, hashable, hmatrix, ieee754, MonadRandom, mtl, QuickCheck, transformers, unordered-containers, vector [details]
LicenseMIT
AuthorLi-yao Xia
Maintainerlysxia@gmail.com
CategoryData, Generic, Random
Home pagehttps://github.com/Lysxia/boltzmann-samplers#readme
Source repositoryhead: git clone https://github.com/Lysxia/boltzmann-samplers
UploadedSun Mar 5 20:22:44 UTC 2017 by lyxia

Modules

[Index]

Flags

NameDescriptionDefaultType
test

Enable testing. Disabled by default because the current test suite is slow and can fail with non-zero probability.

DisabledManual

Use -f <flag> to enable a flag, or -f -<flag> to disable that flag. More info

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Readme for boltzmann-samplers-0.1.0.0

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Boltzmann samplers Hackage Build Status

Boltzmann.Data

Define sized random generators for Data.Data generic types.

    {-# LANGUAGE DeriveDataTypeable #-}

    import Data.Data
    import Test.QuickCheck
    import Boltzmann.Data

    data Term = Lambda Int Term | App Term Term | Var Int
      deriving (Show, Data)

    instance Arbitrary Term where
      arbitrary = sized $ generatorPWith [positiveInts]

    positiveInts :: Alias Gen
    positiveInts =
      alias $ \() -> fmap getPositive arbitrary :: Gen Int

    main = sample (arbitrary :: Gen Term)

Boltzmann.Species

An experimental interface to obtain Boltzmann samplers from an applicative specification of a combinatorial system.

No documentation (yet).

References