boltzmann-samplers

Uniform random generators https://github.com/Lysxia/boltzmann-samplers#readme

This package is not currently in any snapshots. If you're interested in using it, we recommend adding it to Stackage Nightly. Doing so will make builds more reliable, and allow stackage.org to host generated Haddocks.

MIT licensed by Li-yao Xia
Maintained by lysxia@gmail.com

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)
  • Objects of the same size (number of constructors) occur with the same probability (see Duchon et al., references below).
  • Implements rejection sampling and pointing.
  • Works with QuickCheck and MonadRandom, but also similar user-defined monads for randomness (just implement MonadRandomLike).
  • Can be tweaked somewhat with user defined generators.

Boltzmann.Species

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

No documentation (yet).

References

Changes

0.1.1.0

  • Added Semigroup Nat instance, for compatibility with GHC 8.4