Uniform random generators

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MIT licensed by Li-yao Xia
Maintained by

Boltzmann samplers Hackage Build Status


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.


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

No documentation (yet).



  • Added Semigroup Nat instance, for compatibility with GHC 8.4