name: boltzmann-samplers version: 0.1.0.0 synopsis: Uniform random generators description: Random generators with a uniform distribution conditioned to a given size. See also @@, which is currently a faster method with similar results. homepage: https://github.com/Lysxia/boltzmann-samplers#readme license: MIT license-file: LICENSE author: Li-yao Xia maintainer: lysxia@gmail.com category: Data, Generic, Random build-type: Simple extra-source-files: README.md cabal-version: >=1.10 flag test Description: Enable testing. Disabled by default because the current test suite is slow and can fail with non-zero probability. Manual: True Default: False library hs-source-dirs: src exposed-modules: Boltzmann.Data Boltzmann.Data.Data Boltzmann.Data.Common Boltzmann.Data.Oracle Boltzmann.Data.Types Boltzmann.Solver Boltzmann.Species build-depends: ad, base >= 4.9 && < 5, containers, hashable, hmatrix, ieee754, unordered-containers, MonadRandom, mtl, QuickCheck, transformers, vector default-language: Haskell2010 source-repository head type: git location: https://github.com/Lysxia/boltzmann-samplers test-suite test-tree type: exitcode-stdio-1.0 hs-source-dirs: test main-is: tree.hs default-language: Haskell2010 other-modules: Test.Stats if flag(test) build-depends: base, QuickCheck, optparse-generic, boltzmann-samplers else buildable: False benchmark bench-binarytree type: exitcode-stdio-1.0 hs-source-dirs: bench main-is: binaryTree.hs default-language: Haskell2010 ghc-options: -O2 if flag(test) build-depends: base, criterion, deepseq, QuickCheck, transformers, testing-feat, boltzmann-samplers else buildable: False