name: sparse-tensor version: 0.2.1 synopsis: typesafe tensor algebra library description: . This package is intended to be used as a general purpose tensor algebra library. It defines the usual tensor algebra functions such as addition, scalar multiplication, tensor product, and contractions, but also general symmetrizations and further utility functions. . The implemented tensor data type is capable of being used with an arbitrary number of general abstract indices and can incorporate values of any type that allow for a meaningful addition, scaling, and multiplication. The package is thus very flexible and can easily be customised at wish. homepage: https://github.com/TobiReinhart/sparse-tensor#readme license: MIT license-file: LICENSE author: Tobias Reinhart and Nils Alex maintainer: tobi.reinhart@fau.de, nils.alex@fau.de copyright: 2019 Tobias Reinhart and Nils Alex category: Data, Math, Algebra build-type: Custom cabal-version: 1.24 extra-source-files: README.md CHANGELOG.md custom-setup setup-depends: base >= 4.9 && < 5, Cabal >= 1.24 && < 3.0 source-repository head type: git location: git://github.com/TobiReinhart/sparse-tensor.git library hs-source-dirs: src default-language: Haskell2010 build-depends: base >= 4.9 && < 5, containers >= 0.5 && < 0.7, tf-random >= 0.5 && < 0.6, ghc-typelits-natnormalise >= 0.5 && < 0.7, ghc-typelits-knownnat >= 0.2 && < 0.7, parallel >= 3.2 && < 3.3, deepseq >= 1.1 && < 1.5, cereal >= 0.4 && < 0.6, bytestring >= 0.10 && < 0.11, zlib >= 0.6 && < 0.7, ad >= 4.2 && < 4.4, hmatrix >= 0.16.1 && < 0.21 exposed-modules: Math.Tensor Math.Tensor.LorentzGenerator Math.Tensor.Examples.Gravity Math.Tensor.Examples.Gravity.Schwarzschild Math.Tensor.Examples.Gravity.SchwarzschildSymbolic Math.Tensor.Examples.Gravity.DiffeoSymEqns Math.Tensor.Internal.LinearAlgebra test-suite test-sparse-tensor type: exitcode-stdio-1.0 hs-source-dirs: test default-language: Haskell2010 main-is: TestMain.hs other-modules: LinearAlgebra, IndList, Ansatz, Serialization build-depends: base >= 4.9 && < 5, hmatrix >= 0.16.1 && < 0.21, QuickCheck >= 2.8.2 && < 2.14, tasty >= 0.11 && < 1.3, tasty-hunit >= 0.9 && < 0.11, tasty-quickcheck >= 0.8 && < 0.11, sparse-tensor