name:         ad
version:      4.2
x-revision: 1
license:      BSD3
license-File: LICENSE
copyright:    (c) Edward Kmett 2010-2014,
              (c) Barak Pearlmutter and Jeffrey Mark Siskind 2008-2009
author:       Edward Kmett
maintainer:   ekmett@gmail.com
stability:    Experimental
category:     Math
homepage:     http://github.com/ekmett/ad
bug-reports:  http://github.com/ekmett/ad/issues
build-type:   Custom
cabal-version: >= 1.10
extra-source-files:
  .ghci
  .gitignore
  .travis.yml
  .vim.custom
  TODO
  CHANGELOG.markdown
  README.markdown
  travis/cabal-apt-install
  travis/config
  include/instances.h
synopsis:     Automatic Differentiation
description:
    Forward-, reverse- and mixed- mode automatic differentiation combinators with a common API.
    .
    Type-level \"branding\" is used to both prevent the end user from confusing infinitesimals
    and to limit unsafe access to the implementation details of each Mode.
    .
    Each mode has a separate module full of combinators.
    .
    * @Numeric.AD.Mode.Forward@ provides basic forward-mode AD. It is good for computing simple derivatives.
    .
    * @Numeric.AD.Mode.Reverse@ uses benign side-effects to compute reverse-mode AD. It is good for computing gradients in one pass. It generates a Wengert list (linear tape) using @Data.Reflection@.
    .
    * @Numeric.AD.Mode.Kahn@ uses benign side-effects to compute reverse-mode AD. It is good for computing gradients in one pass. It generates a tree-like tape that needs to be topologically sorted in the end.
    .
    * @Numeric.AD.Mode.Sparse@ computes a sparse forward-mode AD tower. It is good for higher derivatives or large numbers of outputs.
    .
    * @Numeric.AD.Mode.Tower@ computes a dense forward-mode AD tower useful for higher derivatives of single input functions.
    .
    * @Numeric.AD@ computes using whichever mode or combination thereof is suitable to each individual combinator.
    .
    While not every mode can provide all operations, the following basic operations are supported, modified as
    appropriate by the suffixes below:
    .
    * 'grad' computes the gradient (partial derivatives) of a function at a point.
    .
    * 'jacobian' computes the Jacobian matrix of a function at a point.
    .
    * 'diff' computes the derivative of a function at a point.
    .
    * 'du' computes a directional derivative of a function at a point.
    .
    * 'hessian' computes the Hessian matrix (matrix of second partial derivatives) of a function at a point.
    .
    The following suffixes alter the meanings of the functions above as follows:
    .
    * @\'@ -- also return the answer
    .
    * @With@ lets the user supply a function to blend the input with the output
    .
    * @F@ is a version of the base function lifted to return a 'Traversable' (or 'Functor') result
    .
    * @s@ means the function returns all higher derivatives in a list or f-branching 'Stream'
    .
    * @T@ means the result is transposed with respect to the traditional formulation.
    .
    * @0@ means that the resulting derivative list is padded with 0s at the end.

flag lib-Werror
  default: False
  manual: True

source-repository head
  type: git
  location: git://github.com/ekmett/ad.git

library
  -- package version broken due to missing file in source tarball
  build-depends: base<0

  default-extensions: CPP
  hs-source-dirs: src
  include-dirs: include
  default-language: Haskell2010

  other-extensions:
    BangPatterns
    DeriveDataTypeable
    FlexibleContexts
    FlexibleInstances
    FunctionalDependencies
    GeneralizedNewtypeDeriving
    MultiParamTypeClasses
    PatternGuards
    Rank2Types
    ScopedTypeVariables
    TemplateHaskell
    TypeFamilies
    TypeOperators
    UndecidableInstances

  build-depends:
    array            >= 0.2   && < 0.6,
    base             >= 4.5   && < 5,
    comonad          >= 4     && < 5,
    containers       >= 0.2   && < 0.6,
    data-reify       >= 0.6   && < 0.7,
    erf              >= 2.0   && < 2.1,
    free             >= 4.6.1 && < 5,
    mtl              >= 2     && < 2.2,
    nats             >= 0.1.2 && < 1,
    reflection       >= 1.4   && < 2,
    tagged           >= 0.7   && < 1,
    template-haskell,
    transformers     >= 0.3   && < 0.4

  exposed-modules:
    Numeric.AD
    Numeric.AD.Halley
    Numeric.AD.Internal.Dense
    Numeric.AD.Internal.Forward
    Numeric.AD.Internal.Forward.Double
    Numeric.AD.Internal.Identity
    Numeric.AD.Internal.Kahn
    Numeric.AD.Internal.On
    Numeric.AD.Internal.Or
    Numeric.AD.Internal.Reverse
    Numeric.AD.Internal.Sparse
    Numeric.AD.Internal.Tower
    Numeric.AD.Internal.Type
    Numeric.AD.Jacobian
    Numeric.AD.Jet
    Numeric.AD.Mode
    Numeric.AD.Mode.Forward
    Numeric.AD.Mode.Forward.Double
    Numeric.AD.Mode.Kahn
    Numeric.AD.Mode.Reverse
    Numeric.AD.Mode.Sparse
    Numeric.AD.Mode.Tower
    Numeric.AD.Newton
    Numeric.AD.Rank1.Forward
    Numeric.AD.Rank1.Forward.Double
    Numeric.AD.Rank1.Sparse
    Numeric.AD.Rank1.Tower
    Numeric.AD.Rank1.Kahn
    Numeric.AD.Rank1.Newton

  other-modules:
    Numeric.AD.Internal.Combinators

  if flag(lib-Werror)
    ghc-options: -Werror
  else
    ghc-options: -Wall

  ghc-options: -fspec-constr -fdicts-cheap -O2

-- Verify the results of the examples
test-suite doctests
  default-language: Haskell2010
  type:    exitcode-stdio-1.0
  main-is: doctests.hs
  build-depends:
    base,
    directory,
    doctest >= 0.9.0.1 && <= 0.10,
    filepath,
    mtl
  ghc-options: -Wall -threaded
  if impl(ghc<7.6)
    ghc-options: -Werror
  hs-source-dirs: tests

benchmark blackscholes
  default-language: Haskell2010
  type: exitcode-stdio-1.0
  main-is: BlackScholes.hs
  hs-source-dirs: bench
  build-depends: base, ad, erf, criterion
  ghc-options: -fspec-constr -fdicts-cheap -O2