arrayfire-haskell/src/ArrayFire.hs at master · arrayfire/arrayfire-haskell

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--------------------------------------------------------------------------------

-- |

-- Module : ArrayFire

-- License : BSD3

-- Maintainer : David Johnson <code@dmj.io>

-- Stability : Experimental

-- Portability : GHC

-- <<https://user-images.githubusercontent.com/875324/59819703-0fbaf980-92f7-11e9-8f53-adebea590bfb.png>>

--------------------------------------------------------------------------------

module ArrayFire

( -- * Tutorial

-- $tutorial

-- ** Modules

-- $modules

-- ** Exceptions

-- $exceptions

-- ** Construction

-- $construction

-- ** Laws

-- $laws

-- ** Conversion

-- $conversion

-- ** Serialization

-- $serialization

-- ** Device

-- $device

module ArrayFire.Algorithm

, module ArrayFire.Arith

, module ArrayFire.Array

, module ArrayFire.Backend

, module ArrayFire.BLAS

, module ArrayFire.Data

, module ArrayFire.Device

, module ArrayFire.Features

, module ArrayFire.Graphics

, module ArrayFire.Image

, module ArrayFire.Index

, module ArrayFire.LAPACK

, module ArrayFire.Random

, module ArrayFire.Signal

, module ArrayFire.Sparse

, module ArrayFire.Statistics

, module ArrayFire.Types

, module ArrayFire.Util

, module ArrayFire.Vision

, module Foreign.C.Types

, module Data.Int

, module Data.Word

, module Data.Complex

, module Foreign.Storable

) where

import ArrayFire.Algorithm

import ArrayFire.Arith

import ArrayFire.Array

import ArrayFire.Backend

import ArrayFire.BLAS

import ArrayFire.Data

import ArrayFire.Device

import ArrayFire.Features

import ArrayFire.Graphics

import ArrayFire.Image

import ArrayFire.Index

import ArrayFire.LAPACK

import ArrayFire.Random

import ArrayFire.Signal

import ArrayFire.Sparse

import ArrayFire.Statistics

import ArrayFire.Types

import ArrayFire.Util

import ArrayFire.Vision

import ArrayFire.Orphans ()

import Foreign.Storable

import Foreign.C.Types

import Data.Int

import Data.Complex

import Data.Word

-- $tutorial

-- [ArrayFire](http://arrayfire.org/docs/gettingstarted.htm) is a high performance parallel computing library that features modules for statistical and numerical methods.

-- Example usage is depicted below.

-- @

-- module Main where

-- import qualified ArrayFire as A

-- main :: IO ()

-- main = print $ A.matrix @Double (3,2) [[1,2,3],[4,5,6]]

-- @

-- Each 'Array' is constructed and displayed in column-major order.

-- @

-- ArrayFire Array

-- [3 2 1 1]

-- 1.0000 4.0000

-- 2.0000 5.0000

-- 3.0000 6.0000

-- @

-- $modules

-- All child modules are re-exported top-level in the "ArrayFire" module.

-- We recommend importing "ArrayFire" qualified so as to avoid naming collisions.

-- >>> import qualified ArrayFire as A

-- $exceptions

-- @

-- {\-\# LANGUAGE TypeApplications \#\-}

-- module Main where

-- import qualified ArrayFire as A

-- import Control.Exception ( catch )

-- main :: IO ()

-- main = A.printArray action \`catch\` (\\(e :: A.AFException) -> print e)

-- where

-- action =

-- A.matrix \@Double (3,3) [[1..],[1..],[1..]]

-- \`A.mul\` A.matrix \@Double (2,2) [[1..],[1..]]

-- @

-- The above operation is invalid since the matrix multiply has improper dimensions. The caught exception produces the following error:

-- > AFException {afExceptionType = SizeError, afExceptionCode = 203, afExceptionMsg = "Invalid input size"}

-- $construction

-- An 'Array' can be constructed using the following smart constructors:

-- /Note/: All smart constructors (and ArrayFire internally) assume column-major order.

-- @

-- >>> scalar \@Double 2.0

-- ArrayFire Array

-- [1 1 1 1]

-- 2.0000

-- @

-- >>> vector \@Double 10 [1..]

-- ArrayFire Array

-- [10 1 1 1]

-- 1.0000

-- 2.0000

-- 3.0000

-- 4.0000

-- 5.0000

-- 6.0000

-- 7.0000

-- 8.0000

-- 9.0000

-- 10.0000

-- @

-- >>> matrix \@Double (2,2) [[1,2],[3,4]]

-- ArrayFire Array

-- [2 2 1 1]

-- 1.0000 3.0000

-- 2.0000 4.0000

-- @

-- >>> cube \@Double (2,2,2) [[[2,2],[2,2]],[[2,2],[2,2]]]

-- ArrayFire Array

-- [2 2 2 1]

-- 2.0000 2.0000

-- @

-- >>> tensor \@Double (2,2,2,2) [[[[2,2],[2,2]],[[2,2],[2,2]]], [[[2,2],[2,2]],[[2,2],[2,2]]]]

-- ArrayFire Array

-- [2 2 2 2]

-- 2.0000 2.0000

-- @

-- Array construction can use Haskell's lazy lists, since 'take' is called on each dimension before sending to the C API.

-- >>> mkArray @Double [5,3] [1..]

-- ArrayFire Array

-- [5 3 1 1]

-- 1.0000 6.0000 11.0000

-- 2.0000 7.0000 12.0000

-- 3.0000 8.0000 13.0000

-- 4.0000 9.0000 14.0000

-- 5.0000 10.0000 15.0000

-- Specifying up to 4 dimensions is allowed (anything higher is ignored).

-- $laws

-- Every 'Array' has an instance of 'Eq', 'Num', 'Fractional', 'Floating' and 'Show'

-- 'Num'

-- >>> 2.0 :: Array Double

-- ArrayFire Array

-- [1 1 1 1]

-- 2.0000

-- >>> scalar @Int 1 + scalar @Int 1

-- ArrayFire Array

-- [1 1 1 1]

-- 2

-- >>> scalar @Int 1 - scalar @Int 1

-- ArrayFire Array

-- [1 1 1 1]

-- 0

-- >>> scalar @Double 10 / scalar @Double 10

-- ArrayFire Array

-- [1 1 1 1]

-- 1.0000

-- >>> abs $ scalar @Double (-10)

-- ArrayFire Array

-- [1 1 1 1]

-- 10.0000

-- >>> negate (scalar @Double 10)

-- ArrayFire Array

-- [1 1 1 1]

-- -10.0000

-- >>> fromInteger 1.0 :: Array Double

-- ArrayFire Array

-- [1 1 1 1]

-- 1.0000

-- 'Eq'

-- >>> scalar @Double 1 [10] == scalar @Double 1 [10]

-- True

-- >>> scalar @Double 1 [10] /= scalar @Double 1 [10]

-- False

-- 'Floating'

-- >>> pi :: Array Double

-- ArrayFire Array

-- [1 1 1 1]

-- 3.1416

-- >>> A.sqrt pi :: Array Double

-- ArrayFire Array

-- [1 1 1 1]

-- 1.7725

-- 'Fractional'

-- >>> (pi :: Array Double) / pi

-- ArrayFire Array

-- [1 1 1 1]

-- 1.000

-- >>> recip 0.5 :: Array Double

-- ArrayFire Array

-- [1 1 1 1]

-- 2.000

-- 'Show'

-- >>> 0.0 :: Array Double

-- ArrayFire Array

-- [1 1 1 1]

-- 0.000

-- $conversion

-- Any 'Array' can be exported into Haskell using `toVector'. This will create a Storable vector suitable for use in other C programs.

-- >>> vector :: Vector Double <- toVector <$> randu @Double [10,10]

-- $serialization

-- Each 'Array' can be serialized to disk and deserialized from disk efficiently.

-- @

-- import qualified ArrayFire as A

-- import Control.Monad

-- main :: IO ()

-- main = do

-- let arr = A.'constant' [1,1,1,1] 10

-- idx <- A.'saveArray' "key" arr "file.array" False

-- foundIndex <- A.'readArrayKeyCheck' "file.array" "key"

-- when (idx == foundIndex) $ do

-- array <- A.'readArrayKey' "file.array" "key"

-- 'print' array

-- -- ArrayFire Array

-- -- [ 1 1 1 1 ]

-- -- 10

-- @

-- $device

-- The ArrayFire API is able to see which devices are present, and will by default use the GPU if available.

-- >>> afInfo

-- ArrayFire v3.6.4 (OpenCL, 64-bit Mac OSX, build 1b8030c5)

-- [0] APPLE: AMD Radeon Pro 555X Compute Engine, 4096 MB <-- brackets [] signify device being used.

-- -1- APPLE: Intel(R) UHD Graphics 630, 1536 MB

-- $visualization

-- The ArrayFire API is able to display visualizations using the Forge library

-- >>> window <- createWindow 800 600 "Histogram"

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