-- Hoogle documentation, generated by Haddock
-- See Hoogle, http://www.haskell.org/hoogle/
-- | Haskell bindings to the ArrayFire general-purpose GPU library
--
-- High-level Haskell bindings to the ArrayFire General-purpose GPU
-- library
--
@package arrayfire
@version 0.5.1.0
-- | Various Types related to the ArrayFire API
module ArrayFire.Types
-- | Exception type for ArrayFire API
data AFException
AFException :: AFExceptionType -> Int -> String -> AFException
-- | The Exception type to throw
[afExceptionType] :: AFException -> AFExceptionType
-- | Code representing the exception
[afExceptionCode] :: AFException -> Int
-- | Exception message
[afExceptionMsg] :: AFException -> String
-- | ArrayFire exception type
data AFExceptionType
NoMemoryError :: AFExceptionType
DriverError :: AFExceptionType
RuntimeError :: AFExceptionType
InvalidArrayError :: AFExceptionType
ArgError :: AFExceptionType
SizeError :: AFExceptionType
TypeError :: AFExceptionType
DiffTypeError :: AFExceptionType
BatchError :: AFExceptionType
DeviceError :: AFExceptionType
NotSupportedError :: AFExceptionType
NotConfiguredError :: AFExceptionType
NonFreeError :: AFExceptionType
NoDblError :: AFExceptionType
NoGfxError :: AFExceptionType
LoadLibError :: AFExceptionType
LoadSymError :: AFExceptionType
BackendMismatchError :: AFExceptionType
InternalError :: AFExceptionType
UnknownError :: AFExceptionType
UnhandledError :: AFExceptionType
-- | ArrayFire Array
data Array a
-- | ArrayFire Window
data Window
-- | ArrayFire RandomEngine
data RandomEngine
-- | ArrayFire Features
data Features
-- | Mapping of Haskell types to ArrayFire types
class Storable a => AFType a
afType :: AFType a => Proxy a -> AFDtype
-- | TopK type
data TopK
TopKDefault :: TopK
TopKMin :: TopK
TopKMax :: TopK
-- | ArrayFire backends
data Backend
Default :: Backend
CPU :: Backend
CUDA :: Backend
OpenCL :: Backend
-- | Match type
data MatchType
MatchTypeSAD :: MatchType
MatchTypeZSAD :: MatchType
MatchTypeLSAD :: MatchType
MatchTypeSSD :: MatchType
MatchTypeZSSD :: MatchType
MatchTypeLSSD :: MatchType
MatchTypeNCC :: MatchType
MatchTypeZNCC :: MatchType
MatchTypeSHD :: MatchType
-- | Binary operation support
data BinaryOp
Add :: BinaryOp
Mul :: BinaryOp
Min :: BinaryOp
Max :: BinaryOp
-- | Matrix properties
data MatProp
None :: MatProp
Trans :: MatProp
CTrans :: MatProp
Conj :: MatProp
Upper :: MatProp
Lower :: MatProp
DiagUnit :: MatProp
Sym :: MatProp
PosDef :: MatProp
Orthog :: MatProp
TriDiag :: MatProp
BlockDiag :: MatProp
-- | Homography Type
data HomographyType
RANSAC :: HomographyType
LMEDS :: HomographyType
-- | Type for different RandomEngines
data RandomEngineType
Philox :: RandomEngineType
ThreeFry :: RandomEngineType
Mersenne :: RandomEngineType
-- | Cell type, used in Graphics module
data Cell
Cell :: Int -> Int -> String -> ColorMap -> Cell
[cellRow] :: Cell -> Int
[cellCol] :: Cell -> Int
[cellTitle] :: Cell -> String
[cellColorMap] :: Cell -> ColorMap
-- | Marker type
data MarkerType
MarkerTypeNone :: MarkerType
MarkerTypePoint :: MarkerType
MarkerTypeCircle :: MarkerType
MarkerTypeSquare :: MarkerType
MarkerTypeTriangle :: MarkerType
MarkerTypeCross :: MarkerType
MarkerTypePlus :: MarkerType
MarkerTypeStar :: MarkerType
-- | Interpolation type
data InterpType
Nearest :: InterpType
Linear :: InterpType
Bilinear :: InterpType
Cubic :: InterpType
LowerInterp :: InterpType
LinearCosine :: InterpType
BilinearCosine :: InterpType
Bicubic :: InterpType
CubicSpline :: InterpType
BicubicSpline :: InterpType
-- | Connectivity Type
data Connectivity
Conn4 :: Connectivity
Conn8 :: Connectivity
-- | Color Space type
data CSpace
Gray :: CSpace
RGB :: CSpace
HSV :: CSpace
YCBCR :: CSpace
-- | YccStd type
data YccStd
Ycc601 :: YccStd
Ycc709 :: YccStd
Ycc2020 :: YccStd
-- | Moment types
data MomentType
M00 :: MomentType
M01 :: MomentType
M10 :: MomentType
M11 :: MomentType
FirstOrder :: MomentType
-- | Canny Theshold type
data CannyThreshold
Manual :: CannyThreshold
AutoOtsu :: CannyThreshold
-- | Flux function type
data FluxFunction
FluxDefault :: FluxFunction
FluxQuadratic :: FluxFunction
FluxExponential :: FluxFunction
-- | Diffusion type
data DiffusionEq
DiffusionDefault :: DiffusionEq
DiffusionGrad :: DiffusionEq
DiffusionMCDE :: DiffusionEq
-- | Iterative deconvolution algo type
data IterativeDeconvAlgo
DeconvDefault :: IterativeDeconvAlgo
DeconvLandweber :: IterativeDeconvAlgo
DeconvRichardsonLucy :: IterativeDeconvAlgo
-- | Inverse deconvolution algo type
data InverseDeconvAlgo
InverseDeconvDefault :: InverseDeconvAlgo
InverseDeconvTikhonov :: InverseDeconvAlgo
-- | Sequence Type
data Seq
Seq :: !Double -> !Double -> !Double -> Seq
[seqBegin] :: Seq -> !Double
[seqEnd] :: Seq -> !Double
[seqStep] :: Seq -> !Double
-- | Index Type
data Index a
Index :: Either (Array a) Seq -> !Bool -> !Bool -> Index a
[idx] :: Index a -> Either (Array a) Seq
[isSeq] :: Index a -> !Bool
[isBatch] :: Index a -> !Bool
-- | Norm Type
data NormType
-- | treats the input as a vector and returns the sum of absolute values
NormVectorOne :: NormType
-- | treats the input as a vector and returns the max of absolute values
NormVectorInf :: NormType
-- | treats the input as a vector and returns euclidean norm
NormVector2 :: NormType
-- | treats the input as a vector and returns the p-norm
NormVectorP :: NormType
-- | return the max of column sums
NormMatrix1 :: NormType
-- | return the max of row sums
NormMatrixInf :: NormType
-- | returns the max singular value). Currently NOT SUPPORTED
NormMatrix2 :: NormType
-- | returns Lpq-norm
NormMatrixLPQ :: NormType
-- | The default. Same as AF_NORM_VECTOR_2
NormEuclid :: NormType
-- | Convolution Mode
data ConvMode
-- | Output of the convolution is the same size as input
ConvDefault :: ConvMode
-- | Output of the convolution is signal_len + filter_len - 1
ConvExpand :: ConvMode
-- | Convolution Domain
data ConvDomain
-- | ArrayFire automatically picks the right convolution algorithm
ConvDomainAuto :: ConvDomain
-- | Perform convolution in spatial domain
ConvDomainSpatial :: ConvDomain
-- | Perform convolution in frequency domain
ConvDomainFreq :: ConvDomain
-- | Border Type
data BorderType
PadZero :: BorderType
PadSym :: BorderType
-- | Storage type used for Sparse arrays
data Storage
Dense :: Storage
CSR :: Storage
CSC :: Storage
COO :: Storage
-- | Array Fire types
data AFDType
F32 :: AFDType
C32 :: AFDType
F64 :: AFDType
C64 :: AFDType
B8 :: AFDType
S32 :: AFDType
U32 :: AFDType
U8 :: AFDType
S64 :: AFDType
U64 :: AFDType
S16 :: AFDType
U16 :: AFDType
newtype AFDtype
AFDtype :: CInt -> AFDtype
-- | Value corresponding to ArrayFire type
[afDType] :: AFDtype -> CInt
-- | ColorMap type
data ColorMap
ColorMapDefault :: ColorMap
ColorMapSpectrum :: ColorMap
ColorMapColors :: ColorMap
ColorMapRed :: ColorMap
ColorMapMood :: ColorMap
ColorMapHeat :: ColorMap
ColorMapBlue :: ColorMap
ColorMapInferno :: ColorMap
ColorMapMagma :: ColorMap
ColorMapPlasma :: ColorMap
ColorMapViridis :: ColorMap
-- | ArrayFire Docs Functions to create and handle sparse arrays and
-- matrix operations.
--
--
-- - Note* Sparse functionality support was added to ArrayFire in
-- v3.4.0.
--
--
--
-- >>> createSparseArray 10 10 (matrix @Double (10,10) [[1,2],[3,4]]) (vector @Int32 10 [1..]) (vector @Int32 10 [1..]) CSR
--
module ArrayFire.Sparse
-- | This function converts af::array of values, row indices and column
-- indices into a sparse array.
--
-- ArrayFire Docs
--
--
-- - Note* This function only create references of these arrays into
-- the sparse data structure and does not do deep copies.
--
--
--
-- >>> createSparseArray 10 10 (matrix @Double (10,10) [[1,2],[3,4]]) (vector @Int32 10 [1..]) (vector @Int32 10 [1..]) CSR
--
createSparseArray :: (AFType a, Fractional a) => Int -> Int -> Array a -> Array Int32 -> Array Int32 -> Storage -> Array a
-- | This function converts a dense af_array into a sparse array.
--
-- ArrayFire Docs
--
--
-- - Note* This function only create references of these arrays into
-- the sparse data structure and does not do deep copies.
--
--
--
-- >>> createSparseArrayFromDense (matrix @Double (2,2) [[1,2],[3,4]]) CSR
-- ArrayFire Array
-- Storage Format : AF_STORAGE_CSR
-- [2 2 1 1]
-- ArrayFire Array: Values
-- [4 1 1 1]
-- 1.0000 3.0000 2.0000 4.0000
-- ArrayFire Array: RowIdx
-- [3 1 1 1]
-- 0 2 4
-- ArrayFire Array: ColIdx
-- [4 1 1 1]
-- 0 1 0 1
--
createSparseArrayFromDense :: (AFType a, Fractional a) => Array a -> Storage -> Array a
-- | Convert an existing sparse array into a different storage format.
--
-- ArrayFire Docs
--
-- Converting storage formats is allowed between CSR, COO
-- and DENSE.
--
-- When converting to DENSE, a dense array is returned.
--
--
-- - Note* CSC is currently not supported.
--
--
--
-- >>> array = createSparseArrayFromDense (matrix @Double (2,2) [[1,2],[3,4]]) CSR
--
-- >>> array
-- ArrayFire Array
-- Storage Format : AF_STORAGE_CSR
-- [2 2 1 1]
-- ArrayFire Array: Values
-- [4 1 1 1]
-- 1.0000
-- 3.0000
-- 2.0000
-- 4.0000
--
sparseConvertTo :: (AFType a, Fractional a) => Array a -> Storage -> Array a
-- | Returns a dense array from a sparse input
--
-- ArrayFire Docs
--
-- Converts the sparse matrix into a dense matrix and returns it
--
--
-- >>> array = createSparseArrayFromDense (matrix @Double (2,2) [[1,2],[3,4]]) CSR
--
-- >>> array
-- ArrayFire Array
-- Storage Format : AF_STORAGE_CSR
-- [2 2 1 1]
-- ArrayFire Array: Values
-- [4 1 1 1]
-- 1.0000
-- 3.0000
-- 2.0000
-- 4.0000
--
--
-- ArrayFire Array: RowIdx [3 1 1 1] 0 2 4
--
-- ArrayFire Array: ColIdx [4 1 1 1] 0 1 0 1
sparseToDense :: (AFType a, Fractional a) => Array a -> Array a
-- | Returns reference to components of the input sparse array.
--
-- ArrayFire Docs
--
-- Returns reference to values, row indices, column indices and storage
-- format of an input sparse array
--
--
-- >>> (values, cols, rows, storage) = sparseGetInfo $ createSparseArrayFromDense (matrix @Double (2,2) [[1,2],[3,4]]) CSR
--
-- >>> values
-- ArrayFire Array
-- [4 1 1 1]
-- 1.0000
-- 3.0000
-- 2.0000
-- 4.0000
--
--
--
-- >>> cols
-- ArrayFire Array
-- [3 1 1 1]
-- 0
-- 2
-- 4
--
--
--
-- >>> rows
-- ArrayFire Array
-- [4 1 1 1]
-- 0
-- 1
-- 0
-- 1
--
--
--
-- >>> storage
-- CSR
--
sparseGetInfo :: (AFType a, Fractional a) => Array a -> (Array a, Array a, Array a, Storage)
-- | Returns reference to the values component of the sparse array.
--
-- ArrayFire Docs
--
-- Returns reference to the values component of the sparse array. Values
-- is the Array containing the non-zero elements of the dense
-- matrix.
--
--
-- >>> sparseGetValues (createSparseArrayFromDense (matrix @Double (2,2) [[1,2],[3,4]]) CSR)
-- ArrayFire Array
-- [4 1 1 1]
-- 1.0000
-- 3.0000
-- 2.0000
-- 4.0000
--
sparseGetValues :: (AFType a, Fractional a) => Array a -> Array a
-- | Returns reference to the row indices component of the sparse array.
-- More...
--
-- ArrayFire Docs
--
-- Returns reference to the row indices component of the sparse array.
-- Row indices is the Array containing the column indices of the
-- sparse array.
--
--
-- >>> sparseGetRowIdx (createSparseArrayFromDense (matrix @Double (2,2) [[1,2],[3,4]]) CSR)
-- ArrayFire Array
-- [3 1 1 1]
-- 0
-- 2
-- 4
--
sparseGetRowIdx :: (AFType a, Fractional a) => Array a -> Array a
-- | Returns reference to the column indices component of the sparse array.
-- More...
--
-- ArrayFire Docs
--
-- Returns reference to the column indices component of the sparse array.
-- Column indices is the Array containing the column indices of
-- the sparse array.
--
--
-- >>> sparseGetColIdx (createSparseArrayFromDense (matrix @Double (2,2) [[1,2],[3,4]]) CSR)
-- ArrayFire Array
-- [4 1 1 1]
-- 0
-- 1
-- 0
-- 1
--
sparseGetColIdx :: (AFType a, Fractional a) => Array a -> Array a
-- | Returns the storage type of a sparse array.
--
-- ArrayFire Docs
--
-- Returns the number of non zero elements in the sparse array. This is
-- always equal to the size of the values array.
--
--
-- >>> sparseGetStorage $ createSparseArrayFromDense (matrix @Double (2,2) [[1,2],[3,4]]) CSR
-- CSR
--
sparseGetStorage :: (AFType a, Fractional a) => Array a -> Storage
-- | Returns the number of non zero elements in the sparse array. More...
--
-- ArrayFire Docs
--
-- Returns the number of non zero elements in the sparse array. This is
-- always equal to the size of the values array.
--
--
-- >>> sparseGetNNZ $ createSparseArrayFromDense (matrix @Double (2,2) [[1,2],[3,4]]) CSR
-- 4
--
sparseGetNNZ :: (AFType a, Fractional a) => Array a -> Int
-- | ArrayFire Docs
--
-- Functions performing signal processing on Array
--
--
-- >>> input = vector 3 [10,20,30]
--
-- >>> positions = vector 5 [0.0, 0.5, 1.0, 1.5, 2.0]
--
-- >>> approx1 @Double input positions Cubic 0.0
-- ArrayFire Array
-- [5 1 1 1]
-- 10.0000
-- 13.7500
-- 20.0000
-- 26.2500
-- 30.0000
--
module ArrayFire.Signal
-- | approx1 interpolates data along the first dimensions
--
-- ArrayFire Docs
--
-- Interpolation is performed assuming input data is equally spaced with
-- indices in the range [0, n). The positions are sampled with respect to
-- data at these locations.
--
--
-- >>> input = vector 3 [10,20,30]
--
-- >>> positions = vector 5 [0.0, 0.5, 1.0, 1.5, 2.0]
--
-- >>> approx1 @Double input positions Cubic 0.0
-- ArrayFire Array
-- [5 1 1 1]
-- 10.0000
-- 13.7500
-- 20.0000
-- 26.2500
-- 30.0000
--
approx1 :: AFType a => Array a -> Array a -> InterpType -> Float -> Array a
-- | approx2 performs interpolation on data along the first and second
-- dimensions.
--
-- ArrayFire Docs
--
-- Interpolation is performed assuming input data is equally spaced with
-- indices in the range [0, n) along each dimension. The positions are
-- sampled with respect to data at these locations.
--
--
-- >>> input = matrix @Double (3,3) [ [ 1.0,1.0,1.0 ], [ 2.0, 2.0, 2.0 ], [ 3.0,3.0,3.0 ] ]
--
-- >>> positions1 = matrix @Double (2,2) [ [ 0.5,1.5 ],[ 0.5,1.5 ] ]
--
-- >>> positions2 = matrix @Double (2,2) [ [ 0.5,0.5 ],[ 1.5,1.5 ] ]
--
-- >>> approx2 @Double input positions1 positions2 Cubic 0.0
-- ArrayFire Array
-- [2 2 1 1]
-- 1.3750 2.6250
-- 1.3750 2.6250
--
approx2 :: AFType a => Array a -> Array a -> Array a -> InterpType -> Float -> Array a
-- | Fast Fourier Transform
--
-- ArrayFire Docs
--
-- The Fast Fourier Transform (FFT) is an efficient algorithm to compute
-- the discrete Fourier transform (DFT) of a signal or array. This is
-- most commonly used to convert data in the time (or space) domain to
-- the frequency domain, Then, the inverse FFT (iFFT) is used to return
-- the data to the original domain.
--
--
-- >>> fft (vector @Double 10 [1..]) 2.0 10
-- ArrayFire Array
-- [10 1 1 1]
-- (110.0000,0.0000)
-- (-10.0000,30.7768)
-- (-10.0000,13.7638)
-- (-10.0000,7.2654)
-- (-10.0000,3.2492)
-- (-10.0000,0.0000)
-- (-10.0000,-3.2492)
-- (-10.0000,-7.2654)
-- (-10.0000,-13.7638)
-- (-10.0000,-30.7768)
--
fft :: (AFType a, Fractional a) => Array a -> Double -> Int -> Array a
-- | Fast Fourier Transform (in-place)
--
-- ArrayFire Docs
--
-- C Interface for fast fourier transform on one dimensional signals.
--
--
-- - Note* The input in must be a complex array
--
fftInPlace :: (AFType a, Fractional a) => Array (Complex a) -> Double -> IO ()
-- | Fast Fourier Transform (2-dimensional)
--
-- ArrayFire Docs
--
-- C Interface for fast fourier transform on two dimensional signals.
fft2 :: AFType a => Array a -> Double -> Int -> Int -> Array a
-- | Fast Fourier Transform (2-dimensional, in-place)
--
-- ArrayFire Docs
--
-- C Interface for fast fourier transform on two dimensional signals.
--
--
-- - Note* The input in must be a complex array
--
fft2_inplace :: (Fractional a, AFType a) => Array (Complex a) -> Double -> IO ()
-- | Fast Fourier Transform (3-dimensional)
--
-- ArrayFire Docs
--
-- C Interface for fast fourier transform on three dimensional signals.
fft3 :: AFType a => Array a -> Double -> Int -> Int -> Int -> Array a
-- | Fast Fourier Transform (3-dimensional, in-place)
--
-- ArrayFire Docs
--
-- C Interface for fast fourier transform on three dimensional signals.
--
--
-- - Note* The input in must be a complex array
--
fft3_inplace :: (Fractional a, AFType a) => Array (Complex a) -> Double -> IO ()
-- | Inverse Fast Fourier Transform
--
-- ArrayFire Docs
--
-- C Interface for inverse fast fourier transform on one dimensional
-- signals.
ifft :: AFType a => Array a -> Double -> Int -> Array a
-- | Inverse Fast Fourier Transform (in-place)
--
-- ArrayFire Docs
--
-- C Interface for fast fourier transform on one dimensional signals.
ifft_inplace :: (AFType a, Fractional a) => Array (Complex a) -> Double -> IO ()
-- | Inverse Fast Fourier Transform (2-dimensional signals)
--
-- ArrayFire Docs
--
-- C Interface for inverse fast fourier transform on two dimensional
-- signals.
ifft2 :: AFType a => Array a -> Double -> Int -> Int -> Array a
-- | Inverse Fast Fourier Transform (2-dimensional, in-place)
--
-- ArrayFire Docs
--
-- C Interface for fast fourier transform on two dimensional signals.
ifft2_inplace :: (AFType a, Fractional a) => Array (Complex a) -> Double -> IO ()
-- | Inverse Fast Fourier Transform (3-dimensional)
--
-- ArrayFire Docs
--
-- C Interface for inverse fast fourier transform on three dimensional
-- signals.
ifft3 :: AFType a => Array a -> Double -> Int -> Int -> Int -> Array a
-- | Inverse Fast Fourier Transform (3-dimensional, in-place)
--
-- ArrayFire Docs
--
-- C Interface for fast fourier transform on two dimensional signals.
ifft3_inplace :: (AFType a, Fractional a) => Array (Complex a) -> Double -> IO ()
-- | Real to Complex Fast Fourier Transform
--
-- ArrayFire Docs
--
-- C Interface for real to complex fast fourier transform for one
-- dimensional signals.
--
-- The first dimension of the output will be of size (pad0 / 2) + 1. The
-- second dimension of the output will be pad1. The third dimension of
-- the output will be pad 2.
fftr2c :: (Fractional a, AFType a) => Array a -> Double -> Int -> Array a
-- | Real to Complex Fast Fourier Transform
--
-- ArrayFire Docs
--
-- C Interface for real to complex fast fourier transform for two
-- dimensional signals.
--
-- The first dimension of the output will be of size (pad0 / 2) + 1. The
-- second dimension of the output will be pad1. The third dimension of
-- the output will be pad 2.
fft2r2c :: (Fractional a, AFType a) => Array a -> Double -> Int -> Int -> Array a
-- | Real to Complex Fast Fourier Transform
--
-- ArrayFire Docs
--
-- C Interface for real to complex fast fourier transform for three
-- dimensional signals.
--
-- The first dimension of the output will be of size (pad0 / 2) + 1. The
-- second dimension of the output will be pad1. The third dimension of
-- the output will be pad 2.
fft3r2c :: (Fractional a, AFType a) => Array a -> Double -> Int -> Int -> Int -> Array a
-- | Complex to Real Fast Fourier Transform
--
-- ArrayFire Docs
--
-- C Interface for complex to real fast fourier transform for one
-- dimensional signals.
--
-- The first dimension of the output will be 2 * dim0 - 1 if is_odd is
-- true else 2 * dim0 - 2 where dim0 is the first dimension of the input.
-- The remaining dimensions are unchanged.
fftc2r :: AFType a => Array a -> Double -> Bool -> Array a
-- | Complex to Real Fast Fourier Transform (2-dimensional)
--
-- ArrayFire Docs
--
-- C Interface for complex to real fast fourier transform for two
-- dimensional signals.
--
-- The first dimension of the output will be 2 * dim0 - 1 if is_odd is
-- true else 2 * dim0 - 2 where dim0 is the first dimension of the input.
-- The remaining dimensions are unchanged.
fft2C2r :: AFType a => Array a -> Double -> Bool -> Array a
-- | Complex to Real Fast Fourier Transform (3-dimensional)
--
-- ArrayFire Docs
--
-- C Interface for complex to real fast fourier transform for three
-- dimensional signals.
--
-- The first dimension of the output will be 2 * dim0 - 1 if is_odd is
-- true else 2 * dim0 - 2 where dim0 is the first dimension of the input.
-- The remaining dimensions are unchanged.
fft3C2r :: AFType a => Array a -> Double -> Bool -> Array a
-- | Convolution Integral for one dimensional data
--
-- ArrayFire Docs
--
-- C Interface for convolution on one dimensional signals.
--
--
-- - Note* The default parameter of domain, AF_CONV_AUTO, heuristically
-- switches between frequency and spatial domain.
--
convolve1 :: AFType a => Array a -> Array a -> ConvMode -> ConvDomain -> Array a
-- | Convolution Integral for two dimensional data
--
-- ArrayFire Docs
--
-- C Interface for convolution on two dimensional signals.
--
--
-- - Note* The default parameter of domain, AF_CONV_AUTO, heuristically
-- switches between frequency and spatial domain.
--
convolve2 :: AFType a => Array a -> Array a -> ConvMode -> ConvDomain -> Array a
-- | Convolution Integral for three dimensional data
--
-- ArrayFire Docs
--
-- C Interface for convolution on three dimensional signals.
--
--
-- - Note* The default parameter of domain, AF_CONV_AUTO, heuristically
-- switches between frequency and spatial domain.
--
convolve3 :: AFType a => Array a -> Array a -> ConvMode -> ConvDomain -> Array a
-- | C Interface for separable convolution on two dimensional signals.
--
-- ArrayFire Docs
--
-- C Interface for separable convolution on two dimensional signals.
--
--
-- - Note* The default parameter of domain, AF_CONV_AUTO, heuristically
-- switches between frequency and spatial domain.
--
convolve2Sep :: AFType a => Array a -> Array a -> Array a -> ConvMode -> Array a
-- | 2D Convolution using Fast Fourier Transform
--
-- ArrayFire Docs
--
-- A convolution is a common operation between a source array, a, and a
-- filter (or kernel) array b. The answer to the convolution is the same
-- as computing the coefficients in polynomial multiplication, if a and b
-- are the coefficients.
--
-- C Interface for FFT-based convolution on two dimensional signals.
fftConvolve2 :: AFType a => Array a -> Array a -> ConvMode -> Array a
-- | 3D Convolution using Fast Fourier Transform
--
-- ArrayFire Docs
--
-- A convolution is a common operation between a source array, a, and a
-- filter (or kernel) array b. The answer to the convolution is the same
-- as computing the coefficients in polynomial multiplication, if a and b
-- are the coefficients.
--
-- C Interface for FFT-based convolution on three dimensional signals.
fftConvolve3 :: AFType a => Array a -> Array a -> ConvMode -> Array a
-- | Finite Impulse Filter.
--
-- ArrayFire Docs
--
-- Finite impulse filters take an input x and a co-efficient array b to
-- generate an output y such that:
--
-- C Interface for finite impulse response filter.
fir :: AFType a => Array a -> Array a -> Array a
-- | Infinite Impulse Filter.
--
-- ArrayFire Docs
--
-- Infinite impulse filters take an input x and a feedforward array b,
-- feedback array a to generate an output y such that:
--
-- C Interface for infinite impulse response filter.
--
--
-- - Note* The feedforward coefficients are currently limited to a
-- length of 512
--
iir :: AFType a => Array a -> Array a -> Array a -> Array a
-- | Median Filter
--
-- ArrayFire Docs
--
-- A median filter is similar to the arbitrary filter except that instead
-- of a weighted sum, the median value of the pixels covered by the
-- kernel is returned.
--
-- C Interface for median filter.
medFilt :: AFType a => Array a -> Int -> Int -> BorderType -> Array a
-- | 1D Median Filter
--
-- ArrayFire Docs
--
-- A median filter is similar to the arbitrary filter except that instead
-- of a weighted sum, the median value of the pixels covered by the
-- kernel is returned.
--
-- C Interface for 1D median filter.
medFilt1 :: AFType a => Array a -> Int -> BorderType -> Array a
-- | 2D Median Filter
--
-- ArrayFire Docs
--
-- A median filter is similar to the arbitrary filter except that instead
-- of a weighted sum, the median value of the pixels covered by the
-- kernel is returned.
--
-- C Interface for 2D median filter.
medFilt2 :: AFType a => Array a -> Int -> Int -> BorderType -> Array a
-- | C Interface for setting plan cache size.
--
-- ArrayFire Docs
--
-- This function doesn't do anything if called when CPU backend is
-- active. The plans associated with the most recently used array sizes
-- are cached.
--
--
-- >>> setFFTPlanCacheSize 2
-- ()
--
setFFTPlanCacheSize :: Int -> IO ()
-- | RandomEngine generation, Random Array generation.
--
--
-- {-# LANGUAGE TypeApplications #-}
-- module Main where
--
-- import ArrayFire
--
-- main :: IO ()
-- main = do
-- seed <- getSeed
-- -- ^ Retrieves seed
-- engine <- createRandomEngine Mersenne seed
-- -- ^ Creates engine
-- array <- randomUniform [3,3] engine
-- -- ^ Creates random Array from engine with uniformly distributed data
-- print array
--
-- print =<< randu @Double [2,2]
-- -- ^ Shorthand for creating random Array
--
--
--
-- ArrayFire Array
-- [3 3 1 1]
-- 0.4446 0.1143 0.4283
-- 0.5725 0.1456 0.9182
-- 0.1915 0.1643 0.5997
--
--
--
-- ArrayFire Array
-- [2 2 1 1]
-- 0.6010 0.0278
-- 0.9806 0.2126
--
module ArrayFire.Random
-- | Create random number generator object.
--
--
-- >>> engine <- createRandomEngine 100 Philox
--
createRandomEngine :: Int -> RandomEngineType -> IO RandomEngine
-- | Retains RandomEngine reference
--
--
-- >>> nextEngine <- retainRandomEngine engine
--
retainRandomEngine :: RandomEngine -> IO RandomEngine
-- | Sets RandomEngine to a new RandomEngineType
--
--
-- >>> setRandomEngine engine Philox
--
setRandomEngine :: RandomEngine -> RandomEngineType -> IO ()
-- | Retrieves RandomEngine
--
--
-- >>> randomEngineType <- getRandomEngineType engine
--
getRandomEngineType :: RandomEngine -> IO RandomEngineType
-- | Sets seed on RandomEngine
--
--
-- >>> randomEngineSetSeed engine 100
--
randomEngineSetSeed :: RandomEngine -> Int -> IO ()
-- | Retrieve default RandomEngine
--
--
-- >>> engine <- getDefaultRandomEngine
--
getDefaultRandomEngine :: IO RandomEngine
-- | Set defualt RandomEngine type
--
--
-- >>> setDefaultRandomEngineType Philox
--
setDefaultRandomEngineType :: RandomEngineType -> IO ()
-- | Retrieve seed of RandomEngine
--
--
-- >>> seed <- randomEngineGetSeed engine
--
randomEngineGetSeed :: RandomEngine -> IO Int
-- | Set random seed
--
--
-- >>> setSeed 100
--
setSeed :: Int -> IO ()
-- | Retrieve random seed
--
--
-- >>> seed <- getSeed
--
getSeed :: IO Int
-- | Generate random Array
--
--
-- >>> randn @Double [2,2]
--
--
--
-- ArrayFire Array
-- [2 2 1 1]
-- 0.9428 -0.9523
-- -1.0564 -0.4199
--
randn :: forall a. (AFType a, Fractional a) => [Int] -> IO (Array a)
-- | Generate random uniform Array
--
--
-- >>> randu @Double [2,2]
--
--
--
-- ArrayFire Array
-- [2 2 1 1]
-- 0.6010 0.0278
-- 0.9806 0.2126
--
randu :: forall a. AFType a => [Int] -> IO (Array a)
-- | Generate random uniform Array
--
--
-- >>> randomUniform @Double [2,2] =<< getDefaultRandomEngine
--
--
--
-- ArrayFire Array
-- [2 2 1 1]
-- 0.6010 0.9806
-- 0.0278 0.2126
--
randomUniform :: forall a. AFType a => [Int] -> RandomEngine -> IO (Array a)
-- | Generate random uniform Array
--
--
-- >>> randomNormal @Double [2,2] =<< getDefaultRandomEngine
--
--
--
-- ArrayFire Array
-- [2 2 1 1]
-- -1.4394 0.1952
-- 0.7982 -0.9783
--
randomNormal :: forall a. AFType a => [Int] -> RandomEngine -> IO (Array a)
-- | LAPACK — Linear Algebra PACKage
--
--
-- >>> (u,e,d) = svd (constant @Double [3,3] 10)
-- >>> u
-- ArrayFire Array
-- [3 3 1 1]
-- -0.5774 0.8165 -0.0000
-- -0.5774 -0.4082 -0.7071
-- -0.5774 -0.4082 0.7071
--
-- >>> e
-- ArrayFire Array
-- [3 1 1 1]
-- 30.0000
-- 0.0000
-- 0.0000
--
-- >>> d
-- ArrayFire Array
-- [3 3 1 1]
-- -0.5774 -0.5774 -0.5774
-- -0.8165 0.4082 0.4082
-- -0.0000 0.7071 -0.7071
--
module ArrayFire.LAPACK
-- | Singular Value Decomposition
--
-- ArrayFire Docs
--
-- The arrayfire function only returns the non zero diagonal elements of
-- S.
svd :: AFType a => Array a -> (Array a, Array a, Array a)
-- | Singular Value Decomposition (in-place)
--
-- ArrayFire Docs
--
-- The arrayfire function only returns the non zero diagonal elements of
-- S.
svdInPlace :: AFType a => Array a -> (Array a, Array a, Array a)
-- | Perform LU decomposition
--
-- ArrayFire Docs
--
-- C Interface for LU decomposition.
lu :: AFType a => Array a -> (Array a, Array a, Array a)
-- | Perform LU decomposition (in-place).
--
-- ArrayFire Docs
--
-- C Interface for in place LU decomposition.
luInPlace :: AFType a => Array a -> Bool -> Array a
-- | Perform QR decomposition
--
-- ArrayFire Docs
--
-- C Interface for QR decomposition.
qr :: AFType a => Array a -> (Array a, Array a, Array a)
-- | Perform QR decomposition
--
-- ArrayFire Docs
--
-- C Interface for QR decomposition.
qrInPlace :: AFType a => Array a -> Array a
-- | Perform Cholesky Decomposition
--
-- ArrayFire Docs
--
-- This function decomposes a positive definite matrix A into two
-- triangular matrices.
cholesky :: AFType a => Array a -> Bool -> (Int, Array a)
-- | Perform Cholesky Decomposition
--
-- ArrayFire Docs
--
-- C Interface for in place cholesky decomposition.
choleskyInplace :: AFType a => Array a -> Bool -> Int
-- | Solve a system of equations
--
-- ArrayFire Docs
solve :: AFType a => Array a -> Array a -> MatProp -> Array a
-- | Solve a system of equations.
--
-- ArrayFire Docs
solveLU :: AFType a => Array a -> Array a -> Array a -> MatProp -> Array a
-- | Invert a matrix.
--
-- ArrayFire Docs
--
-- C Interface for inverting a matrix.
inverse :: AFType a => Array a -> MatProp -> Array a
-- | Pseudo-inverse
--
-- Not implemented in 3.6.4
--
-- ArrayFire Docs
--
-- pinverse :: AFType a => Array a -> Double -> MatProp ->
-- Array a pinverse a d m = op1 a (x y -> af_pinverse x y d (toMatProp
-- m))
--
-- Find the rank of the input matrix
--
-- ArrayFire Docs
--
-- This function uses af::qr to find the rank of the input matrix within
-- the given tolerance.
rank :: AFType a => Array a -> Double -> Int
-- | Find the determinant of a Matrix
--
-- ArrayFire Docs
--
-- C Interface for finding the determinant of a matrix.
det :: AFType a => Array a -> (Double, Double)
-- | Find the norm of the input matrix.
--
-- ArrayFire Docs
--
-- This function can return the norm using various metrics based on the
-- type paramter.
norm :: AFType a => Array a -> NormType -> Double -> Double -> Double
-- | Is LAPACK available
--
-- ArrayFire Docs
isLAPACKAvailable :: Bool
-- | Functions for indexing into an Array
module ArrayFire.Index
-- | Index into an Array by Seq
index :: Array a -> [Seq] -> Array a
-- | Lookup an Array by keys along a specified dimension
lookup :: Array a -> Array a -> Int -> Array a
-- | Functions for displaying Array graphically.
--
--
-- >>> window <- createWindow 800 600 "New Chart"
--
module ArrayFire.Graphics
-- | Create window
--
-- ArrayFire Docs
--
--
-- >>> window <- createWindow 800 600 "New Chart"
--
createWindow :: Int -> Int -> String -> IO Window
-- | Sets Window position
--
-- ArrayFire Docs
--
--
-- >>> window <- createWindow 800 600 "New Chart"
--
-- >>> setPosition window 800 600
--
setPosition :: Window -> Int -> Int -> IO ()
-- | Sets Window title
--
-- ArrayFire Docs
--
--
-- >>> window <- createWindow 800 600 "New Chart"
--
-- >>> setTitle window "window title"
--
setTitle :: Window -> String -> IO ()
-- | Sets Window size
--
-- ArrayFire Docs
--
--
-- >>> window <- createWindow 800 600 "New Chart"
--
-- >>> setSize window 800 600
--
setSize :: Window -> Int -> Int -> IO ()
-- | Draw an image onto a Window
--
-- ArrayFire Docs
--
--
-- >>> drawImage window ('constant' \@'Int' 1) ('Cell' 10 10 "test" 'ColorMapSpectrum')
--
drawImage :: Window -> Array a -> Cell -> IO ()
-- | Draw a plot onto a Window
--
-- ArrayFire Docs
--
--
-- >>> drawPlot window ('constant' \@'Int' 1) ('constant' \@'Int' 1) ('Cell' 10 10 "test" 'ColorMapSpectrum')
--
--
--
-- - Note* X and Y should be vectors.
--
drawPlot :: Window -> Array a -> Array a -> Cell -> IO ()
-- | Draw a plot onto a Window
--
-- ArrayFire Docs
--
--
-- - Note* P should be a 3n x 1 vector or one of a 3xn or nx3
-- matrices.
--
drawPlot3 :: Window -> Array a -> Cell -> IO ()
-- | Draw a plot onto a Window
--
-- ArrayFire Docs
--
--
-- - Note* in must be 2d and of the form [n, order], where order is
-- either 2 or 3. If order is 2, then chart is 2D and if order is 3, then
-- chart is 3D.
--
drawPlotNd :: Window -> Array a -> Cell -> IO ()
-- | Draw a plot onto a Window
--
-- ArrayFire Docs
--
--
-- - Note* X and Y should be vectors.
--
drawPlot2d :: Window -> Array a -> Array a -> Cell -> IO ()
-- | Draw a 3D plot onto a Window
--
-- ArrayFire Docs
--
--
-- - Note* X, Y and Z should be vectors.
--
drawPlot3d :: Window -> Array a -> Array a -> Array a -> Cell -> IO ()
-- | Draw a scatter plot onto a Window
--
-- ArrayFire Docs
--
--
-- - Note* X and Y should be vectors.
--
drawScatter :: Window -> Array a -> Array a -> MarkerType -> Cell -> IO ()
-- | Draw a scatter plot onto a Window
--
-- ArrayFire Docs
--
--
-- - Note* X and Y should be vectors.
--
drawScatter3 :: Window -> Array a -> MarkerType -> Cell -> IO ()
-- | Draw a scatter plot onto a Window
--
-- ArrayFire Docs
--
--
-- - Note* in must be 2d and of the form [n, order], where order is
-- either 2 or 3. If order is 2, then chart is 2D and if order is 3, then
-- chart is 3D.
--
drawScatterNd :: Window -> Array a -> MarkerType -> Cell -> IO ()
-- | Draw a scatter plot onto a Window
--
-- ArrayFire Docs
--
--
-- - Note* in must be 2d and of the form [n, order], where order is
-- either 2 or 3. If order is 2, then chart is 2D and if order is 3, then
-- chart is 3D.
--
drawScatter2d :: Window -> Array a -> Array a -> MarkerType -> Cell -> IO ()
-- | Draw a scatter plot onto a Window
--
-- ArrayFire Docs
--
--
-- - Note* X, Y and Z should be vectors.
--
drawScatter3d :: Window -> Array a -> Array a -> Array a -> MarkerType -> Cell -> IO ()
-- | Draw a Histogram onto a Window
--
-- ArrayFire Docs
--
--
-- - Note* X should be a vector.
--
drawHistogram :: Window -> Array a -> Double -> Double -> Cell -> IO ()
-- | Draw a Surface onto a Window
--
-- ArrayFire Docs
--
--
-- - Note* X and Y should be vectors. S should be a 2D array
--
drawSurface :: Window -> Array a -> Array a -> Array a -> Cell -> IO ()
-- | Draw a Vector Field onto a Window
--
-- ArrayFire Docs
--
--
-- - Note* all the Array inputs should be vectors and the same
-- size
--
drawVectorFieldND :: Window -> Array a -> Array a -> Cell -> IO ()
-- | Draw a Vector Field onto a Window
--
-- ArrayFire Docs
--
--
-- - Note* all the Array inputs should be vectors and the same
-- size
--
drawVectorField3d :: Window -> Array a -> Array a -> Array a -> Array a -> Array a -> Array a -> Cell -> IO ()
-- | Draw a Vector Field onto a Window
--
-- ArrayFire Docs
--
--
-- - Note* all the Array inputs should be vectors and the same
-- size
--
drawVectorField2d :: Window -> Array a -> Array a -> Array a -> Array a -> Cell -> IO ()
-- | Draw a grid onto a Window
--
-- ArrayFire Docs
--
--
-- - Note* all the Array inputs should be vectors and the same
-- size
--
grid :: Window -> Int -> Int -> IO ()
-- | Setting axes limits for a histogramplotsurface/vector field.
--
-- ArrayFire Docs
--
--
-- - Note* Set to NULL if the chart is 2D.
--
setAxesLimitsCompute :: Window -> Array a -> Array a -> Array a -> Bool -> Cell -> IO ()
-- | Setting axes limits for a 2D histogramplotsurface/vector field.
--
-- ArrayFire Docs
setAxesLimits2d :: Window -> Float -> Float -> Float -> Float -> Bool -> Cell -> IO ()
-- | Setting axes limits for a 3D histogramplotsurface/vector field.
--
-- ArrayFire Docs
setAxesLimits3d :: Window -> Float -> Float -> Float -> Float -> Float -> Float -> Bool -> Cell -> IO ()
-- | Setting axes titles
--
-- ArrayFire Docs
setAxesTitles :: Window -> String -> String -> String -> Cell -> IO ()
-- | Displays Window
--
-- ArrayFire Docs
showWindow :: Window -> IO ()
-- | Checks if Window is closed
--
-- ArrayFire Docs
isWindowClosed :: Window -> IO Bool
-- | Sets Window visibility
--
-- ArrayFire Docs
setVisibility :: Window -> Bool -> IO ()
-- | Functions for constructing and querying Features
--
--
-- >>> createFeatures 10
--
module ArrayFire.Features
-- | Construct Features
--
--
-- >>> features = createFeatures 10
--
createFeatures :: Int -> Features
-- | Retain Features
--
--
-- >>> features = retainFeatures (createFeatures 10)
--
retainFeatures :: Features -> Features
-- | Get number of Features
--
-- link
--
--
-- >>> getFeaturesNum (createFeatures 10)
-- 10
--
getFeaturesNum :: Features -> Int
-- | Get Feature X-position
--
--
-- >>> getFeaturesXPos (createFeatures 10)
-- ArrayFire Array
-- [10 1 1 1]
-- 0.0000
-- 1.8750
-- 0.0000
-- 2.3750
-- 0.0000
-- 2.5938
-- 0.0000
-- 2.0000
-- 0.0000
-- 2.4375
--
getFeaturesXPos :: Features -> Array a
-- | Get Feature Y-position
--
--
-- >>> getFeaturesYPos (createFeatures 10)
-- ArrayFire Array
-- [10 1 1 1]
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
--
getFeaturesYPos :: Features -> Array a
-- | Get Feature Score
--
--
-- >>> getFeaturesScore (createFeatures 10)
-- ArrayFire Array
-- [10 1 1 1]
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
--
getFeaturesScore :: Features -> Array a
-- | Get Feature orientation
--
--
-- >>> getFeaturesOrientation (createFeatures 10)
-- ArrayFire Array
-- [10 1 1 1]
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
--
getFeaturesOrientation :: Features -> Array a
-- | Get Feature size
--
--
-- >>> getFeaturesSize (createFeatures 10)
-- ArrayFire Array
-- [10 1 1 1]
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
--
getFeaturesSize :: Features -> Array a
-- | Information about ArrayFire API and devices
--
--
-- >>> info
-- ArrayFire v3.6.4 (OpenCL, 64-bit Mac OSX, build 1b8030c5)
-- [0] APPLE: AMD Radeon Pro 555X Compute Engine, 4096 MB
-- -1- APPLE: Intel(R) UHD Graphics 630, 1536 MB
--
module ArrayFire.Device
-- | Retrieve info from ArrayFire API
--
--
-- ArrayFire v3.6.4 (OpenCL, 64-bit Mac OSX, build 1b8030c5)
-- [0] APPLE: AMD Radeon Pro 555X Compute Engine, 4096 MB
-- -1- APPLE: Intel(R) UHD Graphics 630, 1536 MB
--
info :: IO ()
-- | Calls af_init C function from ArrayFire API
--
--
-- >>> afInit
-- ()
--
afInit :: IO ()
-- | Retrieves ArrayFire device information as String, same as
-- info.
--
--
-- >>> getInfoString
-- "ArrayFire v3.6.4 (OpenCL, 64-bit Mac OSX, build 1b8030c5)\n[0] APPLE: AMD Radeon Pro 555X Compute Engine, 4096 MB\n-1- APPLE: Intel(R) UHD Graphics 630, 1536 MB\n"
--
getInfoString :: IO String
-- | Retrieves count of devices
--
--
-- >>> getDeviceCount
-- 2
--
getDeviceCount :: IO Int
-- | Sets a device by Int
--
--
-- >>> setDevice 0
-- ()
--
setDevice :: Int -> IO ()
-- | Retrieves device identifier
--
--
-- >>> getDevice
-- 0
--
getDevice :: IO Int
-- | Set and get available ArrayFire Backends.
--
--
-- module Main where
--
-- import ArrayFire
--
-- main :: IO ()
-- main = print =<< getAvailableBackends
--
--
--
-- [CPU,OpenCL]
--
module ArrayFire.Backend
-- | Set specific Backend to use
--
--
-- >>> setBackend OpenCL
-- ()
--
setBackend :: Backend -> IO ()
-- | Retrieve count of Backends available
--
--
-- >>> getBackendCount
-- 2
--
getBackendCount :: IO Int
-- | Retrieve available Backends
--
--
-- >>> mapM_ print =<< getAvailableBackends
-- CPU
-- OpenCL
--
getAvailableBackends :: IO [Backend]
-- | Retrieve Backend that specific Array was created from
--
--
-- >>> getBackend (scalar @Double 2.0)
-- OpenCL
--
getBackend :: Array a -> Backend
-- | Retrieve active Backend
--
--
-- >>> getActiveBackend
-- OpenCL
--
getActiveBackend :: IO Backend
-- | Retrieve Device ID that Array was created from
--
--
-- >>> getDeviceID (scalar \@Double 2.0)
-- 1
--
getDeviceID :: Array a -> Int
-- | Basic Linear Algebra Subprograms (BLAS) API
--
--
-- main :: IO ()
-- main = print (matmul x y xProp yProp)
-- where
-- x,y :: Array Double
-- x = matrix (2,3) [[1,2],[3,4],[5,6]]
-- y = matrix (3,2) [[1,2,3],[4,5,6]]
--
-- xProp, yProp :: MatProp
-- xProp = None
-- yProp = None
--
--
--
-- ArrayFire Array
-- [2 2 1 1]
-- 22.0000 49.0000
-- 28.0000 64.0000
--
module ArrayFire.BLAS
-- | The following applies for Sparse-Dense matrix multiplication.
--
-- This function can be used with one sparse input. The sparse input must
-- always be the lhs and the dense matrix must be rhs.
--
-- The sparse array can only be of CSR format.
--
-- The returned array is always dense.
--
-- optLhs an only be one of AF_MAT_NONE, AF_MAT_TRANS, AF_MAT_CTRANS.
--
-- optRhs can only be AF_MAT_NONE.
--
--
-- >>> matmul (matrix @Double (2,2) [[1,2],[3,4]]) (matrix @Double (2,2) [[1,2],[3,4]]) None None
-- ArrayFire Array
-- [2 2 1 1]
-- 7.0000 15.0000
-- 10.0000 22.0000
--
matmul :: Array a -> Array a -> MatProp -> MatProp -> Array a
-- | Scalar dot product between two vectors. Also referred to as the inner
-- product.
--
--
-- >>> dot (vector @Double 10 [1..]) (vector @Double 10 [1..]) None None
-- ArrayFire Array
-- [1 1 1 1]
-- 385.0000
--
dot :: Array a -> Array a -> MatProp -> MatProp -> Array a
-- | Scalar dot product between two vectors. Also referred to as the inner
-- product. Returns the result as a host scalar.
--
--
-- >>> dotAll (vector @Double 10 [1..]) (vector @Double 10 [1..]) None None
-- 385.0 :+ 0.0
--
dotAll :: Array a -> Array a -> MatProp -> MatProp -> Complex Double
-- | Transposes a matrix.
--
--
-- >>> array = matrix @Double (2,3) [[2,3],[3,4],[5,6]]
--
-- >>> array
-- ArrayFire Array
-- [2 3 1 1]
-- 2.0000 3.0000 5.0000
-- 3.0000 4.0000 6.0000
--
--
--
-- >>> transpose array True
-- ArrayFire Array
-- [3 2 1 1]
-- 2.0000 3.0000
-- 3.0000 4.0000
-- 5.0000 6.0000
--
transpose :: Array a -> Bool -> Array a
-- | Transposes a matrix.
--
--
-- - Warning: This function mutates an array in-place, all subsequent
-- references will be changed. Use carefully.
--
--
--
-- >>> array = matrix @Double (2,2) [[1,2],[3,4]]
--
-- >>> array
-- ArrayFire Array
-- [3 2 1 1]
-- 1.0000 4.0000
-- 2.0000 5.0000
-- 3.0000 6.0000
--
--
--
-- >>> transposeInPlace array False
--
-- >>> array
-- ArrayFire Array
-- [2 2 1 1]
-- 1.0000 2.0000
-- 3.0000 4.0000
--
transposeInPlace :: Array a -> Bool -> IO ()
-- | Arithmetic functions over Array
--
--
-- module Main where
--
-- import qualified ArrayFire as A
--
-- main :: IO ()
-- main = print $ A.scalar @Int 1 `A.add` A.scalar @Int 1
--
-- -- ArrayFire Array
-- -- [1 1 1 1]
-- -- 2
--
module ArrayFire.Arith
-- | Adds two Array objects
--
--
-- >>> A.scalar @Int 1 `A.add` A.scalar @Int 1
-- ArrayFire Array
-- [1 1 1 1]
-- 2
--
add :: AFType a => Array a -> Array a -> Array a
-- | Adds two Array objects
--
--
-- >>> (A.scalar @Int 1 `A.addBatched` A.scalar @Int 1) True
-- ArrayFire Array
-- [1 1 1 1]
-- 2
--
addBatched :: AFType a => Array a -> Array a -> Bool -> Array a
-- | Subtracts two Array objects
--
--
-- >>> A.scalar @Int 1 `A.sub` A.scalar @Int 1
-- ArrayFire Array
-- [1 1 1 1]
-- 0
--
sub :: AFType a => Array a -> Array a -> Array a
-- | Subtracts two Array objects
--
--
-- >>> (A.scalar @Int 1 `subBatched` A.scalar @Int 1) True
-- ArrayFire Array
-- [1 1 1 1]
-- 0
--
subBatched :: AFType a => Array a -> Array a -> Bool -> Array a
-- | Multiply two Array objects
--
--
-- >>> A.scalar @Int 2 `mul` A.scalar @Int 2
-- ArrayFire Array
-- [1 1 1 1]
-- 4
--
mul :: AFType a => Array a -> Array a -> Array a
-- | Multiply two Array objects
--
--
-- >>> (A.scalar @Int 2 `mulBatched` A.scalar @Int 2) True
-- ArrayFire Array
-- [1 1 1 1]
-- 4
--
mulBatched :: AFType a => Array a -> Array a -> Bool -> Array a
-- | Divide two Array objects
--
--
-- >>> A.scalar @Int 6 `A.div` A.scalar @Int 3
-- ArrayFire Array
-- [1 1 1 1]
-- 2
--
div :: AFType a => Array a -> Array a -> Array a
-- | Divide two Array objects
--
--
-- >>> (A.scalar @Int 6 `A.divBatched` A.scalar @Int 3) True
-- ArrayFire Array
-- [1 1 1 1]
-- 2
--
divBatched :: AFType a => Array a -> Array a -> Bool -> Array a
-- | Test if on Array is less than another Array
--
--
-- >>> A.scalar @Int 1 `A.lt` A.scalar @Int 1
-- ArrayFire Array
-- [1 1 1 1]
-- 0
--
lt :: AFType a => Array a -> Array a -> Array CBool
-- | Test if on Array is less than another Array
--
--
-- >>> (A.scalar @Int 1 `A.ltBatched` A.scalar @Int 1) True
-- ArrayFire Array
-- [1 1 1 1]
-- 0
--
ltBatched :: AFType a => Array a -> Array a -> Bool -> Array CBool
-- | Test if an Array is greater than another Array
--
--
-- >>> A.scalar @Int 1 `A.gt` A.scalar @Int 1
-- ArrayFire Array
-- [1 1 1 1]
-- 0
--
gt :: AFType a => Array a -> Array a -> Array CBool
-- | Test if an Array is greater than another Array
--
--
-- >>> (A.scalar @Int 1 `gtBatched` A.scalar @Int 1) True
-- ArrayFire Array
-- [1 1 1 1]
-- 0
--
gtBatched :: AFType a => Array a -> Array a -> Bool -> Array CBool
-- | Test if one Array is less than or equal to another Array
--
--
-- >>> A.scalar @Int 1 `A.le` A.scalar @Int 1
-- ArrayFire Array
-- [1 1 1 1]
-- 1
--
le :: AFType a => Array a -> Array a -> Array CBool
-- | Test if one Array is less than or equal to another Array
--
--
-- >>> (A.scalar @Int 1 `A.leBatched` A.scalar @Int 1) True
-- ArrayFire Array
-- [1 1 1 1]
-- 1
--
leBatched :: AFType a => Array a -> Array a -> Bool -> Array CBool
-- | Test if one Array is greater than or equal to another
-- Array
--
--
-- >>> A.scalar @Int 1 `A.ge` A.scalar @Int 1
-- ArrayFire Array
-- [1 1 1 1]
-- 1
--
ge :: AFType a => Array a -> Array a -> Array CBool
-- | Test if one Array is greater than or equal to another
-- Array
--
--
-- >>> (A.scalar @Int 1 `A.geBatched` A.scalar @Int 1) True
-- ArrayFire Array
-- [1 1 1 1]
-- 1
--
geBatched :: AFType a => Array a -> Array a -> Bool -> Array CBool
-- | Test if one Array is equal to another Array
--
--
-- >>> A.scalar @Int 1 `A.eq` A.scalar @Int 1
-- ArrayFire Array
-- [1 1 1 1]
-- 1
--
eq :: AFType a => Array a -> Array a -> Array CBool
-- | Test if one Array is equal to another Array
--
--
-- >>> (A.scalar @Int 1 `A.eqBatched` A.scalar @Int 1) True
-- ArrayFire Array
-- [1 1 1 1]
-- 1
--
eqBatched :: AFType a => Array a -> Array a -> Bool -> Array CBool
-- | Test if one Array is not equal to another Array
--
--
-- >>> A.scalar @Int 1 `A.neq` A.scalar @Int 1
-- ArrayFire Array
-- [1 1 1 1]
-- 0
--
neq :: AFType a => Array a -> Array a -> Array CBool
-- | Test if one Array is not equal to another Array
--
--
-- >>> (A.scalar @Int 1 `A.neqBatched` A.scalar @Int 1) True
-- ArrayFire Array
-- [1 1 1 1]
-- 0
--
neqBatched :: AFType a => Array a -> Array a -> Bool -> Array CBool
-- | Logical and one Array with another
--
--
-- >>> A.scalar @Int 1 `A.and` A.scalar @Int 1
-- ArrayFire Array
-- [1 1 1 1]
-- 1
--
and :: AFType a => Array a -> Array a -> Array CBool
-- | Logical and one Array with another
--
--
-- >>> (A.scalar @Int 1 `andBatched` A.scalar @Int 1) True
-- ArrayFire Array
-- [1 1 1 1]
-- 1
--
andBatched :: AFType a => Array a -> Array a -> Bool -> Array CBool
-- | Logical or one Array with another
--
--
-- >>> A.scalar @Int 1 `A.or` A.scalar @Int 1
-- ArrayFire Array
-- [1 1 1 1]
-- 1
--
or :: AFType a => Array a -> Array a -> Array CBool
-- | Logical or one Array with another
--
--
-- >>> (A.scalar @Int 1 `A.orBatched` A.scalar @Int 1) True
-- ArrayFire Array
-- [1 1 1 1]
-- 1
--
orBatched :: AFType a => Array a -> Array a -> Bool -> Array CBool
-- | Not the values of an Array
--
--
-- >>> A.not (A.scalar @Int 1)
-- ArrayFire Array
-- [1 1 1 1]
-- 0
--
not :: AFType a => Array a -> Array CBool
-- | Bitwise and the values in one Array against another
-- Array
--
--
-- >>> A.bitAnd (A.scalar @Int 1) (A.scalar @Int 1)
-- ArrayFire Array
-- [1 1 1 1]
-- 1
--
bitAnd :: AFType a => Array a -> Array a -> Array CBool
-- | Bitwise and the values in one Array against another
-- Array
bitAndBatched :: AFType a => Array a -> Array a -> Bool -> Array CBool
-- | Bitwise or the values in one Array against another Array
--
--
-- >>> A.bitOr (A.scalar @Int 1) (A.scalar @Int 1)
-- ArrayFire Array
-- [1 1 1 1]
-- 1
--
bitOr :: AFType a => Array a -> Array a -> Array CBool
-- | Bitwise or the values in one Array against another Array
--
--
-- >>> A.bitOrBatched (A.scalar @Int 1) (A.scalar @Int 1) False
-- ArrayFire Array
-- [1 1 1 1]
-- 1
--
bitOrBatched :: AFType a => Array a -> Array a -> Bool -> Array CBool
-- | Bitwise xor the values in one Array against another
-- Array
--
--
-- >>> A.bitXor (A.scalar @Int 1) (A.scalar @Int 1)
-- ArrayFire Array
-- [1 1 1 1]
-- 0
--
bitXor :: AFType a => Array a -> Array a -> Array CBool
-- | Bitwise xor the values in one Array against another
-- Array
--
--
-- >>> A.bitXorBatched (A.scalar @Int 1) (A.scalar @Int 1) False
-- ArrayFire Array
-- [1 1 1 1]
-- 0
--
bitXorBatched :: AFType a => Array a -> Array a -> Bool -> Array CBool
-- | Left bit shift the values in one Array against another
-- Array
--
--
-- >>> A.bitShiftL (A.scalar @Int 1) (A.scalar @Int 1)
-- ArrayFire Array
-- [1 1 1 1]
-- 2
--
bitShiftL :: AFType a => Array a -> Array a -> Array CBool
-- | Left bit shift the values in one Array against another
-- Array
--
--
-- >>> A.bitShiftLBatched (A.scalar @Int 1) (A.scalar @Int 1) False
-- ArrayFire Array
-- [1 1 1 1]
-- 2
--
bitShiftLBatched :: AFType a => Array a -> Array a -> Bool -> Array CBool
-- | Right bit shift the values in one Array against another
-- Array
--
--
-- >>> A.bitShiftR (A.scalar @Int 1) (A.scalar @Int 1)
-- ArrayFire Array
-- [1 1 1 1]
-- 0
--
bitShiftR :: AFType a => Array a -> Array a -> Array CBool
-- | Right bit shift the values in one Array against another
-- Array
--
--
-- >>> A.bitShiftRBatched (A.scalar @Int 1) (A.scalar @Int 1) False
-- ArrayFire Array
-- [1 1 1 1]
-- 0
--
bitShiftRBatched :: AFType a => Array a -> Array a -> Bool -> Array CBool
-- | Cast one Array into another
--
--
-- >>> A.cast (A.scalar @Int 1) :: Array Double
-- ArrayFire Array
-- [1 1 1 1]
-- 1.0000
--
cast :: forall a b. (AFType a, AFType b) => Array a -> Array b
-- | Find the minimum of two Arrays
--
--
-- >>> A.minOf (A.scalar @Int 1) (A.scalar @Int 0)
-- ArrayFire Array
-- [1 1 1 1]
-- 0
--
minOf :: AFType a => Array a -> Array a -> Array a
-- | Find the minimum of two Arrays
--
--
-- >>> A.minOfBatched (A.scalar @Int 1) (A.scalar @Int 0) False
-- ArrayFire Array
-- [1 1 1 1]
-- 0
--
minOfBatched :: AFType a => Array a -> Array a -> Bool -> Array a
-- | Find the maximum of two Arrays
--
--
-- >>> A.maxOf (A.scalar @Int 1) (A.scalar @Int 0)
-- ArrayFire Array
-- [1 1 1 1]
-- 1
--
maxOf :: AFType a => Array a -> Array a -> Array a
-- | Find the maximum of two Arrays
--
--
-- >>> A.maxOfBatched (A.scalar @Int 1) (A.scalar @Int 0) False
-- ArrayFire Array
-- [1 1 1 1]
-- 1
--
maxOfBatched :: AFType a => Array a -> Array a -> Bool -> Array a
-- | Should take the clamp
--
--
-- >>> clamp (A.scalar @Int 2) (A.scalar @Int 1) (A.scalar @Int 3)
-- ArrayFire Array
-- [1 1 1 1]
-- 2
--
clamp :: Array a -> Array a -> Array a -> Array a
-- | Should take the clamp
--
--
-- >>> (clampBatched (A.scalar @Int 2) (A.scalar @Int 1) (A.scalar @Int 3)) True
-- ArrayFire Array
-- [1 1 1 1]
-- 2
--
clampBatched :: Array a -> Array a -> Array a -> Bool -> Array a
-- | Find the remainder of two Arrays
--
--
-- >>> A.rem (A.vector @Int 10 [1..]) (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
--
rem :: AFType a => Array a -> Array a -> Array a
-- | Find the remainder of two Arrays
--
--
-- >>> A.remBatched (A.vector @Int 10 [1..]) (vector @Int 10 [2..]) True
-- ArrayFire Array
-- [10 1 1 1]
-- 1
-- 2
-- 3
-- 4
-- 5
-- 6
-- 7
-- 8
-- 9
-- 10
--
remBatched :: AFType a => Array a -> Array a -> Bool -> Array a
-- | Take the mod of two Arrays
--
--
-- >>> A.mod (A.vector @Int 10 [1..]) (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
--
mod :: AFType a => Array a -> Array a -> Array a
-- | Take the mod of two Arrays
--
--
-- >>> A.modBatched (vector @Int 10 [1..]) (vector @Int 10 [1..]) True
-- ArrayFire Array
-- [10 1 1 1]
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
--
modBatched :: AFType a => Array a -> Array a -> Bool -> Array a
-- | Take the absolute value of an array
--
--
-- >>> A.abs (A.scalar @Int (-1))
-- ArrayFire Array
-- [1 1 1 1]
-- 1.0000
--
abs :: AFType a => Array a -> Array a
-- | Find the arg of an array
--
--
-- >>> A.arg (vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
--
arg :: AFType a => Array a -> Array a
-- | Find the sign of two Arrays
--
--
-- >>> A.sign (vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.0000
-- 0.0000
-- 0.0000
-- 0.0000
-- 0.0000
-- 0.0000
-- 0.0000
-- 0.0000
-- 0.0000
-- 0.0000
--
sign :: AFType a => Array a -> Array a
-- | Round the values in an Array
--
--
-- >>> A.round (A.vector @Double 10 [1.4,1.5..])
-- ArrayFire Array
-- [10 1 1 1]
-- 1.0000
-- 2.0000
-- 2.0000
-- 2.0000
-- 2.0000
-- 2.0000
-- 2.0000
-- 2.0000
-- 2.0000
-- 2.0000
--
round :: AFType a => Array a -> Array a
-- | Truncate the values of an Array
--
--
-- >>> A.trunc (A.vector @Double 10 [0.9,1.0..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.0000
-- 1.0000
-- 1.0000
-- 1.0000
-- 1.0000
-- 1.0000
-- 1.0000
-- 1.0000
-- 1.0000
-- 1.0000
--
trunc :: AFType a => Array a -> Array a
-- | Take the floor of all values in an Array
--
--
-- >>> A.floor (A.vector @Double 10 [11.0,10.9..])
-- ArrayFire Array
-- [10 1 1 1]
-- 11.0000
-- 10.0000
-- 10.0000
-- 10.0000
-- 10.0000
-- 10.0000
-- 10.0000
-- 10.0000
-- 10.0000
-- 10.0000
--
floor :: AFType a => Array a -> Array a
-- | Take the ceil of all values in an Array
--
--
-- >>> A.ceil (A.vector @Double 10 [0.9,1.0..])
-- ArrayFire Array
-- [10 1 1 1]
-- 1.0000
-- 1.0000
-- 2.0000
-- 2.0000
-- 2.0000
-- 2.0000
-- 2.0000
-- 2.0000
-- 2.0000
-- 2.0000
--
ceil :: AFType a => Array a -> Array a
-- | Take the sin of all values in an Array
--
--
-- >>> A.sin (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.8415
-- 0.9093
-- 0.1411
-- -0.7568
-- -0.9589
-- -0.2794
-- 0.6570
-- 0.9894
-- 0.4121
-- -0.5440
--
sin :: AFType a => Array a -> Array a
-- | Take the cos of all values in an Array
--
--
-- >>> A.cos (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.5403
-- -0.4161
-- -0.9900
-- -0.6536
-- 0.2837
-- 0.9602
-- 0.7539
-- -0.1455
-- -0.9111
-- -0.8391
--
cos :: AFType a => Array a -> Array a
-- | Take the tan of all values in an Array
--
--
-- >>> A.tan (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 1.5574
-- -2.1850
-- -0.1425
-- 1.1578
-- -3.3805
-- -0.2910
-- 0.8714
-- -6.7997
-- -0.4523
-- 0.6484
--
tan :: AFType a => Array a -> Array a
-- | Take the asin of all values in an Array
--
--
-- >>> A.asin (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 1.5708
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
--
asin :: AFType a => Array a -> Array a
-- | Take the acos of all values in an Array
--
--
-- >>> A.acos (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.0000
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
--
acos :: AFType a => Array a -> Array a
-- | Take the atan of all values in an Array
--
--
-- >>> A.atan (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.7854
-- 1.1071
-- 1.2490
-- 1.3258
-- 1.3734
-- 1.4056
-- 1.4289
-- 1.4464
-- 1.4601
-- 1.4711
--
atan :: AFType a => Array a -> Array a
-- | Take the atan2 of all values in an Array
--
--
-- >>> A.atan2 (A.vector @Double 10 [1..]) (A.vector @Double 10 [2..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.4636
-- 0.5880
-- 0.6435
-- 0.6747
-- 0.6947
-- 0.7086
-- 0.7188
-- 0.7266
-- 0.7328
-- 0.7378
--
atan2 :: AFType a => Array a -> Array a -> Array a
-- | Take the atan2 of all values in an Array
--
--
-- >>> A.atan2Batched (A.vector @Double 10 [1..]) (A.vector @Double 10 [2..]) True
-- ArrayFire Array
-- [10 1 1 1]
-- 0.4636
-- 0.5880
-- 0.6435
-- 0.6747
-- 0.6947
-- 0.7086
-- 0.7188
-- 0.7266
-- 0.7328
-- 0.7378
--
atan2Batched :: AFType a => Array a -> Array a -> Bool -> Array a
-- | Take the cplx2 of all values in an Array
--
--
-- >>> A.cplx2 (A.vector @Int 10 [1..]) (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- (1.0000,1.0000)
-- (2.0000,2.0000)
-- (3.0000,3.0000)
-- (4.0000,4.0000)
-- (5.0000,5.0000)
-- (6.0000,6.0000)
-- (7.0000,7.0000)
-- (8.0000,8.0000)
-- (9.0000,9.0000)
-- (10.0000,10.0000)
--
cplx2 :: AFType a => Array a -> Array a -> Array a
-- | Take the cplx2Batched of all values in an Array
--
--
-- >>> A.cplx2Batched (A.vector @Int 10 [1..]) (A.vector @Int 10 [1..]) True
-- ArrayFire Array
-- [10 1 1 1]
-- (1.0000,1.0000)
-- (2.0000,2.0000)
-- (3.0000,3.0000)
-- (4.0000,4.0000)
-- (5.0000,5.0000)
-- (6.0000,6.0000)
-- (7.0000,7.0000)
-- (8.0000,8.0000)
-- (9.0000,9.0000)
-- (10.0000,10.0000)
--
cplx2Batched :: AFType a => Array a -> Array a -> Bool -> Array a
-- | Execute cplx
--
--
-- >>> A.cplx (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- (1.0000,0.0000)
-- (2.0000,0.0000)
-- (3.0000,0.0000)
-- (4.0000,0.0000)
-- (5.0000,0.0000)
-- (6.0000,0.0000)
-- (7.0000,0.0000)
-- (8.0000,0.0000)
-- (9.0000,0.0000)
-- (10.0000,0.0000)
--
cplx :: AFType a => Array a -> Array a
-- | Execute real
--
--
-- >>> A.real (A.scalar @(Complex Double) (10 :+ 11)) :: Array Double
-- ArrayFire Array
-- [1 1 1 1]
-- 10.0000
--
real :: (AFType a, AFType (Complex b), RealFrac a, RealFrac b) => Array (Complex b) -> Array a
-- | Execute imag
--
--
-- >>> A.imag (A.scalar @(Complex Double) (10 :+ 11)) :: Array Double
-- ArrayFire Array
-- [1 1 1 1]
-- 11.0000
--
imag :: (AFType a, AFType (Complex b), RealFrac a, RealFrac b) => Array (Complex b) -> Array a
-- | Execute conjg
--
--
-- >>> A.conjg (A.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
--
conjg :: AFType a => Array a -> Array a
-- | Execute sinh
--
--
-- >>> A.sinh (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 1.1752
-- 3.6269
-- 10.0179
-- 27.2899
-- 74.2032
-- 201.7132
-- 548.3161
-- 1490.4789
-- 4051.5420
-- 11013.2324
--
sinh :: AFType a => Array a -> Array a
-- | Execute cosh
--
--
-- >>> A.cosh (A.vector @Double 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 1.5431
-- 3.7622
-- 10.0677
-- 27.3082
-- 74.2099
-- 201.7156
-- 548.3170
-- 1490.4792
-- 4051.5420
-- 11013.2329
--
cosh :: AFType a => Array a -> Array a
-- | Execute tanh
--
--
-- >>> A.tanh (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.7616
-- 0.9640
-- 0.9951
-- 0.9993
-- 0.9999
-- 1.0000
-- 1.0000
-- 1.0000
-- 1.0000
-- 1.0000
--
tanh :: AFType a => Array a -> Array a
-- | Execute asinh
--
--
-- >>> A.asinh (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.8814
-- 1.4436
-- 1.8184
-- 2.0947
-- 2.3124
-- 2.4918
-- 2.6441
-- 2.7765
-- 2.8934
-- 2.9982
--
asinh :: AFType a => Array a -> Array a
-- | Execute acosh
--
--
-- >>> A.acosh (A.vector @Double 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.0000
-- 1.3170
-- 1.7627
-- 2.0634
-- 2.2924
-- 2.4779
-- 2.6339
-- 2.7687
-- 2.8873
-- 2.9932
--
acosh :: AFType a => Array a -> Array a
-- | Execute atanh
--
--
-- >>> A.atanh (A.vector @Double 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- inf
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
-- nan
--
atanh :: AFType a => Array a -> Array a
-- | Execute root
--
--
-- >>> A.root (A.vector @Double 10 [1..]) (A.vector @Double 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 1.0000
-- 1.4142
-- 1.4422
-- 1.4142
-- 1.3797
-- 1.3480
-- 1.3205
-- 1.2968
-- 1.2765
-- 1.2589
--
root :: AFType a => Array a -> Array a -> Array a
-- | Execute rootBatched
--
--
-- >>> A.rootBatched (vector @Double 10 [1..]) (vector @Double 10 [1..]) True
-- ArrayFire Array
-- [10 1 1 1]
-- 1.0000
-- 1.4142
-- 1.4422
-- 1.4142
-- 1.3797
-- 1.3480
-- 1.3205
-- 1.2968
-- 1.2765
-- 1.2589
--
rootBatched :: AFType a => Array a -> Array a -> Bool -> Array a
-- | Execute pow
--
--
-- >>> A.pow (A.vector @Int 10 [1..]) 2
-- ArrayFire Array
-- [10 1 1 1]
-- 1
-- 4
-- 9
-- 16
-- 25
-- 36
-- 49
-- 64
-- 81
-- 100
--
pow :: AFType a => Array a -> Array a -> Array a
-- | Execute powBatched
--
--
-- >>> A.powBatched (A.vector @Int 10 [1..]) (A.constant @Int [1] 2) True
-- ArrayFire Array
-- [10 1 1 1]
-- 1
-- 4
-- 9
-- 16
-- 25
-- 36
-- 49
-- 64
-- 81
-- 100
--
powBatched :: AFType a => Array a -> Array a -> Bool -> Array a
-- | Raise an Array to the second power
--
--
-- >>> A.pow2 (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 2
-- 4
-- 8
-- 16
-- 32
-- 64
-- 128
-- 256
-- 512
-- 1024
--
pow2 :: AFType a => Array a -> Array a
-- | Execute exp on Array
--
--
-- >>> A.exp (A.vector @Double 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 2.7183
-- 7.3891
-- 20.0855
-- 54.5982
-- 148.4132
-- 403.4288
-- 1096.6332
-- 2980.9580
-- 8103.0839
-- 22026.4658
--
exp :: AFType a => Array a -> Array a
-- | Execute sigmoid on Array
--
--
-- >>> A.sigmoid (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.7311
-- 0.8808
-- 0.9526
-- 0.9820
-- 0.9933
-- 0.9975
-- 0.9991
-- 0.9997
-- 0.9999
-- 1.0000
--
sigmoid :: AFType a => Array a -> Array a
-- | Execute expm1
--
--
-- >>> A.expm1 (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 1.7183
-- 6.3891
-- 19.0855
-- 53.5981
-- 147.4132
-- 402.4288
-- 1095.6332
-- 2979.9580
-- 8102.0840
-- 22025.4648
--
expm1 :: AFType a => Array a -> Array a
-- | Execute erf
--
--
-- >>> A.erf (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.8427
-- 0.9953
-- 1.0000
-- 1.0000
-- 1.0000
-- 1.0000
-- 1.0000
-- 1.0000
-- 1.0000
-- 1.0000
--
erf :: AFType a => Array a -> Array a
-- | Execute erfc
--
--
-- >>> A.erfc (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.1573
-- 0.0047
-- 0.0000
-- 0.0000
-- 0.0000
-- 0.0000
-- 0.0000
-- 0.0000
-- 0.0000
-- 0.0000
--
erfc :: AFType a => Array a -> Array a
-- | Execute log
--
--
-- >>> A.log (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.0000
-- 0.6931
-- 1.0986
-- 1.3863
-- 1.6094
-- 1.7918
-- 1.9459
-- 2.0794
-- 2.1972
-- 2.3026
--
log :: AFType a => Array a -> Array a
-- | Execute log1p
--
--
-- >>> A.log1p (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.6931
-- 1.0986
-- 1.3863
-- 1.6094
-- 1.7918
-- 1.9459
-- 2.0794
-- 2.1972
-- 2.3026
-- 2.3979
--
log1p :: AFType a => Array a -> Array a
-- | Execute log10
--
--
-- >>> A.log10 (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.0000
-- 0.3010
-- 0.4771
-- 0.6021
-- 0.6990
-- 0.7782
-- 0.8451
-- 0.9031
-- 0.9542
-- 1.0000
--
log10 :: AFType a => Array a -> Array a
-- | Execute log2
--
--
-- >>> A.log2 (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.0000
-- 1.0000
-- 1.5850
-- 2.0000
-- 2.3219
-- 2.5850
-- 2.8074
-- 3.0000
-- 3.1699
-- 3.3219
--
log2 :: AFType a => Array a -> Array a
-- | Execute sqrt
--
--
-- >>> A.sqrt (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 1.0000
-- 1.4142
-- 1.7321
-- 2.0000
-- 2.2361
-- 2.4495
-- 2.6458
-- 2.8284
-- 3.0000
-- 3.1623
--
sqrt :: AFType a => Array a -> Array a
-- | Execute cbrt
--
--
-- >>> A.cbrt (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 1.0000
-- 1.2599
-- 1.4422
-- 1.5874
-- 1.7100
-- 1.8171
-- 1.9129
-- 2.0000
-- 2.0801
-- 2.1544
--
cbrt :: AFType a => Array a -> Array a
-- | Execute factorial
--
--
-- >>> A.factorial (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 1.0000
-- 2.0000
-- 6.0000
-- 24.0000
-- 120.0000
-- 720.0001
-- 5040.0020
-- 40319.9961
-- 362880.0000
-- 3628801.7500
--
factorial :: AFType a => Array a -> Array a
-- | Execute tgamma
--
--
-- >>> tgamma (vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 1.0000
-- 1.0000
-- 2.0000
-- 6.0000
-- 24.0000
-- 120.0000
-- 720.0001
-- 5040.0020
-- 40319.9961
-- 362880.0000
--
tgamma :: AFType a => Array a -> Array a
-- | Execute lgamma
--
--
-- >>> A.lgamma (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0.0000
-- 0.0000
-- 0.6931
-- 1.7918
-- 3.1781
-- 4.7875
-- 6.5793
-- 8.5252
-- 10.6046
-- 12.8018
--
lgamma :: AFType a => Array a -> Array a
-- | Execute isZero
--
--
-- >>> A.isZero (A.vector @CBool 10 (repeat 0))
-- ArrayFire Array
-- [10 1 1 1]
-- 1
-- 1
-- 1
-- 1
-- 1
-- 1
-- 1
-- 1
-- 1
-- 1
--
isZero :: AFType a => Array a -> Array a
-- | Execute isInf
--
--
-- >>> A.isInf (A.vector @Double 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
-- 0
--
isInf :: (Real a, AFType a) => Array a -> Array a
-- | Execute isNaN
--
--
-- >>> A.isNaN $ A.acos (A.vector @Int 10 [1..])
-- ArrayFire Array
-- [10 1 1 1]
-- 0
-- 1
-- 1
-- 1
-- 1
-- 1
-- 1
-- 1
-- 1
-- 1
--
isNaN :: forall a. (AFType a, Real a) => Array a -> Array a
-- | Functions for loading and manipulating images with Array
--
--
-- >>> image <- loadImage "image.png" True
--
module ArrayFire.Image
-- | Calculates the gradient of an image
--
--
-- >>> print (gradient image)
--
gradient :: Array a -> (Array a, Array a)
-- | Loads an image from disk
--
--
-- >>> image <- loadImage "image.png" True
--
loadImage :: String -> Bool -> IO (Array a)
-- | Saves an image to disk
--
--
-- >>> saveImage image "image.png"
--
saveImage :: Array a -> String -> IO ()
-- | Loads an image natively
--
--
-- >>> image <- loadImageNative "image.png"
--
loadImageNative :: String -> IO (Array a)
-- | Saves an image natively
--
--
-- >>> saveImageNative image "image.png"
--
saveImageNative :: Array a -> String -> IO ()
-- | Returns true if ArrayFire was compiled with ImageIO (FreeImage)
-- support
--
--
-- >>> print =<< isImageIOAvailable
--
isImageIOAvailable :: IO Bool
-- | Resize an input image.
--
-- ArrayFire Docs
--
-- Resizing an input image can be done using either AF_INTERP_NEAREST,
-- AF_INTERP_BILINEAR or AF_INTERP_LOWER, interpolations. Nearest
-- interpolation will pick the nearest value to the location, bilinear
-- interpolation will do a weighted interpolation for calculate the new
-- size and lower interpolation is similar to the nearest, except it will
-- use the floor function to get the lower neighbor.
resize :: Array a -> Int -> Int -> InterpType -> Array a
-- | Transform an input image.
--
-- ArrayFire Docs
--
-- The transform function uses an affine or perspective transform matrix
-- to tranform an input image into a new one.
transform :: Array a -> Array a -> Int -> Int -> InterpType -> Bool -> Array a
-- | Transform input coordinates.
--
-- ArrayFire Docs
--
-- C Interface for transforming an image C++ Interface for transforming
-- coordinates.
transformCoordinates :: Array a -> Float -> Float -> Array a
-- | Rotate an input image.
--
-- ArrayFire Docs
--
-- Rotating an input image can be done using AF_INTERP_NEAREST,
-- AF_INTERP_BILINEAR or AF_INTERP_LOWER interpolations. Nearest
-- interpolation will pick the nearest value to the location, whereas
-- bilinear interpolation will do a weighted interpolation for calculate
-- the new size.
rotate :: Array a -> Float -> Bool -> InterpType -> Array a
-- | Translate an input image.
--
-- ArrayFire Docs
--
-- Translating an image is moving it along 1st and 2nd dimensions by
-- trans0 and trans1. Positive values of these will move the data towards
-- negative x and negative y whereas negative values of these will move
-- the positive right and positive down. See the example below for more.
translate :: Array a -> Float -> Float -> Int -> Int -> InterpType -> Array a
-- | Scale an input image.
--
-- ArrayFire Docs
--
-- Scale is the same functionality as af::resize except that the scale
-- function uses the transform kernels. The other difference is that
-- scale does not set boundary values to be the boundary of the input
-- array. Instead these are set to 0.
scale :: Array a -> Float -> Float -> Int -> Int -> InterpType -> Array a
-- | Skew an input image.
--
-- ArrayFire Docs
--
-- Skew function skews the input array along dim0 by skew0 and along dim1
-- by skew1. The skew areguments are in radians. Skewing the data means
-- the data remains parallel along 1 dimensions but the other dimensions
-- gets moved along based on the angle. If both skew0 and skew1 are
-- specified, then the data will be skewed along both directions.
skew :: Array a -> Float -> Float -> Int -> Int -> InterpType -> Bool -> Array a
-- | Histogram of input data.
--
-- ArrayFire Docs
--
-- A histogram is a representation of the distribution of given data.
-- This representation is essentially a graph consisting of the data
-- range or domain on one axis and frequency of occurence on the other
-- axis. All the data in the domain is counted in the appropriate bin.
-- The total number of elements belonging to each bin is known as the
-- bin's frequency.
histogram :: AFType a => Array a -> Int -> Double -> Double -> Array Word32
-- | Dilation(morphological operator) for images.
--
-- ArrayFire Docs
--
-- The dilation function takes two pieces of data as inputs. The first is
-- the input image to be morphed, and the second is the mask indicating
-- the neighborhood around each pixel to match.
--
--
-- - Note* if mask is all ones, this function behaves like max
-- filter
--
dilate :: Array a -> Array a -> Array a
-- | Dilation (morphological operator) for volumes.
--
-- ArrayFire Docs
--
-- Dilation for a volume is similar to the way dilation works on an
-- image. Only difference is that the masking operation is performed on a
-- volume instead of a rectangular region.
dilate3 :: Array a -> Array a -> Array a
-- | Erosion (morphological operator) for volumes.
--
-- ArrayFire Docs
--
-- The erosion function is a morphological transformation on an image
-- that requires two inputs. The first is the image to be morphed, and
-- the second is the mask indicating neighborhood that must be white in
-- order to preserve each pixel.
--
--
-- - Note* if mask is all ones, this function behaves like min
-- filter
--
erode :: Array a -> Array a -> Array a
-- | Erosion (morphological operator) for volumes.
--
-- ArrayFire Docs
--
-- Erosion for a volume is similar to the way erosion works on an image.
-- Only difference is that the masking operation is performed on a volume
-- instead of a rectangular region.
erode3 :: Array a -> Array a -> Array a
-- | Bilateral Filter.
--
-- ArrayFire Docs
--
-- A bilateral filter is a edge-preserving filter that reduces noise in
-- an image. The intensity of each pixel is replaced by a weighted
-- average of the intensities of nearby pixels. The weights follow a
-- Gaussian distribution and depend on the distance as well as the color
-- distance.
bilateral :: Array a -> Float -> Float -> Bool -> Array a
-- | Meanshift Filter.
--
-- ArrayFire Docs
--
-- A meanshift filter is an edge-preserving smoothing filter commonly
-- used in object tracking and image segmentation.
meanShift :: Array a -> Float -> Float -> Int -> Bool -> Array a
-- | Find minimum value from a window.
--
-- ArrayFire Docs
--
-- minfilt finds the smallest value from a 2D window and assigns it to
-- the current pixel.
minFilt :: Array a -> Int -> Int -> BorderType -> Array a
-- | Find maximum value from a window.
--
-- ArrayFire Docs
--
-- maxFilt finds the smallest value from a 2D window and assigns
-- it to the current pixel.
maxFilt :: Array a -> Int -> Int -> BorderType -> Array a
-- | Find blobs in given image.
--
-- ArrayFire Docs
--
-- Given a binary image (with zero representing background pixels),
-- regions computes a floating point image where each connected component
-- is labeled from 1 to N, the total number of components in the image.
-- ** FIX ME**
regions :: forall a. AFType a => Array a -> Connectivity -> Array a
-- | Sobel Operators.
--
-- ArrayFire Docs
--
-- Sobel operators perform a 2-D spatial gradient measurement on an image
-- to emphasize the regions of high spatial frequency, namely edges
--
--
-- - Note* If img is 3d array, a batch operation will be
-- performed.
--
sobel_operator :: Array a -> Int -> (Array a, Array a)
-- | RGB to Grayscale colorspace converter.
--
-- ArrayFire Docs
--
-- RGB (Red, Green, Blue) is the most common format used in computer
-- imaging. RGB stores individual values for red, green and blue, and
-- hence the 3 values per pixel. A combination of these three values
-- produces the gamut of unique colors.
rgb2gray :: Array a -> Float -> Float -> Float -> Array a
-- | Grayscale to RGB colorspace converter.
--
-- ArrayFire Docs
--
-- Grayscale is a single channel color space where pixel value ranges
-- from 0 to 1. Zero represents black, one represent white and any value
-- between zero & one is a gray value
gray2rgb :: Array a -> Float -> Float -> Float -> Array a
-- | Histogram equalization of input image.
--
-- ArrayFire Docs
--
-- Histogram equalization is a method in image processing of contrast
-- adjustment using the image's histogram.
histEqual :: Array a -> Array a -> Array a
-- | Creates a Gaussian Kernel.
--
-- ArrayFire Docs
--
-- This function creates a kernel of a specified size that contains a
-- Gaussian distribution. This distribution is normalized to one. This is
-- most commonly used when performing a Gaussian blur on an image. The
-- function takes two sets of arguments, the size of the kernel (width
-- and height in pixels) and the sigma parameters (for row and column)
-- which effect the distribution of the weights in the y and x
-- directions, respectively.
gaussianKernel :: Int -> Int -> Double -> Double -> Array a
-- | HSV to RGB colorspace converter.
--
-- ArrayFire Docs
--
-- C Interface for converting HSV to RGB.
--
--
-- - Note* input must be three dimensional
--
hsv2rgb :: Array a -> Array a
-- | RGB to HSV colorspace converter.
--
-- ArrayFire Docs
--
-- RGB (Red, Green, Blue) is the most common format used in computer
-- imaging. RGB stores individual values for red, green and blue, and
-- hence the 3 values per pixel. A combination of these three values
-- produces the gamut of unique colors.
rgb2hsv :: Array a -> Array a
-- | Colorspace conversion function.
--
-- ArrayFire Docs
--
-- C Interface wrapper for color space conversion.
colorSpace :: Array a -> CSpace -> CSpace -> Array a
-- | Rearrange windowed sections of an array into columns (or rows).
--
-- ArrayFire Docs
--
-- C Interface for rearranging windowed sections of an input into columns
-- (or rows)
unwrap :: Array a -> Int -> Int -> Int -> Int -> Int -> Int -> Bool -> Array a
-- | Performs the opposite of unwrap.
--
-- ArrayFire Docs
wrap :: Array a -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Bool -> Array a
-- | Summed Area Tables.
--
-- ArrayFire Docs
--
-- RGB (Red, Green, Blue) is the most common format used in computer
-- imaging. RGB stores individual values for red, green and blue, and
-- hence the 3 values per pixel. A combination of these three values
-- produces the gamut of unique colors.
sat :: Array a -> Array a
-- | YCbCr to RGB colorspace converter
--
-- ArrayFire Docs
--
-- YCbCr is a family of color spaces used as a part of the color image
-- pipeline in video and digital photography systems where Y is luma
-- component and Cb & Cr are the blue-difference and red-difference
-- chroma components.
ycbcr2rgb :: Array a -> YccStd -> Array a
-- | RGB to YCbCr colorspace converter.
--
-- ArrayFire Docs
--
-- RGB (Red, Green, Blue) is the most common format used in computer
-- imaging. RGB stores individual values for red, green and blue, and
-- hence the 3 values per pixel. A combination of these three values
-- produces the gamut of unique colors.
rgb2ycbcr :: Array a -> YccStd -> Array a
-- | Finding different properties of image regions.
--
-- ArrayFire Docs
--
-- C Interface for calculating image moment(s) of a single image.
moments :: Array a -> MomentType -> Array a
-- | Finding different properties of image regions.
--
-- ArrayFire Docs
--
-- C Interface for calculating image moment(s) of a single image.
momentsAll :: Array a -> MomentType -> Double
-- | Canny Edge Detector
--
-- ArrayFire Docs
--
-- The Canny edge detector is an edge detection operator that uses a
-- multi-stage algorithm to detect a wide range of edges in images.
canny :: Array a -> CannyThreshold -> Float -> Float -> Int -> Bool -> Array a
-- | Anisotropic Smoothing Filter.
--
-- ArrayFire Docs
--
-- C Interface for anisotropic diffusion.
anisotropicDiffusion :: Array a -> Float -> Float -> Int -> FluxFunction -> DiffusionEq -> Array a
-- | Functions for populating Array with Data.
--
--
-- >>> constant @Double [2,2] 2.0
-- ArrayFire Array
-- [2 2 1 1]
-- 2.0000 2.0000
-- 2.0000 2.0000
--
module ArrayFire.Data
-- | Creates an Array from a scalar value from given dimensions
--
--
-- >>> constant @Double [2,2] 2.0
-- ArrayFire Array
-- [2 2 1 1]
-- 2.0000 2.0000
-- 2.0000 2.0000
--
constant :: forall a. AFType a => [Int] -> a -> Array a
-- | Creates a range of values in an Array
--
--
-- >>> range @Double [10] (-1)
-- ArrayFire Array
-- [10 1 1 1]
-- 0.0000
-- 1.0000
-- 2.0000
-- 3.0000
-- 4.0000
-- 5.0000
-- 6.0000
-- 7.0000
-- 8.0000
-- 9.0000
--
range :: forall a. AFType a => [Int] -> Int -> Array a
-- | Create an sequence [0, dims.elements() - 1] and modify to specified
-- dimensions dims and then tile it according to tile_dims.
--
-- http://arrayfire.org/docs/group__data__func__iota.htm
--
--
-- >>> iota @Double [5,3] []
-- ArrayFire Array
-- [5 3 1 1]
-- 0.0000 5.0000 10.0000
-- 1.0000 6.0000 11.0000
-- 2.0000 7.0000 12.0000
-- 3.0000 8.0000 13.0000
-- 4.0000 9.0000 14.0000
--
--
--
-- >>> iota @Double [5,3] [1,2]
-- ArrayFire Array
-- [5 6 1 1]
-- 0.0000 5.0000 10.0000 0.0000 5.0000 10.0000
-- 1.0000 6.0000 11.0000 1.0000 6.0000 11.0000
-- 2.0000 7.0000 12.0000 2.0000 7.0000 12.0000
-- 3.0000 8.0000 13.0000 3.0000 8.0000 13.0000
-- 4.0000 9.0000 14.0000 4.0000 9.0000 14.0000
--
iota :: forall a. AFType a => [Int] -> [Int] -> Array a
-- | Creates the identity Array from given dimensions
--
--
-- >>> identity [2,2]
-- ArrayFire Array
-- [2 2 1 1]
-- 1.0000 0.0000
-- 0.0000 1.0000
--
identity :: forall a. AFType a => [Int] -> Array a
-- | Create a diagonal matrix from input array when extract is set to false
--
--
-- >>> diagCreate (vector @Double 2 [1..]) 0
-- ArrayFire Array
-- [2 2 1 1]
-- 1.0000 0.0000
-- 0.0000 2.0000
--
diagCreate :: AFType (a :: *) => Array a -> Int -> Array a
-- | Create a diagonal matrix from input array when extract is set to false
--
--
-- >>> diagExtract (matrix @Double (2,2) [[1,2],[3,4]]) 0
-- ArrayFire Array
-- [2 1 1 1]
-- 1.0000
-- 4.0000
--
diagExtract :: AFType (a :: *) => Array a -> Int -> Array a
-- | Join two Arrays together along a specified dimension
--
--
-- >>> join 0 (matrix @Double (2,2) [[1,2],[3,4]]) (matrix @Double (2,2) [[5,6],[7,8]])
-- ArrayFire Array
-- [4 2 1 1]
-- 1.0000 3.0000
-- 2.0000 4.0000
-- 5.0000 7.0000
-- 6.0000 8.0000
--
join :: Int -> Array (a :: *) -> Array a -> Array a
-- | Join many Arrays together along a specified dimension
--
--
--
--
-- >>> joinMany 0 [1,2,3]
-- ArrayFire Array
-- [3 1 1 1]
-- 1.0000 2.0000 3.0000
--
joinMany :: Int -> [Array a] -> Array a
-- | Tiles an Array according to specified dimensions
--
--
-- >>> tile @Double (scalar 22.0) [5,5]
-- ArrayFire Array
-- [5 5 1 1]
-- 22.0000 22.0000 22.0000 22.0000 22.0000
-- 22.0000 22.0000 22.0000 22.0000 22.0000
-- 22.0000 22.0000 22.0000 22.0000 22.0000
-- 22.0000 22.0000 22.0000 22.0000 22.0000
-- 22.0000 22.0000 22.0000 22.0000 22.0000
--
tile :: Array (a :: *) -> [Int] -> Array a
-- | Reorders an Array according to newly specified dimensions
--
--
--
--
-- >>> reorder @Double (scalar 22.0) [5,5]
-- ArrayFire Array
-- [5 5 1 1]
-- 22.0000 22.0000 22.0000 22.0000 22.0000
-- 22.0000 22.0000 22.0000 22.0000 22.0000
-- 22.0000 22.0000 22.0000 22.0000 22.0000
-- 22.0000 22.0000 22.0000 22.0000 22.0000
-- 22.0000 22.0000 22.0000 22.0000 22.0000
--
reorder :: Array (a :: *) -> [Int] -> Array a
-- | Shift elements in an Array along a specified dimension (elements will
-- wrap).
--
--
-- >>> shift (vector @Double 4 [1..]) 2 0 0 0
-- ArrayFire Array
-- [4 1 1 1]
-- 3.0000
-- 4.0000
-- 1.0000
-- 2.0000
--
shift :: Array (a :: *) -> Int -> Int -> Int -> Int -> Array a
-- | Modify dimensions of array
--
--
-- >>> moddims (vector @Double 3 [1..]) [1,3]
-- ArrayFire Array
-- [1 3 1 1]
-- 1.0000 2.0000 3.0000
--
moddims :: forall a. Array (a :: *) -> [Int] -> Array a
-- | Flatten an Array into a single dimension
--
--
-- >>> flat (matrix @Double (2,2) [[1..],[1..]])
-- ArrayFire Array
-- [4 1 1 1]
-- 1.0000
-- 2.0000
-- 1.0000
-- 2.0000
--
--
--
-- >>> flat $ cube @Int (2,2,2) [[[1,1],[1,1]],[[1,1],[1,1]]]
-- ArrayFire Array
-- [8 1 1 1]
-- 1
-- 1
-- 1
-- 1
-- 1
-- 1
-- 1
-- 1
--
flat :: Array a -> Array a
-- | Flip the values of an Array along a specified dimension
--
--
-- >>> matrix @Double (2,2) [[2,2],[3,3]]
-- ArrayFire Array
-- [2 2 1 1]
-- 2.0000 3.0000
-- 2.0000 3.0000
--
--
--
-- >>> A.flip (matrix @Double (2,2) [[2,2],[3,3]]) 1
-- ArrayFire Array
-- [2 2 1 1]
-- 3.0000 2.0000
-- 3.0000 2.0000
--
flip :: Array a -> Int -> Array a
-- | Create a lower triangular matrix from input array.
--
--
-- >>> lower (constant [2,2] 10 :: Array Double) True
-- ArrayFire Array
-- [2 2 1 1]
-- 1.0000 0.0000
-- 10.0000 1.0000
--
lower :: Array a -> Bool -> Array a
-- | Create an upper triangular matrix from input array.
--
--
-- >>> upper (constant [2,2] 10 :: Array Double) True
-- ArrayFire Array
-- [2 2 1 1]
-- 1.0000 10.0000
-- 0.0000 1.0000
--
upper :: Array a -> Bool -> Array a
-- | Selects elements from two arrays based on the values of a binary
-- conditional array.
--
--
-- >>> cond = vector @CBool 5 [1,0,1,0,1]
--
-- >>> arr1 = vector @Double 5 (repeat 1)
--
-- >>> arr2 = vector @Double 5 (repeat 2)
--
-- >>> select cond arr1 arr2
-- ArrayFire Array
-- [5 1 1 1]
-- 1.0000
-- 2.0000
-- 1.0000
-- 2.0000
-- 1.0000
--
select :: Array CBool -> Array a -> Array a -> Array a
-- | Selects elements from two arrays based on the values of a binary
-- conditional array.
--
--
-- http://arrayfire.org/docs/group__data__func__select.htm#gab6886120d0bac4717276910e468bbe88
--
--
-- >>> cond = vector @CBool 5 [1,0,1,0,1]
--
-- >>> arr1 = vector @Double 5 (repeat 1)
--
-- >>> x = 99
--
-- >>> selectScalarR cond arr1 x
-- ArrayFire Array
-- [5 1 1 1]
-- 1.0000
-- 99.0000
-- 1.0000
-- 99.0000
-- 1.0000
--
selectScalarR :: Array CBool -> Array a -> Double -> Array a
-- | Selects elements from two arrays based on the values of a binary
-- conditional array.
--
-- ArrayFire Docs
--
--
-- >>> cond = vector @CBool 5 [1,0,1,0,1]
--
-- >>> arr1 = vector @Double 5 (repeat 1)
--
-- >>> x = 99
--
-- >>> selectScalarL cond x arr1
-- ArrayFire Array
-- [5 1 1 1]
-- 99.0000
-- 1.0000
-- 99.0000
-- 1.0000
-- 99.0000
--
selectScalarL :: Array CBool -> Double -> Array a -> Array a
-- | Functions for aggregation, manipulation of Array
--
--
-- module Main where
--
-- import qualified ArrayFire as A
--
-- main :: IO ()
-- main = print $ A.sum (A.vector @Double 10 [1..]) 0
-- -- ArrayFire Array
-- -- [1 1 1 1]
-- -- 55.0000
--
module ArrayFire.Algorithm
-- | Sum all of the elements in Array along the specified dimension
--
--
-- >>> A.sum (A.vector @Double 10 [1..]) 0
-- ArrayFire Array
-- [1 1 1 1]
-- 55.0000
--
--
--
-- >>> A.sum (A.matrix @Double (10,10) $ replicate 10 [1..]) 1
-- ArrayFire Array
-- [10 1 1 1]
-- 10.0000
-- 20.0000
-- 30.0000
-- 40.0000
-- 50.0000
-- 60.0000
-- 70.0000
-- 80.0000
-- 90.0000
-- 100.0000
--
sum :: AFType a => Array a -> Int -> Array a
-- | Sum all of the elements in Array along the specified dimension,
-- using a default value for NaN
--
--
-- >>> A.sumNaN (A.vector @Double 10 [1..]) 0 0.0
-- ArrayFire Array
-- [1 1 1 1]
-- 55.0000
--
sumNaN :: (Fractional a, AFType a) => Array a -> Int -> Double -> Array a
-- | Product all of the elements in Array along the specified
-- dimension
--
--
-- >>> A.product (A.vector @Double 10 [1..]) 0
-- ArrayFire Array
-- [1 1 1 1]
-- 3628800.0000
--
product :: AFType a => Array a -> Int -> Array a
-- | Product all of the elements in Array along the specified
-- dimension, using a default value for NaN
--
--
-- >>> A.productNaN (A.vector @Double 10 [1..]) 0 0.0
-- ArrayFire Array
-- [1 1 1 1]
-- 3628800.0000
--
productNaN :: (AFType a, Fractional a) => Array a -> Int -> Double -> Array a
-- | Take the minimum of an Array along a specific dimension
--
--
-- >>> A.min (A.vector @Double 10 [1..]) 0
-- ArrayFire Array
-- [1 1 1 1]
-- 1.0000
--
min :: AFType a => Array a -> Int -> Array a
-- | Take the maximum of an Array along a specific dimension
--
--
-- >>> A.max (A.vector @Double 10 [1..]) 0
-- ArrayFire Array
-- [1 1 1 1]
-- 10.0000
--
max :: AFType a => Array a -> Int -> Array a
-- | Find if all elements in an Array are True along a
-- dimension
--
--
-- >>> A.allTrue (A.vector @CBool 10 (repeat 0)) 0
-- ArrayFire Array
-- [1 1 1 1]
-- 0
--
allTrue :: forall a. AFType a => Array a -> Int -> Array a
-- | Find if any elements in an Array are True along a
-- dimension
--
--
-- >>> A.anyTrue (A.vector @CBool 10 (repeat 0)) 0
-- ArrayFire Array
-- [1 1 1 1]
-- 0
--
anyTrue :: forall a. AFType a => Array a -> Int -> Array a
-- | Count elements in an Array along a dimension
--
--
-- >>> A.count (A.vector @Double 10 [1..]) 0
-- ArrayFire Array
-- [1 1 1 1]
-- 10
--
count :: forall a. AFType a => Array a -> Int -> Array Int
-- | Sum all elements in an Array along all dimensions
--
--
-- >>> A.sumAll (A.vector @Double 10 [1..])
-- (55.0,0.0)
--
sumAll :: AFType a => Array a -> (Double, Double)
-- | Sum all elements in an Array along all dimensions, using a
-- default value for NaN
--
--
-- >>> A.sumNaNAll (A.vector @Double 10 [1..]) 0.0
-- (55.0,0.0)
--
sumNaNAll :: (AFType a, Fractional a) => Array a -> Double -> (Double, Double)
-- | Product all elements in an Array along all dimensions, using a
-- default value for NaN
--
--
-- >>> A.productAll (A.vector @Double 10 [1..])
-- (3628800.0,0.0)
--
productAll :: AFType a => Array a -> (Double, Double)
-- | Product all elements in an Array along all dimensions, using a
-- default value for NaN
--
--
-- >>> A.productNaNAll (A.vector @Double 10 [1..]) 1.0
-- (3628800.0,0.0)
--
productNaNAll :: (AFType a, Fractional a) => Array a -> Double -> (Double, Double)
-- | Take the minimum across all elements along all dimensions in
-- Array
--
--
-- >>> A.minAll (A.vector @Double 10 [1..])
-- (1.0,0.0)
--
minAll :: AFType a => Array a -> (Double, Double)
-- | Take the maximum across all elements along all dimensions in
-- Array
--
--
-- >>> A.maxAll (A.vector @Double 10 [1..])
-- (10.0,0.0)
--
maxAll :: AFType a => Array a -> (Double, Double)
-- | Decide if all elements along all dimensions in Array are True
--
--
-- >>> A.allTrueAll (A.vector @CBool 10 (repeat 1))
-- (1.0, 0.0)
--
allTrueAll :: AFType a => Array a -> (Double, Double)
-- | Decide if any elements along all dimensions in Array are True
--
--
-- >>> A.anyTrueAll $ A.vector @CBool 10 (repeat 0)
-- (0.0,0.0)
--
anyTrueAll :: AFType a => Array a -> (Double, Double)
-- | Count all elements along all dimensions in Array
--
--
-- >>> A.countAll (A.matrix @Double (100,100) (replicate 100 [1..]))
-- (10000.0,0.0)
--
countAll :: AFType a => Array a -> (Double, Double)
-- | Find the minimum element along a specified dimension in Array
--
--
-- >>> A.imin (A.vector @Double 10 [1..]) 0
-- (ArrayFire Array
-- [1 1 1 1]
-- 1.0000
-- ,ArrayFire Array
-- [1 1 1 1]
-- 0
-- )
--
imin :: AFType a => Array a -> Int -> (Array a, Array a)
-- | Find the maximum element along a specified dimension in Array
--
--
-- >>> A.imax (A.vector @Double 10 [1..]) 0
-- (ArrayFire Array
-- [1 1 1 1]
-- 10.0000
-- ,ArrayFire Array
-- [1 1 1 1]
-- 9
-- )
--
imax :: AFType a => Array a -> Int -> (Array a, Array a)
-- | Find the minimum element along all dimensions in Array
--
--
-- >>> A.iminAll (A.vector @Double 10 [1..])
-- (1.0,0.0,0)
--
iminAll :: AFType a => Array a -> (Double, Double, Int)
-- | Find the maximum element along all dimensions in Array
--
--
-- >>> A.imaxAll (A.vector @Double 10 [1..])
-- (10.0,0.0,9)
--
imaxAll :: AFType a => Array a -> (Double, Double, Int)
-- | Calculate sum of Array across specified dimension
--
--
-- >>> A.accum (A.vector @Double 10 [1..]) 0
-- ArrayFire Array
-- [10 1 1 1]
-- 1.0000
-- 3.0000
-- 6.0000
-- 10.0000
-- 15.0000
-- 21.0000
-- 28.0000
-- 36.0000
-- 45.0000
-- 55.0000
--
accum :: AFType a => Array a -> Int -> Array a
-- | Scan elements of an Array across a dimension, using a
-- BinaryOp, specifying inclusivity.
--
--
-- >>> A.scan (A.vector @Double 10 [1..]) 0 Add True
-- ArrayFire Array
-- [10 1 1 1]
-- 1.0000
-- 3.0000
-- 6.0000
-- 10.0000
-- 15.0000
-- 21.0000
-- 28.0000
-- 36.0000
-- 45.0000
-- 55.0000
--
scan :: AFType a => Array a -> Int -> BinaryOp -> Bool -> Array a
-- | Scan elements of an Array across a dimension, by key, using a
-- BinaryOp, specifying inclusivity.
--
--
-- >>> A.scanByKey (A.vector @Int 7 [2..]) (A.vector @Int 10 [1..]) 1 Add True
-- ArrayFire Array
-- [10 1 1 1]
-- 1
-- 2
-- 3
-- 4
-- 5
-- 6
-- 7
-- 8
-- 9
-- 10
--
scanByKey :: (AFType a, AFType k) => Array k -> Array a -> Int -> BinaryOp -> Bool -> Array a
-- | Find indices where input Array is non zero
--
--
-- >>> A.where' (A.vector @Double 10 (repeat 0))
-- ArrayFire Array
-- [0 1 1 1]
-- <empty>
--
where' :: AFType a => Array a -> Array a
-- | First order numerical difference along specified dimension.
--
--
-- >>> A.diff1 (A.vector @Double 4 [10,35,65,95]) 0
-- ArrayFire Array
-- [3 1 1 1]
-- 25.0000
-- 30.0000
-- 30.0000
--
diff1 :: AFType a => Array a -> Int -> Array a
-- | Second order numerical difference along specified dimension.
--
--
-- >>> A.diff2 (A.vector @Double 5 [1.0,20,55,89,44]) 0
-- ArrayFire Array
-- [3 1 1 1]
-- 16.0000
-- -1.0000
-- -79.0000
--
diff2 :: AFType a => Array a -> Int -> Array a
-- | Sort an Array along a specified dimension, specifying ordering of
-- results (ascending / descending)
--
--
-- >>> A.sort (A.vector @Double 4 [ 2,4,3,1 ]) 0 True
-- ArrayFire Array
-- [4 1 1 1]
-- 1.0000
-- 2.0000
-- 3.0000
-- 4.0000
--
--
--
-- >>> A.sort (A.vector @Double 4 [ 2,4,3,1 ]) 0 False
-- ArrayFire Array
-- [4 1 1 1]
-- 4.0000
-- 3.0000
-- 2.0000
-- 1.0000
--
sort :: AFType a => Array a -> Int -> Bool -> Array a
-- | Sort an Array along a specified dimension, specifying ordering
-- of results (ascending / descending), returns indices of sorted results
--
--
-- >>> A.sortIndex (A.vector @Double 4 [3,2,1,4]) 0 True
-- (ArrayFire Array
-- [4 1 1 1]
-- 1.0000
-- 2.0000
-- 3.0000
-- 4.0000
-- ,ArrayFire Array
-- [4 1 1 1]
-- 2
-- 1
-- 0
-- 3
-- )
--
sortIndex :: AFType a => Array a -> Int -> Bool -> (Array a, Array a)
-- | Sort an Array along a specified dimension by keys, specifying
-- ordering of results (ascending / descending)
--
--
-- >>> A.sortByKey (A.vector @Double 4 [2,1,4,3]) (A.vector @Double 4 [10,9,8,7]) 0 True
-- (ArrayFire Array
-- [4 1 1 1]
-- 1.0000
-- 2.0000
-- 3.0000
-- 4.0000
-- ,ArrayFire Array
-- [4 1 1 1]
-- 9.0000
-- 10.0000
-- 7.0000
-- 8.0000
-- )
--
sortByKey :: AFType a => Array a -> Array a -> Int -> Bool -> (Array a, Array a)
-- | Finds the unique values in an Array, specifying if sorting
-- should occur.
--
--
-- >>> A.setUnique (A.vector @Double 2 [1.0,1.0]) True
-- ArrayFire Array
-- [1 1 1 1]
-- 1.0000
--
setUnique :: AFType a => Array a -> Bool -> Array a
-- | Takes the union of two Arrays, specifying if setUnique
-- should be called first.
--
--
-- >>> A.setUnion (A.vector @Double 3 [3,4,5]) (A.vector @Double 3 [1,2,3]) True
-- ArrayFire Array
-- [5 1 1 1]
-- 1.0000
-- 2.0000
-- 3.0000
-- 4.0000
-- 5.0000
--
setUnion :: AFType a => Array a -> Array a -> Bool -> Array a
-- | Takes the intersection of two Arrays, specifying if
-- setUnique should be called first.
--
--
-- >>> A.setIntersect (A.vector @Double 3 [3,4,5]) (A.vector @Double 3 [1,2,3]) True
-- ArrayFire Array
-- [1 1 1 1]
-- 3.0000
--
setIntersect :: AFType a => Array a -> Array a -> Bool -> Array a
-- | Various utilities for working with the ArrayFire C library
--
--
-- 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
--
module ArrayFire.Util
-- | Retrieve version for ArrayFire API
--
--
-- >>> print =<< getVersion
--
--
--
-- (3.6.4)
--
getVersion :: IO (Int, Int, Int)
-- | Prints array to stdout
--
--
-- >>> printArray (constant @Double [1] 1)
--
--
--
-- ArrayFire Array
-- [ 1 1 1 1 ]
-- 1.0
--
printArray :: Array a -> IO ()
-- | Gets git revision of ArrayFire
--
--
-- >>> putStrLn =<< getRevision
--
--
--
-- 1b8030c5
--
getRevision :: IO String
-- | Prints Array with error codes
--
--
-- >>> printArrayGen "test" (constant @Double [1] 1) 2
--
--
--
-- ArrayFire Array
-- [ 1 1 1 1 ]
-- 1.00
--
printArrayGen :: String -> Array a -> Int -> IO ()
-- | Saves Array to disk
--
-- Save an array to a binary file. The saveArray and readArray
-- functions are designed to provide store and read access to arrays
-- using files written to disk.
-- http://arrayfire.org/docs/group__stream__func__save.htm
--
--
-- >>> saveArray "my array" (constant @Double [1] 1) "array.file" True
--
--
--
-- 0
--
saveArray :: String -> Array a -> FilePath -> Bool -> IO Int
-- | Reads Array by index
--
-- The saveArray and readArray functions are designed to provide
-- store and read access to arrays using files written to disk.
-- http://arrayfire.org/docs/group__stream__func__save.htm
--
--
-- >>> readArrayIndex "array.file" 0
--
--
--
-- ArrayFire Array
-- [ 1 1 1 1 ]
-- 10.0000
--
readArrayIndex :: FilePath -> Int -> IO (Array a)
-- | Reads Array by key
--
--
-- >>> readArrayKey "array.file" "my array"
--
--
--
-- ArrayFire Array
-- [ 1 1 1 1 ]
-- 10.0000
--
readArrayKey :: FilePath -> String -> IO (Array a)
-- | Reads Array, checks if a key exists in the specified file
--
-- When reading by key, it may be a good idea to run this function first
-- to check for the key and then call the readArray using the index.
-- http://arrayfire.org/docs/group__stream__func__read.htm#ga31522b71beee2b1c06d49b5aa65a5c6f
--
--
-- >>> readArrayCheck "array.file" "my array"
--
--
--
-- 0
--
readArrayKeyCheck :: FilePath -> String -> IO Int
-- | Convert ArrayFire Array to String, used for Show
-- instance.
--
--
-- >>> putStrLn $ arrayString (constant @Double 10 [1,1,1,1])
--
--
--
-- ArrayFire Array
-- [ 1 1 1 1 ]
-- 10.0000
--
arrayString :: Array a -> String
-- | Convert ArrayFire Array to String
--
--
-- >>> print (constant @Double 10 [1,1,1,1]) 4 False
--
--
--
-- ArrayFire Array
-- [ 1 1 1 1 ]
-- 10.0000
--
arrayToString :: String -> Array a -> Int -> Bool -> String
-- | Retrieve size of ArrayFire data type
--
--
-- >>> getSizeOf (Proxy @ Double)
--
--
--
-- 8
--
getSizeOf :: forall a. AFType a => Proxy a -> Int
-- | Functions for constructing and querying metadata from Array
--
--
-- module Main where
--
-- import ArrayFire
--
-- main :: IO ()
-- main = print (matrix @Double (2,2) [ [1..], [1..] ])
--
--
--
-- ArrayFire Array
-- [2 2 1 1]
-- 1.0000 1.0000
-- 2.0000 2.0000
--
module ArrayFire.Array
-- | Smart constructor for creating a scalar Array
--
--
-- >>> scalar @Double 2.0
-- ArrayFire Array
-- [1 1 1 1]
-- 2.0000
--
scalar :: AFType a => a -> Array a
-- | Smart constructor for creating a vector Array
--
--
-- >>> 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
--
vector :: AFType a => Int -> [a] -> Array a
-- | Smart constructor for creating a matrix Array
--
--
-- >>> A.matrix @Double (3,2) [[1,2,3],[4,5,6]]
-- ArrayFire Array
-- [3 2 1 1]
-- 1.0000 4.0000
-- 2.0000 5.0000
-- 3.0000 6.0000
--
matrix :: AFType a => (Int, Int) -> [[a]] -> Array a
-- | Smart constructor for creating a cubic Array
--
--
-- >>> cube @Double (2,2,2) [[[2,2],[2,2]],[[2,2],[2,2]]]
--
--
--
-- ArrayFire Array
-- [2 2 2 1]
-- 2.0000 2.0000
-- 2.0000 2.0000
--
-- 2.0000 2.0000
-- 2.0000 2.0000
--
cube :: AFType a => (Int, Int, Int) -> [[[a]]] -> Array a
-- | Smart constructor for creating a tensor Array
--
--
-- >>> 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
-- 2.0000 2.0000
--
-- 2.0000 2.0000
-- 2.0000 2.0000
--
--
-- 2.0000 2.0000
-- 2.0000 2.0000
--
-- 2.0000 2.0000
-- 2.0000 2.0000
--
tensor :: AFType a => (Int, Int, Int, Int) -> [[[[a]]]] -> Array a
-- | Internal function for Array construction
--
--
-- >>> mkArray @Double [10] [1.0 .. 10.0]
-- 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
--
mkArray :: forall array. AFType array => [Int] -> [array] -> Array array
-- | Copies an Array to a new Array
--
--
-- >>> copyArray (scalar @Double 10)
-- ArrayFire Array
-- [1 1 1 1]
-- 10.0000
--
copyArray :: AFType a => Array a -> Array a
-- | Retains an Array, increases reference count
--
--
-- >>> retainArray (scalar @Double 10)
-- ArrayFire Array
-- [1 1 1 1]
-- 10.0000
--
retainArray :: AFType a => Array a -> Array a
-- | Retrieves Array reference count
--
--
-- >>> initialArray = scalar @Double 10
--
-- >>> retainedArray = retain initialArray
--
-- >>> getDataRefCount retainedArray
-- 2
--
getDataRefCount :: AFType a => Array a -> Int
-- | Should manual evaluation occur
--
--
-- >>> setManualEvalFlag True
-- ()
--
setManualEvalFlag :: Bool -> IO ()
-- | Retrieve manual evaluation status
--
--
-- >>> setManualEvalFlag False
--
-- >>> getManualEvalFlag
-- False
--
getManualEvalFlag :: IO Bool
-- | Retrieve element count
--
--
-- >>> getElements (vector @Double 10 [1..])
-- 10
--
getElements :: AFType a => Array a -> Int
-- | Retrieve type of Array
--
--
-- >>> getType (vector @Double 10 [1..])
-- F64
--
getType :: AFType a => Array a -> AFDType
-- | Retrieves dimensions of Array
--
--
-- >>> getDims (vector @Double 10 [1..])
-- (10,1,1,1)
--
getDims :: AFType a => Array a -> (Int, Int, Int, Int)
-- | Retrieves number of dimensions in Array
--
--
-- >>> getNumDims (matrix @Double (2,2) [[1..],[1..]])
-- 2
--
getNumDims :: AFType a => Array a -> Int
-- | Checks if an Array is empty
--
--
-- >>> isEmpty (matrix @Double (2,2) [[1..],[1..]])
-- False
--
isEmpty :: AFType a => Array a -> Bool
-- | Checks if an Array is a scalar (contains only one element)
--
--
-- >>> isScalar (matrix @Double (2,2) [[1..],[1..]])
-- False
--
-- >>> isScalar (1.0 :: Array Double)
-- True
--
isScalar :: AFType a => Array a -> Bool
-- | Checks if an Array is row-oriented
--
--
-- >>> isRow (matrix @Double (2,2) [[1..],[1..]])
-- False
--
isRow :: AFType a => Array a -> Bool
-- | Checks if an Array is a column-oriented
--
--
-- >>> isColumn (vector @Double 10 [1..])
-- True
--
isColumn :: AFType a => Array a -> Bool
-- | Checks if an Array is a vector
--
--
-- >>> isVector (vector @Double 10 [1..])
-- True
--
-- >>> isVector (1.0 :: Array Double)
-- False
--
isVector :: AFType a => Array a -> Bool
-- | Checks if an Array is a Complex
--
--
-- >>> isComplex (scalar (1.0 :+ 1.0) :: Array (Complex Double))
-- True
--
isComplex :: AFType a => Array a -> Bool
-- | Checks if an Array is Real
--
--
-- >>> isReal (scalar 1.0 :: Array Double)
-- True
--
isReal :: AFType a => Array a -> Bool
-- | Checks if an Array is Double
--
--
-- >>> isDouble (scalar 1.0 :: Array Double)
-- True
--
isDouble :: AFType a => Array a -> Bool
-- | Checks if an Array is Float
--
--
-- >>> isSingle (scalar 1.0 :: Array Float)
-- True
--
isSingle :: AFType a => Array a -> Bool
-- | Checks if an Array is Double, Float, Complex
-- Double, or Complex Float
--
--
-- >>> isRealFloating (scalar 1.0 :: Array Double)
-- True
--
isRealFloating :: AFType a => Array a -> Bool
-- | Checks if an Array is Double or Float
--
--
-- >>> isFloating (scalar 1.0 :: Array Double)
-- True
--
isFloating :: AFType a => Array a -> Bool
-- | Checks if an Array is of type Int16, Int32, or Int64
--
--
-- >>> isInteger (scalar 1 :: Array Int16)
-- True
--
isInteger :: AFType a => Array a -> Bool
-- | Checks if an Array is of type CBool
--
--
-- >>> isBool (scalar 1 :: Array CBool)
-- True
--
isBool :: AFType a => Array a -> Bool
-- | Checks if an Array is sparse
--
--
-- >>> isSparse (scalar 1 :: Array Double)
-- False
--
isSparse :: AFType a => Array a -> Bool
-- | Converts an Array to a Storable Vector
--
--
-- >>> toVector (vector @Double 10 [1..])
-- [1.0,2.0,3.0,4.0,5.0,6.0,7.0,8.0,9.0,10.0]
--
toVector :: forall a. AFType a => Array a -> Vector a
-- | Converts an Array to [a]
--
--
-- >>> toList (vector @Double 10 [1..])
-- [1.0,2.0,3.0,4.0,5.0,6.0,7.0,8.0,9.0,10.0]
--
toList :: forall a. AFType a => Array a -> [a]
-- | Retrieves single scalar value from an Array
--
--
-- >>> getScalar (scalar @Double 22.0) :: Double
-- 22.0
--
getScalar :: forall a b. (Storable a, AFType b) => Array b -> a
-- | Statistics API. Example of finding the top k elements along with their
-- indices from an Array
--
--
-- >>> let (vals,indexes) = topk ( vector @Double 10 [1..] ) 3 TopKDefault
-- >>> vals
--
-- ArrayFire Array
-- [3 1 1 1]
-- 10.0000
-- 9.0000
-- 8.0000
--
-- >>> indexes
--
-- ArrayFire Array
-- [3 1 1 1]
-- 9
-- 8
-- 7
--
module ArrayFire.Statistics
-- | Calculates mean of Array along user-specified dimension.
--
--
-- >>> mean ( vector @Int 10 [1..] ) 0
-- ArrayFire Array
-- [1 1 1 1]
-- 5.5000
--
mean :: AFType a => Array a -> Int -> Array a
-- | Calculates meanWeighted of Array along user-specified
-- dimension.
--
--
-- >>> meanWeighted (vector @Double 10 [1..10]) (vector @Double 10 [1..10]) 0
-- ArrayFire Array
-- [1 1 1 1]
-- 7.0000
--
meanWeighted :: AFType a => Array a -> Array a -> Int -> Array a
-- | Calculates variance of Array along user-specified
-- dimension.
--
--
-- >>> var (vector @Double 8 [1..8]) False 0
-- ArrayFire Array
-- [1 1 1 1]
-- 6.0000
--
var :: AFType a => Array a -> Bool -> Int -> Array a
-- | Calculates varWeighted of Array along user-specified
-- dimension.
--
--
-- >>> varWeighted ( vector @Double 10 [1..] ) ( vector @Double 10 [1..] ) 0
-- ArrayFire Array
-- [1 1 1 1]
-- 6.0000
--
varWeighted :: AFType a => Array a -> Array a -> Int -> Array a
-- | Calculates stdev of Array along user-specified
-- dimension.
--
--
-- >>> stdev (vector @Double 10 (cycle [1,-1])) 0
-- ArrayFire Array
-- [1 1 1 1]
-- 1.0000
--
stdev :: AFType a => Array a -> Int -> Array a
-- | Calculates covariance of two Arrays with a bias
-- specifier.
--
--
-- >>> cov (vector @Double 10 (repeat 1)) (vector @Double 10 (repeat 1)) False
-- ArrayFire Array
-- [1 1 1 1]
-- 0.0000
--
cov :: AFType a => Array a -> Array a -> Bool -> Array a
-- | Calculates median of Array along user-specified
-- dimension.
--
--
-- >>> median ( vector @Double 10 [1..] ) 0
-- ArrayFire Array
-- [1 1 1 1]
-- 5.5000
--
median :: AFType a => Array a -> Int -> Array a
-- | Calculates mean of all elements in an Array
--
--
-- >>> meanAll $ matrix @Double (2,2) [[1,2],[4,5]]
-- (3.0,2.232709401e-314)
--
meanAll :: AFType a => Array a -> (Double, Double)
-- | Calculates weighted mean of all elements in an Array
--
--
-- >>> meanAllWeighted (matrix @Double (2,2) [[1,2],[3,4]]) (matrix @Double (2,2) [[1,2],[3,4]])
-- (3.0,1.400743288453e-312)
--
meanAllWeighted :: AFType a => Array a -> Array a -> (Double, Double)
-- | Calculates variance of all elements in an Array
--
--
-- >>> varAll (vector @Double 10 (repeat 10)) False
-- (0.0,1.4013073623e-312)
--
varAll :: AFType a => Array a -> Bool -> (Double, Double)
-- | Calculates weighted variance of all elements in an Array
--
--
-- >>> varAllWeighted ( vector @Double 10 [1..] ) ( vector @Double 10 [1..] )
-- (6.0,2.1941097984e-314)
--
varAllWeighted :: AFType a => Array a -> Array a -> (Double, Double)
-- | Calculates standard deviation of all elements in an Array
--
--
-- >>> stdevAll (vector @Double 10 (repeat 10))
-- (0.0,2.190573324e-314)
--
stdevAll :: AFType a => Array a -> (Double, Double)
-- | Calculates median of all elements in an Array
--
--
-- >>> medianAll (vector @Double 10 (repeat 10))
-- (10.0,2.1961564713e-314)
--
medianAll :: (AFType a, Fractional a) => Array a -> (Double, Double)
-- | This algorithm returns Pearson product-moment correlation coefficient.
-- https://en.wikipedia.org/wiki/Pearson_correlation_coefficient
--
--
-- >>> corrCoef ( vector @Int 10 [1..] ) ( vector @Int 10 [10,9..] )
-- (-1.0,2.1904819737e-314)
--
corrCoef :: AFType a => Array a -> Array a -> (Double, Double)
-- | This function returns the top k values along a given dimension of the
-- input array.
--
--
-- >>> let (vals,indexes) = topk ( vector @Double 10 [1..] ) 3 TopKDefault
-- >>> indexes
--
-- ArrayFire Array
-- [3 1 1 1]
-- 9
-- 8
-- 7
--
-- >>> vals
-- ArrayFire Array
-- [3 1 1 1]
-- 10.0000
-- 9.0000
-- 8.0000
--
--
-- The indices along with their values are returned. If the input is a
-- multi-dimensional array, the indices will be the index of the value in
-- that dimension. Order of duplicate values are not preserved. This
-- function is optimized for small values of k. This function performs
-- the operation across all dimensions of the input array. This function
-- is optimized for small values of k. The order of the returned keys may
-- not be in the same order as the appear in the input array
topk :: AFType a => Array a -> Int -> TopK -> (Array a, Array a)
-- | Functions pertaining to Computer Vision.
module ArrayFire.Vision
-- | FAST feature detectors
--
-- ArrayFire Docs
--
-- A circle of radius 3 pixels, translating into a total of 16 pixels, is
-- checked for sequential segments of pixels much brighter or much darker
-- than the central one. For a pixel p to be considered a feature, there
-- must exist a sequential segment of arc_length pixels in the circle
-- around it such that all are greather than (p + thr) or smaller than (p
-- - thr). After all features in the image are detected, if nonmax is
-- true, the non-maximal suppression is applied, checking all detected
-- features and the features detected in its 8-neighborhood and discard
-- it if its score is non maximal.
fast :: Array a -> Float -> Int -> Bool -> Float -> Int -> Features
-- | Harris corner detection
--
-- ArrayFire Docs
--
-- Harris corner detector.
harris :: Array a -> Int -> Float -> Float -> Int -> Float -> Features
-- | ORB Feature descriptor
--
-- ArrayFire Docs
--
-- Extract ORB descriptors from FAST features that hold higher Harris
-- responses. FAST does not compute orientation, thus, orientation of
-- features is calculated using the intensity centroid. As FAST is also
-- not multi-scale enabled, a multi-scale pyramid is calculated by
-- downsampling the input image multiple times followed by FAST feature
-- detection on each scale.
orb :: Array a -> Float -> Int -> Float -> Int -> Bool -> (Features, Array a)
-- | SIFT feature detector and descriptor extractor.
--
-- ArrayFire Docs
--
-- C Interface for SIFT feature detector and descriptor.
sift :: Array a -> Int -> Float -> Float -> Float -> Bool -> Float -> Float -> (Features, Array a)
-- | SIFT feature detector and descriptor extractor.
--
-- ArrayFire Docs
--
-- C Interface for SIFT feature detector and descriptor.
gloh :: Array a -> Int -> Float -> Float -> Float -> Bool -> Float -> Float -> (Features, Array a)
-- | Hamming Matcher
--
-- ArrayFire Docs
--
-- Calculates Hamming distances between two 2-dimensional arrays
-- containing features, one of the arrays containing the training data
-- and the other the query data. One of the dimensions of the both arrays
-- must be equal among them, identifying the length of each feature. The
-- other dimension indicates the total number of features in each of the
-- training and query arrays. Two 1-dimensional arrays are created as
-- results, one containg the smallest N distances of the query array and
-- another containing the indices of these distances in the training
-- array. The resulting 1-dimensional arrays have length equal to the
-- number of features contained in the query array.
hammingMatcher :: Array a -> Array a -> Int -> Int -> (Array a, Array a)
-- | Nearest Neighbor
--
-- ArrayFire Docs
--
-- Calculates nearest distances between two 2-dimensional arrays
-- containing features based on the type of distance computation chosen.
-- Currently, AF_SAD (sum of absolute differences), AF_SSD (sum of
-- squared differences) and AF_SHD (hamming distance) are supported. One
-- of the arrays containing the training data and the other the query
-- data. One of the dimensions of the both arrays must be equal among
-- them, identifying the length of each feature. The other dimension
-- indicates the total number of features in each of the training and
-- query arrays. Two 1-dimensional arrays are created as results, one
-- containg the smallest N distances of the query array and another
-- containing the indices of these distances in the training array. The
-- resulting 1-dimensional arrays have length equal to the number of
-- features contained in the query array.
nearestNeighbor :: Array a -> Array a -> Int -> Int -> MatchType -> (Array a, Array a)
-- | Nearest Neighbor
--
-- ArrayFire Docs
--
-- C Interface for image template matching.
matchTemplate :: Array a -> Array a -> MatchType -> Array a
-- | SUSAN corner detector.
--
-- ArrayFire Docs
--
-- SUSAN is an acronym standing for Smallest Univalue Segment
-- Assimilating Nucleus. This method places a circular disc over the
-- pixel to be tested (a.k.a nucleus) to compute the corner measure of
-- that corresponding pixel. The region covered by the circular disc is
-- M, and a pixel in this region is represented by m M where m 0 is the
-- nucleus. Every pixel in the region is compared to the nucleus using
-- the following comparison function:
susan :: Array a -> Int -> Float -> Float -> Float -> Int -> Features
-- | Difference of Gaussians.
--
-- ArrayFire Docs
--
-- Given an image, this function computes two different versions of
-- smoothed input image using the difference smoothing parameters and
-- subtracts one from the other and returns the result.
dog :: Array a -> Int -> Int -> Array a
-- | Homography Estimation.
--
-- ArrayFire Docs
--
-- Homography estimation find a perspective transform between two sets of
-- 2D points.
homography :: forall a. AFType a => Array a -> Array a -> Array a -> Array a -> HomographyType -> Float -> Int -> (Int, Array a)
module ArrayFire