Data.Array.Accelerate.Math.FFT

Computation of a Discrete Fourier Transform using the Cooley-Tuckey algorithm. The time complexity is O(n log n) in the size of the input.

This uses a naïve divide-and-conquer algorithm whose absolute performance is appalling.

Documentation

data Mode

Constructors

Forward

Reverse

Inverse

Instances

Eq Mode

Show Mode

fft1D :: (Elt e, IsFloating e) => Mode -> Vector (Complex e) -> Acc (Vector (Complex e))

fft1D' :: forall e. (Elt e, IsFloating e) => Mode -> Int -> Acc (Vector (Complex e)) -> Acc (Vector (Complex e))

fft2D :: (Elt e, IsFloating e) => Mode -> Array DIM2 (Complex e) -> Acc (Array DIM2 (Complex e))

fft2D'

Arguments

:: forall e . (Elt e, IsFloating e)

=> Mode

-> Int

width

-> Int

height

-> Acc (Array DIM2 (Complex e))

-> Acc (Array DIM2 (Complex e))

fft3D :: (Elt e, IsFloating e) => Mode -> Array DIM3 (Complex e) -> Acc (Array DIM3 (Complex e))

fft3D'

Arguments

:: forall e . (Elt e, IsFloating e)

=> Mode

-> Int

width

-> Int

height

-> Int

depth

-> Acc (Array DIM3 (Complex e))

-> Acc (Array DIM3 (Complex e))

fft :: forall sh e. (Slice sh, Shape sh, IsFloating e, Elt e) => e -> sh -> Int -> Acc (Array (sh :. Int) (Complex e)) -> Acc (Array (sh :. Int) (Complex e))