Data.Array.Accelerate.Math.PseudoWigner

Computation of a PsudoWigner transform using the accelerate-fft library.

This module uses the accelerate-fft library. And the base implementation of fft uses a naive divide-and-conquer fft implementation whose absolute performance is appalling. It also requires that you know on the Haskell side the size of the data being transformed, and that this is a power-of-two in each dimension.

For performance, compile accelerate-fft against the foreign library bindings (using any number of '-fllvm-ptx', and '-fllvm-cpu' for the accelerate-llvm-ptx, and accelerate-llvm-native backends, respectively), which have none of the above restrictions. Both this flags are enabled by default.

Documentation

pWignerVille

Arguments

:: (RealFloat e, IsFloating e, FromIntegral Int e, Elt e, sh ~ DIM2)

=> sh

shape of the data array. It is ignored, when compiled with Native or PTX backend.

-> Acc (Array DIM1 e)

Smoothing window. Length of it must be odd.

-> Acc (Array DIM1 (Complex e))

Data array

-> Acc (Array DIM2 e)

Pseudo Wigner-ville distribution. It takes 1D array of complex floating numbers, window and returns 2D array of real numbers. Columns of result array represents time and rows - frequency. Frequency range is from 0 to n/4, where n is a sampling frequency.