arnetheduck/nim-fftr

The fastest Fourier transform in the Rhein (so far). Pure Nim.

nim-fftr's Issues

Inverse FFT seems need divider the FFT points

fftr is an very handy library. I am porting some code from numpy to nim and utilize the fftr libaray.
Forward FFT works well, but IFFT seems not match with numpy.fft.ifft.

After divider fftr result with FFT points, they are match again.

fft(some_complex_seq ,true)/fft_num_of_points => this match with numpy.fft.ifft

Example code fails to compile

Code

import fftr, std/math, std/sequtils

let
  signal = (0..1023).mapIt(complex64(sin(TAU * 0.1 * float64(it))))
  freqs = fft(tmp, false) # False for forward, true for inverse FFT

Error message

Hint: used config file '/home/anon/.choosenim/toolchains/nim-2.0.2/config/nim.cfg' [Conf]
Hint: used config file '/home/anon/.choosenim/toolchains/nim-2.0.2/config/config.nims' [Conf]
......................................................................
/home/anon/Documents/ProgrammingLearning/nim/FFT/fftr.nim(1, 8) Error: module 'fftr' cannot import itself

System Info
--------
OS: Arch Linux x86_64
Host: Oryx Pro (oryp8)
Kernel: 6.6.10-arch1-1
Shell: bash 5.2.21
DE: KDE Plasma 5.27.10
WM: KWin (Wayland)
WM Theme: Breeze
CPU: 11th Gen Intel(R) Core(TM) i7-11800H (16) @ 4.60 GHz
GPU 1: Intel UHD Graphics
GPU 2: NVIDIA GeForce RTX 3070 Mobile / Max-Q
Memory:  31.20 GiB

I am not entirely sure why I am getting the import error message. I installed the package using Nimble.

SciPy example

Testing out your code with a SciPy example and I am getting the incorrect inverse. Am I doing something wrong?

SciPy:

>>> from scipy.fft import fft, ifft
>>> import numpy as np
>>> x = np.array([1.0, 2.0, 1.0, -1.0, 1.5])
>>> y = fft(x)
>>> y
array([ 4.5       +0.j        ,  2.08155948-1.65109876j,
       -1.83155948+1.60822041j, -1.83155948-1.60822041j,
        2.08155948+1.65109876j])
>>> yinv = ifft(y)
>>> yinv
array([ 1.0+0.j,  2.0+0.j,  1.0+0.j, -1.0+0.j,  1.5+0.j])

My example:

let input = @[complex64(1.0, 0.0), complex64(2.0, 0.0), complex64(1.0, 0.0), complex64(-1.0, 0.0), complex64(1.5, 0.0)]
let output = fft(input, false)
echo output

let iOutput = fft(output, true)
echo iOutput

Results in:

@[(4.5, -3.608224830031759e-16), (2.081559480312316, -1.651098762732523), (-1.831559480312317, 1.60822040644407), (-1.831559480312316, -1.60822040644407), (2.081559480312317, 1.651098762732523)]

@[(5.0, -8.881784197001252e-16), (10.0, -1.77635683940025e-15), (4.999999999999999, -4.440892098500626e-16), (-4.999999999999999, 8.881784197001252e-16), (7.5, 0.0)]