python列表上的NP.FFT

Question

Could you please advise me on the following: I gather data from an Arduino ADC and store the data in a list on a Raspberry Pi 4 with Python 3. The list is called 'dataList' and contains 1024 10 bits samples. This all works fine: I can reproduce the sampled signal on the Raspberry.

I would like to use the power spectrum of the acquired signal using numpy FFT. I tried the following:

[see below]

This should illustrate what I'm trying to do; however this produces incoherent output. The sampled signal has a frequency of about 300 Hz. I would be very grateful for any hints in the right direction!

def show_FFT(window):
   fft = np.fft.fft (dataList, 1024, -1, None)
   for X_value in range (0,512, 1):
       Y_value = fft ([X_value]
       gfxdraw.pixel (window, X_value, int(abs(Y_value), black)

Answer 1

As you mentioned in your question, you have a data set whith X starting from 0 to... but for numpy.fft.fft you must keep in mind that it is a discrete Fourier transform ( DFT ) which caculate the fft of equaly spaced samples and i must mntion that it must be a symetric range of dataset from -x to x. You can simply try it with a gausian finction and change the parameters as you wish and see what are the results... Since you didn''t give any data set here , I would refer you to a generl case with below code:

import numpy as np
from scipy import interpolate
import matplotlib.pyplot as plt
# create data from dataframes
x = np.random.rand(50) #unequaly spaced measurment
x.sort()
y = np.exp(-x*x) #measured signal

based on the answer here you can resample your data into equaly spaced points by:

f = interpolate.interp1d(x, y)
num = 500
xx = np.linspace(x[0], x[-1], num)
yy = f(xx)
plt.close('all')
plt.plot(x,y,'bo')
plt.plot(xx,yy, 'g.-')
plt.show()

enter image description here then you can make your x data symetric very simply by :

x=xx
y=yy
xsample = x-((x.max()-x.min())/2)
xsample=xsample-(xsample.max()+xsample.min())/2
x=xsample

thne if you try fft you will get the corect results as:

ysample =yy
ysample_fft = np.fft.fftshift(np.abs(np.fft.fft(ysample/ysample.max()))) / 
np.sqrt(len(ysample))
plt.plot(xsample,ysample_fft/ysample_fft.max(),'b--')
plt.show()

enter image description here