How to do the FFT transform and show the result
井民全, Jing, mqjing@gmail.com
Code
import matplotlib.pyplot as plt import numpy as np from numpy import where from numpy.fft import fft N = 1600 # Define the total number of data points fs = 800.0 # Define the sampling rate dt = 1.0 / fs # Define the sampling interval (sec) t = np.linspace(0.0, N*dt, N) # start=0, stop = N*T, total sample = N s = np.sin(50.0 * 2.0*np.pi*t) + 0.5*np.sin(80.0 * 2.0*np.pi*t) sf = fft(s) # sf = fft(s-s.mean()) # Show the signal fig, (ax0, ax1) = plt.subplots(2, 1) ax0.set_title('Signal') ax0.plot(t, s) fNQ = fs/ 2.0 # Determine Nyquist frequency faxis = np.linspace(0.0, fNQ, N//2) # Construct frequency axis ax1.set_title('FFT') ax1.plot(faxis, np.abs(sf[:N//2])) # ax1.plot(faxis, 2.0/N * np.abs(sf[:N//2])) // amplitude normalization |
Result
