Plotting Magnitude Spectrum Of A Signal Using Python And Matplotlib

Overview:

  • A signal has many components using which it is described.

 

  • A signal has amplitude, phase, frequency, angular frequency, wavelength and a period.

 

  • The Fourier Transform gives the component frequencies that make up the signal. That is, using Fourier Transform any periodic signal can be described as a sum of simple sine waves of different frequencies.

 

  • The Magnitude Spectrum of a signal describes a signal using frequency and amplitude. That is frequency components of a periodic signal are plotted using Frequency Domain - frequencies plotted in X-axis and amplitude plotted in Y-axis.

 

  • The pyplot module of the Python Matplotlib library provides the function magnitude_spectrum() that plots the spectral magnitude representation of a sine wave.

 

  • The Magnitude Spectrum has both a positive frequency component and a negative frequency component. However, the  magnitude_spectrum()function plots both the frequencies together.

 

Example:

# import the numpy and pyplot modules

import numpy as np

import matplotlib.pyplot as plot

 

# Get time values of the signal

time   = np.arange(0, 65, .25);

 

# Get sample points for the discrete signal(which represents a continous signal)

signalAmplitude   = np.sin(time)

 

# plot the signal in time domain

plot.subplot(211)

plot.plot(time, signalAmplitude,'bs')

plot.xlabel('time')

plot.ylabel('amplitude')

 

# plot the signal in frequency domain

plot.subplot(212)

 

# sampling frequency = 4 - get a magnitude spectrum

plot.magnitude_spectrum(signalAmplitude,Fs=4)

# display the plots

plot.show()

 

Output:

Magnitude spectrum of a signal plotted with python and matplotlib


Copyright 2020 © pythontic.com