Plot the phase spectrum in Python using Matplotlib
Last Updated :
27 Apr, 2020
A
Signal is an electromagnetic field or an electric current to transmit data. There are various components of a signal such as frequency, amplitude, wavelength, phase, angular frequency and period from which it is described.
A periodic signal can be represented using the below sine function:
y = A sin(w*t + Q)
In which
A
represents the amplitude(in meter),
w
represents frequency(in hertz),
t
represents time period(in seconds) and
Q
represents phase(in radian) of the periodic signal.
The two major components frequency and phase of a periodic signal define the
Phase Spectrum of that signal. The frequency components of the periodic signal are plotted in the horizontal axis and phase component of the periodic signal is plotted in the vertical axis.
In Python, the
phase_spectrum()
method in the
pyplot
module of Python
matplotlib
library plots the phase spectrum of a periodic signal. Below are some programs which demonstrate the use of
phase_spectrum()
method to visualize the phase spectrum of different periodic signals.
Example 1:
Python3
# importing modules
import numpy
from matplotlib import pyplot
# assigning time values of the signal
# initial time period, final time period and phase angle
signalTime = numpy.arange(5, 10, 0.25);
# getting the amplitude of the signal
signalAmplitude = numpy.sin(signalTime)
# plotting the signal
pyplot.plot(signalTime, signalAmplitude, color ='green')
pyplot.show()
pyplot.xlabel('Time')
pyplot.ylabel('Amplitude')
pyplot.title("Signal")
# plotting the phase spectrum of the signal
pyplot.phase_spectrum(signalAmplitude, color ='green')
pyplot.title("Phase Spectrum of the Signal")
pyplot.show()
Output:

The first graph represent the signal in Amplitude vs Time components, the second graph represents the phase spectrum of the signal in Phase vs Frequency graph by using
phase_spectrum()
on the signal having time period from 5 to 10 seconds, 0.25 radian phase angle, frequency of the signal is calculated from the given time period and amplitude of the signal is calculated using the
sin()
function in
numpy
module.
Example 2:
Python3
# importing modules
import numpy
from matplotlib import pyplot
# assigning time values of the signal
# initial time period, final time period and phase angle
signalTime = numpy.arange(0, 1, 0.1)
# getting the amplitude of the signal
signalAmplitude = numpy.sin(signalTime)
# plotting the signal
pyplot.plot(signalTime, signalAmplitude, color ='green')
pyplot.show()
pyplot.xlabel('Time')
pyplot.ylabel('Amplitude')
pyplot.title("Signal")
# plotting the phase spectrum of the signal
pyplot.phase_spectrum(signalAmplitude, color ='green')
pyplot.title("Phase Spectrum of the Signal")
pyplot.show()
Output:

In the above program, as the amplitude of the signal is increasing with time so a sinusoidal wave is not formed in the first graph. The signal exists in the time period of 0 to 1 second and the phase angle is 0.1 radian, the phase spectrum of the signal is depicted using
phase_spectrum()
method.
Example 3:
Python3
# importing modules
import numpy
from matplotlib import pyplot
# assigning time values of the signal
# initial time period, final time period and phase angle
signalTime = numpy.arange(1, 100, 0.5);
# getting the amplitude of the signal
signalAmplitude = numpy.sin(signalTime)
# plotting the signal
pyplot.plot(signalTime, signalAmplitude, color ='green')
pyplot.show()
pyplot.xlabel('Time')
pyplot.ylabel('Amplitude')
pyplot.title("Signal")
# plotting the phase spectrum of the signal
pyplot.phase_spectrum(signalAmplitude, color ='green')
pyplot.title("Phase Spectrum of the Signal")
pyplot.show()
Output:

Here, the signal is represented in Amplitude vs Time graph which forms sinusoidal waves and the phase spectrum of the signal is represented using
phase_spectrum()
method in Phase vs Frequency graph. The time period of the signal starts from 1 second to 100th second and the phase angle is 0.5 radian.
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