Open In App
Related Articles

Matplotlib.axes.Axes.phase_spectrum() in Python

Improve
Improve
Improve
Like Article
Like
Save Article
Save
Report issue
Report
Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.

matplotlib.axes.Axes.phase_spectrum() Function

The Axes.phase_spectrum() function in axes module of matplotlib library is used to plot the phase spectrum.
Syntax: Axes.phase_spectrum(self, x, Fs=None, Fc=None, window=None, pad_to=None, sides=None, *, data=None, **kwargs) Parameters: This method accept the following parameters that are described below:
  • x: This parameter is a sequence of data.
  • Fs : This parameter is a scalar. Its default value is 2.
  • window: This parameter take a data segment as an argument and return the windowed version of the segment. Its default value is window_hanning()
  • sides: This parameter specifies which sides of the spectrum to return. This can have following values : ‘default’, ‘onesided’ and ‘twosided’.
  • pad_to : This parameter contains the integer value to which the data segment is padded.
  • Fc: This parameter is also contains the integer value to offsets the x extents of the plot to reflect the frequency range. Its default value is 0
Returns: This returns the following:
  • spectrum :This returns the angle spectrum in radians.
  • freqs :This returns the frequencies corresponding to the elements in spectrum.
  • line : This returns the line created by this function.
The resultant is (spectrum, freqs, line)
Below examples illustrate the matplotlib.axes.Axes.phase_spectrum() function in matplotlib.axes: Example 1:
# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np
np.random.seed(10**5)
   
  
dt = 0.0001
Fs = 1 / dt
geeks = np.array([22.00, 61.90, 7.80,
                  24.40, 110.25, 20.05,
                  15.00, 22.80, 34.90,
                  57.30])
  
nse = np.random.randn(len(geeks))
r = np.exp(-geeks / 0.05)
   
s = 0.5 * np.sin(1.5 * np.pi * geeks) + nse
   
# plot phase_spectrum
fig, ax = plt.subplots()
ax.phase_spectrum(s, Fs = Fs, color ="green")
  
ax.set_title('matplotlib.axes.Axes.phase_spectrum()\
Example')
  
plt.show()

                    
Output: Example 2:
# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np
np.random.seed(0)
  
   
dt = 0.01
Fs = 1 / dt
t = np.arange(0, 10, dt)
res = np.random.randn(len(t))
r = np.exp(-t / 0.05)
   
cres = np.convolve(res, r)*dt
cres = cres[:len(t)]
s = 0.5 * np.sin(1.5 * np.pi * t) + cres
   
# plot simple spectrum
fig, (ax1, ax2) = plt.subplots(2, 1)
ax1.plot(t, s, color ="green")
   
# plot phase_spectrum
ax2.phase_spectrum(s, Fs = Fs, color ="green")
   
ax1.set_title('matplotlib.axes.Axes.phase_spectrum()\
Example')
  
plt.show()

                    
Output:

Don't miss your chance to ride the wave of the data revolution! Every industry is scaling new heights by tapping into the power of data. Sharpen your skills and become a part of the hottest trend in the 21st century.

Dive into the future of technology - explore the Complete Machine Learning and Data Science Program by GeeksforGeeks and stay ahead of the curve.


Last Updated : 19 Apr, 2020
Like Article
Save Article
Previous
Next
Share your thoughts in the comments
Similar Reads
Complete Tutorials