Skip to content
Related Articles

Related Articles

Improve Article
Save Article
Like Article

Matplotlib.pyplot.csd() in Python

  • Last Updated : 21 Apr, 2020

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. Pyplot is a state-based interface to a Matplotlib module which provides a MATLAB-like interface.

matplotlib.pyplot.csd() Function

The csd() function in pyplot module of matplotlib library is used to plot the cross-spectral density.

Syntax: matplotlib.pyplot.csd(x, y, NFFT=None, Fs=None, Fc=None, detrend=None, window=None, noverlap=None, pad_to=None, sides=None, scale_by_freq=None, return_line=None, \*, data=None, \*\*kwargs)

Parameters: This method accept the following parameters that are described below:

  • x, y: These parameter are the 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.
  • NFFT : This parameter contains the number of data points used in each block for the FFT.
  • detrend : This parameter contains the function applied to each segment before fft-ing, designed to remove the mean or linear trend {‘none’, ‘mean’, ‘linear’}.
  • scale_by_freq : This parameter is allows for integration over the returned frequency values.
  • noverlap : This parameter is the number of points of overlap between blocks.
  • Fc : This parameter is the center frequency of x.
  • return_line : This parameter include the line object plotted in the returned values.

Returns: This returns the following:

  • Pxy:This returns the values for the cross spectrum P_{xy} before scaling.
  • freqs :This returns the frequencies for the elements in Pxy.
  • line :This returns the line created by this function.

The resultant is (Pxy, freqs, line)

Below examples illustrate the matplotlib.pyplot.csd() function in matplotlib.pyplot:

Example #1:

# Implementation of matplotlib function
import numpy as np
import matplotlib.pyplot as plt
dt = 0.01
t = np.arange(0, 30, dt)
nse1 = np.random.randn(len(t))
nse2 = np.random.randn(len(t))
s1 = 1.5 * np.sin(2 * np.pi * 10 * t) + nse1
s2 = np.cos(np.pi * t) + nse2
plt.csd(s1, s2**2, 128, 1./dt)
plt.title('matplotlib.pyplot.csd() function Example',
          fontweight ="bold")


Example #2:

#Implementation of matplotlib function
import numpy as np
import matplotlib.pyplot as plt
dt = 0.01
t = np.arange(0, 30, dt)
nse1 = np.random.randn(len(t))
nse2 = np.random.randn(len(t))
r = np.exp(-t/0.05)
cnse1 = np.convolve(nse1, r, mode='same')*dt
cnse2 = np.convolve(nse2, r, mode='same')*dt
s1 = 1.5 * np.sin(2*np.pi*10*t) + cnse1
s2 = np.cos(np.pi*t) + cnse2 + np.sin(2*np.pi*10*t)
plt.plot(t, s1, t, s2)
plt.xlim(0, 5)
plt.ylabel('s1 and s2')
plt.csd(s1, s2, 256, 1./dt)
plt.title('matplotlib.pyplot.csd() function Example'



 Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.  

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning - Basic Level Course

My Personal Notes arrow_drop_up
Recommended Articles
Page :

Start Your Coding Journey Now!