Matplotlib.axes.Axes.xcorr() in Python
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.xcorr() Function
The Axes.xcorr() function in axes module of matplotlib library is used to plot the cross correlation between x and y.
Syntax: Axes.xcorr(self, x, y, normed=True, detrend=, usevlines=True, maxlags=10, *, data=None, **kwargs)
Parameters: This method accept the following parameters that are described below:
- x, y : These parameter are the sequence of scalar.
- detrend: This parameter is an optional parameter. Its default value is mlab.detrend_none
- normed: This parameter is also an optional parameter and contains the bool value. Its default value is True
- usevlines: This parameter is also an optional parameter and contains the bool value. Its default value is True
- maxlags: This parameter is also an optional parameter and contains the integer value. Its default value is 10
- linestyle: This parameter is also an optional parameter and used for plotting the data points, only when usevlines is False.
- marker: This parameter is also an optional parameter and contains the string. Its default value is ‘o’
Returns: This method returns the following:
- lags:This method returns the lag vector
- c:This method returns the auto correlation vector.
- line : Added LineCollection if usevlines is True, otherwise add Line2D.
- b: This method returns the horizontal line at 0 if usevlines is True, otherwise None.
The resultant is (lags, c, line, b).
Below examples illustrate the matplotlib.axes.Axes.xcorr() function in matplotlib.axes:
Example 1:
import matplotlib.pyplot as plt
import numpy as np
geeksx = np.array([ 24.40 , 110.25 , 20.05 ,
22.00 , 61.90 , 7.80 ,
15.00 , 22.80 , 34.90 ,
57.30 ])
geeksy = np.array([ 24.40 , 110.25 , 20.05 ,
22.00 , 61.90 , 7.80 ,
15.00 , 22.80 , 34.90 ,
57.30 ])
fig, ax = plt.subplots()
ax.xcorr(geeksx, geeksy, maxlags = 9 ,
color = "green" )
ax.set_ylabel( 'Y-axis' )
ax.set_xlabel( 'X-axis' )
ax.set_title( 'matplotlib.axes.Axes.xcorr() Example' )
plt.show()
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Output:
Example 2:
import matplotlib.pyplot as plt
import numpy as np
np.random.seed( 10 * * 7 )
geeksx = np.random.randn( 100 )
geeksy = np.random.randn( 100 )
fig, ax = plt.subplots()
ax.xcorr(geeksx, geeksy, usevlines = True ,
normed = True , maxlags = 80 ,
color = "green" )
ax.grid( True )
ax.set_title( 'matplotlib.axes.Axes.xcorr() Example' )
plt.show()
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Output:
Last Updated :
21 Apr, 2020
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