Open In App

Matplotlib.axes.Axes.set_autoscale_on() in Python

Last Updated : 22 Dec, 2021
Improve
Improve
Like Article
Like
Save
Share
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.set_autoscale_on() Function

The Axes.set_autoscale_on() function in axes module of matplotlib library is used to set whether autoscaling is applied on plot commands.
 

Syntax: Axes.set_autoscale_on(self, b)
Parameters: This method accepts the following parameters. 
 

  • b: This parameter is used to whether to autoscaling is applied on plot commands or not.

Return value: This method does not return any value. 
 

Below examples illustrate the matplotlib.axes.Axes.set_autoscale_on() function in matplotlib.axes:
Example 1: 
 

Python3




# ImpleIn Reviewtation of matplotlib function 
import numpy as np
import matplotlib.pyplot as plt
 
xdata = np.linspace(16, 365, 300)
ydata = np.sin(2 * np.pi * xdata / 15) + np.cos(2 * np.pi * xdata / 17)
 
fig, ax = plt.subplots()
 
ax.plot(xdata, ydata, 'g-')
ax.set_autoscale_on(True)
 
fig.suptitle('matplotlib.axes.Axes.set_autoscale_on() function\
 Example\n', fontweight ="bold")
fig.canvas.draw()
plt.show()


Output: 
 

Example 2: 
 

Python3




# ImpleIn Reviewtation of matplotlib function 
import numpy as np
import matplotlib.pyplot as plt
 
xdata = np.linspace(16, 365, (365-16)*4)
ydata = np.sin(2 * np.pi * xdata / 153) + np.cos(2 * np.pi * xdata / 127)
 
fig, (ax, ax1) = plt.subplots(1, 2)
 
ax.plot(xdata, ydata, 'g-')
ax1.set_autoscale_on(True)
ax.set_title("set_autoscale_on value : True")
ax1.plot(xdata, ydata, 'g-')
ax1.set_autoscale_on(False)
ax1.set_title("set_autoscale_on value : False")
 
fig.suptitle('matplotlib.axes.Axes.set_autoscale_on() function \
Example\n', fontweight ="bold")
fig.canvas.draw()
plt.show()


Output: 
 

 



Like Article
Suggest improvement
Share your thoughts in the comments

Similar Reads