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Matplotlib.axes.Axes.get_autoscale_on() in Python

Last Updated : 19 Apr, 2020
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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.get_autoscale_on() Function

The Axes.get_autoscale_on() function in axes module of matplotlib library is used to get whether autoscaling is applied for both axes on plot commands.
Syntax: Axes.get_autoscale_on(self) Parameters: This method does not accepts any parameters. Return value: This method returns the boolean value.
Below examples illustrate the matplotlib.axes.Axes.get_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-')

w = ax.get_autoscale_on()
ax.text(75, 1.95, "Value return by get_autoscale_on : " 
        + str(w), fontweight ="bold")

fig.suptitle('matplotlib.axes.Axes.get_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))
ydata = np.sin(2 * np.pi * xdata / 50) + np.cos(2 * np.pi * xdata / 20)
 
fig, (ax, ax1) = plt.subplots(1, 2)
 
ax.plot(xdata, ydata, 'g-', alpha = 0.4)
ax.set_title("Axes 1")
ax1.plot(xdata, ydata, 'g-')
ax1.set_autoscale_on(False)
ax1.set_title("Axes 2")

w = ax.get_autoscale_on()
ax.text(75, 0, "Value return : " + str(w), 
        fontweight ="bold")

w1 = ax1.get_autoscale_on()
ax1.text(0.2, 0.5, "Value return : " + str(w1), 
         fontweight ="bold")

fig.suptitle('matplotlib.axes.Axes.get_autoscale_on()\
function Example\n', fontweight ="bold")
fig.canvas.draw()
plt.show()
Output:

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