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Matplotlib.axes.Axes.get_animated() in Python
  • Last Updated : 30 Apr, 2020

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_animated() Function

The Axes.get_animated() function in axes module of matplotlib library is used to get the animated state.

Syntax: Axes.get_animated(self)

Parameters: This method does not accepts any parameter.

Returns: This method return the the animated state.



Below examples illustrate the matplotlib.axes.Axes.get_animated() function in matplotlib.axes:

Example 1:




# Implementation of matplotlib function
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
  
   
data = np.array([[1, 2, 3, 4, 5], 
                [7, 4, 9, 2, 3]])
   
fig = plt.figure()
ax = plt.axes(xlim =(0, 20), ylim =(0, 20))
   
line, = ax.plot([], [], 'r-')
annotation = ax.annotate('', xy =(data[0][0], 
                         data[1][0]))
annotation.set_animated(True)
w = annotation.get_animated()
  
print(str(w))
  
fig.suptitle('matplotlib.axes.Axes.get_animated() \
function Example\n\n', fontweight ="bold")
  
plt.show()

Output:

True

Example 2:




# Implementation of matplotlib function
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
   
  
fig, ax = plt.subplots()
   
ax.set_xlim([-1, 1])
ax.set_ylim([-1, 1])
   
L = 50
theta = np.linspace(0, 2 * np.pi, L)
r = np.ones_like(theta)
   
x = r * np.cos(theta)
y = r * np.sin(theta)
   
line, = ax.plot(1, 0, 'ro')
   
annotation = ax.annotate(
    'annotation', xy =(1, 0), xytext =(-1, 0),
    arrowprops = {'arrowstyle': "->"}
)
annotation.set_animated(False)
   
w = annotation.get_animated()
  
print(str(w))
  
fig.suptitle('matplotlib.axes.Axes.get_animated()\
 function Example\n\n', fontweight ="bold")
  
plt.show()

Output:

False

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