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Matplotlib.axes.Axes.set_animated() in Python

Last Updated : 30 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.set_animated() Function

The Axes.set_animated() function in axes module of matplotlib library is used to set the artist’s animation state.

Syntax: Axes.set_animated(self, b)

Parameters: This method accepts only one parameters.

  • b: This parameter is the contains boolean value.

Returns: This method does not return any value.

Below examples illustrate the matplotlib.axes.Axes.set_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)
  
def init():
    return line, annotation
  
def update(num):
    newData = np.array([[1 + num,
                         2 + num / 2,
                         3,
                         4 - num / 4,
                         5 + num],
                        [7, 4
                         9 + num / 3,
                         2, 3]])
      
    line.set_data(newData)
    return line, annotation
  
anim = animation.FuncAnimation(fig,
                               update, 
                               frames = 25,
                               init_func = init,
                               interval = 200,
                               blit = True)
   
fig.suptitle('matplotlib.axes.Axes.set_animated() \
function Example\n\n', fontweight ="bold")
  
plt.show()


Output:

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)
  
  
def update(i):
  
    new_x = x[i % L]
    new_y = y[i % L]
    line.set_data(new_x, new_y)
  
    annotation.set_position((-new_x, -new_y))
    annotation.xy = (new_x, new_y)
  
    return line, annotation
  
ani = animation.FuncAnimation(
    fig, update, interval = 500, blit = False
)
   
fig.suptitle('matplotlib.axes.Axes.set_animated()\
 function Example\n\n', fontweight ="bold")
  
plt.show()


Output:



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