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Matplotlib.axis.Tick.set_clip_box() function in Python
  • Last Updated : 10 Jun, 2020

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. It is an amazing visualization library in Python for 2D plots of arrays and used for working with the broader SciPy stack.
 

Matplotlib.axis.Tick.set_clip_box() Function

The Tick.set_clip_box() function in axis module of matplotlib library is used to set the artist’s clip Bbox. 
 

Syntax: Tick.set_clip_box(self, clipbox) 
 

Parameters: This method accepts the following parameters. 

  • clipbox: This parameter is the Bbox.

Return value: This method does not return any value. 



Below examples illustrate the matplotlib.axis.Tick.set_clip_box() function in matplotlib.axis:
Example 1:

Python3




# Implementation of matplotlib function
from matplotlib.axis import Tick
import matplotlib.pyplot as plt  
import numpy as np  
from matplotlib.patches import Ellipse  
       
     
delta = 10.0
       
angles = np.arange(0, 360 + delta, delta)  
ells = [Ellipse((2, 2), 5, 2, a) for a in angles]  
       
fig, ax = plt.subplots()  
       
for e in ells:  
    Tick.set_clip_box(e, ax.bbox)  
    e.set_alpha(0.1)  
    ax.add_artist(e)  
       
plt.xlim(-1, 5)  
plt.ylim(-1, 5
  
fig.suptitle('matplotlib.axis.Tick.set_clip_box() \
function Example', fontweight ="bold")  
     
plt.show() 
=

Output: 

Example 2:

Python3




# Implementation of matplotlib function
from matplotlib.axis import Tick
import matplotlib.pyplot as plt  
import numpy as np  
from matplotlib.patches import Ellipse  
         
     
NUM = 200
         
ells = [Ellipse(xy = np.random.rand(2),  
                width = np.random.rand(),   
                height = np.random.rand(),  
                angle = np.random.rand() * 360)  
        for i in range(NUM)]  
         
fig, ax = plt.subplots(subplot_kw ={'aspect': 'equal'})  
     
for e in ells:  
    ax.add_artist(e) 
    Tick.set_clip_box(e, ax.bbox)  
    e.set_clip_box(ax.bbox)  
    e.set_alpha(np.random.rand())  
    e.set_facecolor(np.random.rand(4))  
  
fig.suptitle('matplotlib.axis.Tick.set_clip_box() \
function Example', fontweight ="bold")  
     
plt.show() 

Output: 

 

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