Matplotlib.axis.Axis.set_clip_on() function in Python

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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.Axis.set_clip_on() Function

The Axis.set_clip_on() function in axis module of matplotlib library is used to set whether the artist uses clipping.

Syntax: Axis.set_clip_on(self, b)

Parameters: This method accepts the following parameters.

b: This parameter contains the boolean value.

Return value: This method does not return any value.

Below examples illustrate the matplotlib.axis.Axis.set_clip_on() function in matplotlib.axis:
Example 1:

Python3

# Implementation of matplotlib function 
from matplotlib.axis import Axis 
import matplotlib.pyplot as plt   
import numpy as np   
from matplotlib.patches import Ellipse   
      
    
delta = 45.0
      
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:   
    e.set_alpha(0.1)   
    ax.add_artist(e)   
          
ax.set_xlim(-1, 5)   
ax.set_ylim(-1, 5)   
Axis.set_clip_on(ax, b = False) 
  
fig.suptitle('matplotlib.axis.Axis.set_clip_on() \ 
function Example\n', fontweight ="bold")   
    
plt.show()  

Output:

Example 2:

Python3

# Implementation of matplotlib function 
from matplotlib.axis import Axis 
import matplotlib.pyplot as plt   
import matplotlib.patches as mpatches   
import matplotlib.transforms as mtransforms   
      
      
x0 = -0.1
      
arrow_style ="simple, head_length = 15, \ 
head_width = 25, tail_width = 10"   
rect_style ="simple, tail_width = 25"
line_style ="simple, tail_width = 1"
      
fig, ax = plt.subplots()   
      
trans = mtransforms.blended_transform_factory(ax.transAxes,  
                                              ax.transData)   
      
y_tail = 5
y_head = 80
arrow1 = mpatches.FancyArrowPatch((x0, y_tail),    
                                  (x0, y_head),   
                                   arrowstyle = arrow_style,   
                                   transform = trans)  
    
Axis.set_clip_on(arrow1, b = False)  
ax.add_patch(arrow1)   
      
ax.set_xlim(0, 30)   
ax.set_ylim(0, 80)  
  
fig.suptitle('matplotlib.axis.Axis.set_clip_on() \ 
function Example\n', fontweight ="bold")   
    
plt.show()  