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

Last Updated : 15 Jul, 2025

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_on() Function

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

Syntax: Tick.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.Tick.set_clip_on() 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 = 5.0
     
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)  
Tick.set_clip_on(ax, b = False)

fig.suptitle('matplotlib.axis.Tick.set_clip_on() \
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 matplotlib.patches as mpatches  
import matplotlib.transforms as mtransforms  
     
     
x0 = 1.05
     
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 = 0
y_head = 10
arrow1 = mpatches.FancyArrowPatch((x0, y_tail),   
                                  (x0, y_head),  
                                   arrowstyle = arrow_style,  
                                   transform = trans) 
   
Tick.set_clip_on(arrow1, b = False) 
ax.add_patch(arrow1)  
     
ax.set_xlim(0, 10)  
ax.set_ylim(0, 10) 

fig.suptitle('matplotlib.axis.Tick.set_clip_on() \
function Example', fontweight ="bold")  
   
plt.show()