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

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() 


Output: 

 

Dominic
Dominichttp://wardslaus.com
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