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

  • Last Updated : 05 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.Axis.set_snap() Function

The Axis.set_snap() function in axis module of matplotlib library is used to set the snapping behavior. 
 

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Syntax: Axis.set_snap(self, snap) 
 



Parameters: This method accepts the following parameters. 

  • snap: This parameter contains the boolean value or None.

Return value: This method does not return any value. 

Below examples illustrate the matplotlib.axis.Axis.set_snap() function in matplotlib.axis:
 

Example 1:

Python3




# Implementation of matplotlib function
from matplotlib.axis import Axis
import matplotlib.pyplot as plt  
from mpl_toolkits.axisartist.axislines import Subplot  
        
    
fig = plt.figure()  
        
ax = Subplot(fig, 111)  
fig.add_subplot(ax)  
        
ax.axis["left"].set_visible(False)  
ax.axis["top"].set_visible(False)  
      
Axis.set_snap(ax, True)  
  
fig.suptitle('matplotlib.axis.Axis.set_snap() \
function Example\n', fontweight ="bold")  
    
plt.show() 

Output: 

Example 2:

Python3




# Implementation of matplotlib function
from matplotlib.axis import Axis
import numpy as np  
import matplotlib.cm as cm  
import matplotlib.pyplot as plt  
import matplotlib.cbook as cbook  
from matplotlib.path import Path  
from matplotlib.patches import PathPatch  
       
      
delta = 0.025
    
x = y = np.arange(-3.0, 3.0, delta)  
X, Y = np.meshgrid(x, y)  
    
Z1 = np.exp(-X**2 - Y**2)  
Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)  
Z = (Z1 - Z2) * 2
       
path = Path([[0, 1], [1, 0], [0, -1],  
            [-1, 0], [0, 1]])  
patch = PathPatch(path, facecolor ='none')  
       
fig, ax = plt.subplots()  
ax.add_patch(patch)  
       
im = ax.imshow(Z, interpolation ='bilinear',   
               cmap = cm.gray,  
               origin ='lower',  
               extent =[-3, 3, -3, 3],  
               clip_path = patch, clip_on = True)  
    
im.set_clip_path(patch) 
      
Axis.set_snap(im, None)  
  
fig.suptitle('matplotlib.axis.Axis.set_snap() \
function Example\n', fontweight ="bold")  
    
plt.show() 

Output: 

 




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