Matplotlib.axes.Axes.set_clip_path() in Python

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Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.

matplotlib.axes.Axes.set_clip_path() Function

The Axes.set_clip_path() function in axes module of matplotlib library is used to set the artist’s clip path.

Syntax: Axes.set_clip_path(self, path, transform=None)

Parameters: This method accepts only two parameters.

path: This parameter is the clip path.

transform: This parameter in which Path is converted to a TransformedPath using transform.

Returns: This method does not return any value.

Below examples illustrate the matplotlib.axes.Axes.set_clip_path() function in matplotlib.axes:

Example 1:

Input Image:

geek-11

# Implementation of matplotlib function 
import matplotlib.pyplot as plt 
import matplotlib.patches as patches 
import matplotlib.cbook as cbook 
   
  
with cbook.get_sample_data('loggf.PNG') as image_file: 
    image = plt.imread(image_file) 
   
fig, ax = plt.subplots() 
im = ax.imshow(image) 
patch = patches.Rectangle((0, 0), 
                          260, 
                          200,  
                          transform = ax.transData) 
im.set_clip_path(patch) 
  
fig.suptitle('matplotlib.axes.Axes.set_clip_path() \ 
function Example\n\n', fontweight ="bold") 
  
plt.show() 

Output:

Example 2:

# Implementation of matplotlib function 
import numpy as np 
import matplotlib.cm as cm 
import matplotlib.pyplot as plt 
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) 
  
fig.suptitle('matplotlib.axes.Axes.set_clip_path() \ 
function Example\n\n', fontweight ="bold") 
  
plt.show() 