Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Artist class contains Abstract base class for objects that render into a FigureCanvas. All visible elements in a figure are subclasses of Artist.
matplotlib.artist.Artist.set_clip_path() method
The set_clip_path() method in artist module of matplotlib library is used to set the artist’s clip path.
Syntax: Artist.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.artist.Artist.set_clip_path() function in matplotlib:
Example 1:
Input Image:
# Implementation of matplotlib function from matplotlib.artist import Artist
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(( 10 , 10 ),
560 ,
500 ,
transform = ax.transData)
Artist.set_clip_path(im, patch) fig.suptitle('matplotlib.artist.Artist.set_clip_path()\ function Example', fontweight = "bold" )
plt.show() |
Output:
Example 2:
# Implementation of matplotlib function from matplotlib.artist import Artist
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 )
Artist.set_clip_path(im, patch) fig.suptitle('matplotlib.artist.Artist.set_clip_path()\ function Example', fontweight = "bold" )
plt.show() |
Output: