Matplotlib.axes.Axes.set_clip_path() in Python
Last Updated :
30 Apr, 2020
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:
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()
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Output:
Example 2:
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()
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Output:
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