Matplotlib.artist.Artist.set_clip_box() in Python

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_box() method

The set_clip_box() method in artist module of matplotlib library is used to set the artist’s clip Bbox.

Syntax: Artist.set_clip_box(self, clipbox)

Parameters: This method accepts only one parameters.

• clipbox: This parameter is the Bbox.

Returns: This method does not return any value.

Below examples illustrate the matplotlib.artist.Artist.set_clip_box() function in matplotlib:

Example 1:

# Implementation of matplotlib function
from matplotlib.artist import Artist
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:
    Artist.set_clip_box(e, ax.bbox)
    e.set_alpha(0.1)
    ax.add_artist(e)

plt.xlim(-1, 5)
plt.ylim(-1, 5)

fig.suptitle('matplotlib.artist.Artist.set_clip_box() \
function Example', fontweight ="bold")

plt.show()

Output:

Example 2:

# Implementation of matplotlib function
from matplotlib.artist import Artist
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Ellipse


NUM = 200

ells = [Ellipse(xy = np.random.rand(2) * 10,
                width = np.random.rand(),
                height = np.random.rand(),
                angle = np.random.rand() * 360)
        for i in range(NUM)]

fig, ax = plt.subplots(subplot_kw ={'aspect': 'equal'})

for e in ells:
    ax.add_artist(e)
    Artist.set_clip_box(e, ax.bbox)
    e.set_clip_box(ax.bbox)
    e.set_alpha(np.random.rand())
    e.set_facecolor(np.random.rand(4))

ax.set_xlim(3, 7)
ax.set_ylim(3, 7)


fig.suptitle('matplotlib.artist.Artist.set_clip_box()\
function Example', fontweight ="bold")

plt.show()

Output: