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_on() method
The set_clip_on() method in artist module of matplotlib library is used to set whether the artist uses clipping.
Syntax: Artist.set_clip_on(self, b)
Parameters: This method accepts only one parameters.
- b: This parameter contains the boolean value.
Returns: This method does not return any value.
Below examples illustrate the matplotlib.artist.Artist.set_clip_on() 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:
e.set_alpha( 0.1 )
ax.add_artist(e)
ax.set_xlim( - 1 , 5 )
ax.set_ylim( - 1 , 5 )
Artist.set_clip_on(ax, b = False )
fig.suptitle('matplotlib.artist.Artist.set_clip_on()\ function Example', fontweight = "bold" )
plt.show() |
Output:
Example 2:
# Implementation of matplotlib function from matplotlib.artist import Artist
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import matplotlib.transforms as mtransforms
x0 = - 0.1
arrow_style = "simple, head_length = 15 , \
head_width = 30 , tail_width = 10 "
rect_style = "simple, tail_width = 25"
line_style = "simple, tail_width = 1"
fig, ax = plt.subplots()
trans = mtransforms.blended_transform_factory(ax.transAxes,
ax.transData)
y_tail = 5
y_head = 15
arrow1 = mpatches.FancyArrowPatch((x0, y_tail),
(x0, y_head),
arrowstyle = arrow_style,
transform = trans)
Artist.set_clip_on(arrow1, b = False )
ax.add_patch(arrow1) ax.set_xlim( 0 , 30 )
ax.set_ylim( 0 , 80 )
fig.suptitle('matplotlib.artist.Artist.set_clip_on()\ function Example', fontweight = "bold" )
plt.show() |
Output: