Matplotlib.axis.Axis.get_clip_on() function in Python

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. It is an amazing visualization library in Python for 2D plots of arrays and used for working with the broader SciPy stack.

Matplotlib.axis.Axis.get_clip_on() Function

The Axis.get_clip_on() function in axis module of matplotlib library is used to get whether the artist uses clipping. 

Syntax: Axis.get_clip_on(self) 

Parameters: This method does not accepts any parameter. 

Return value: This method return the whether the artist uses clipping. 

Below examples illustrate the matplotlib.axis.Axis.get_clip_on() function in matplotlib.axis:

Example 1:

Python3

# Implementation of matplotlib function
from matplotlib.axis import Axis
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)

print("Value Return by get_clip_on() : ",
      Axis.get_clip_on(ax))

fig.suptitle("""matplotlib.axis.Axis.get_clip_on()
function Example\n""", fontweight ="bold")

plt.show()

Output:

Value Return by get_clip_on() :  True

Example 2:

Python3

# Implementation of matplotlib function
from matplotlib.axis import Axis
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 = 80
arrow1 = mpatches.FancyArrowPatch((x0, y_tail),
                                  (x0, y_head),
                                  arrowstyle = arrow_style,
                                  transform = trans)

Axis.set_clip_on(arrow1, False)
ax.add_patch(arrow1)

ax.set_xlim(0, 30)
ax.set_ylim(0, 80)

print("Value Return by get_clip_on() : ",
      Axis.get_clip_on(arrow1))

fig.suptitle("""matplotlib.axis.Axis.get_clip_on()
function Example\n""", fontweight ="bold")

plt.show()

Output:

Value Return by get_clip_on() :  False