Matplotlib.axis.Tick.get_clip_on() in Python

Last Updated : 01 May, 2022

Matplotlib is a library in Python and it is a 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.Tick.get_clip_on() Function

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

Syntax: Tick.get_clip_on(self)

Parameters: This method does not accepts any parameter.

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

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

Example 1:

Python3

# Implementation of matplotlib function
from matplotlib.axis import Tick
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Ellipse


delta = 10.0

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() : ",
      Tick.get_clip_on(ax))

fig.suptitle("""matplotlib.axis.Tick.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 Tick
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import matplotlib.transforms as mtransforms


y0 = -0.8

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)

x_tail = 0.05
x_head = 0.95
arrow1 = mpatches.FancyArrowPatch((x_tail, y0),
                                  (x_head, y0),
                                  arrowstyle=arrow_style,
                                  transform=trans)

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

ax.set_xlim(0, 10)
ax.set_ylim(0, 10)

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

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

plt.show()