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.Tick.set_clip_on() Function
The Tick.set_clip_on() function in axis module of matplotlib library is used to set whether the artist uses clipping.
Syntax: Tick.set_clip_on(self, b)
Parameters: This method accepts the following parameters.
- b: This parameter contains the boolean value.
Return value: This method does not return any value.
Below examples illustrate the matplotlib.axis.Tick.set_clip_on() function in matplotlib.axis:
Example 1:
# Implementation of matplotlib function
from matplotlib.axis import Tick
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Ellipse
delta = 5.0
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)
Tick.set_clip_on(ax, b = False)
fig.suptitle('matplotlib.axis.Tick.set_clip_on() \
function Example', fontweight ="bold")
plt.show()
Output:
Example 2:
# Implementation of matplotlib function
from matplotlib.axis import Tick
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import matplotlib.transforms as mtransforms
x0 = 1.05
arrow_style ="simple, head_length = 15, \
head_width = 25, 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 = 0
y_head = 10
arrow1 = mpatches.FancyArrowPatch((x0, y_tail),
(x0, y_head),
arrowstyle = arrow_style,
transform = trans)
Tick.set_clip_on(arrow1, b = False)
ax.add_patch(arrow1)
ax.set_xlim(0, 10)
ax.set_ylim(0, 10)
fig.suptitle('matplotlib.axis.Tick.set_clip_on() \
function Example', fontweight ="bold")
plt.show()
Output:
