Matplotlib.axes.Axes.set_clip_on() in Python

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.

matplotlib.axes.Axes.set_clip_on() Function

The Axes.set_clip_on() function in axes module of matplotlib library is used to set whether the artist uses clipping.

Syntax: Axes.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.axes.Axes.set_clip_on() function in matplotlib.axes:

Example 1:

# Implementation of matplotlib function
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)
ax.set_clip_on(False)

fig.suptitle('matplotlib.axes.Axes.set_clip_on()\
 function Example\n\n', fontweight ="bold")

plt.show()

Output:

Example 2:

# Implementation of matplotlib function
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)
arrow1.set_clip_on(False)
ax.add_patch(arrow1)

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

fig.suptitle('matplotlib.axes.Axes.set_clip_on() \
function Example\n\n', fontweight ="bold")

plt.show()

Output: