Matplotlib.axis.Axis.set_alpha() 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.set_alpha() Function

The Axis.set_alpha() function in axis module of matplotlib library is used to set the alpha value used for blending. 

Syntax: Axis.set_alpha(self, alpha) 

Parameters: This method accepts the following parameters. 

• alpha: This parameter is the contains float value or None.

Return value: This method does not return any value. 

Below examples illustrate the matplotlib.axis.Axis.set_alpha() 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


# create test data
np.random.seed(10**7)
data = [sorted(np.random.normal(0, std, 100))
       for std in range(1, 5)]

fig, ax1 = plt.subplots()
val = ax1.violinplot(data)
ax1.set_ylabel('Result')
ax1.set_xlabel('Domain Name')

for i in val['bodies']:
    i.set_facecolor('yellow')
    Axis.set_alpha(i, 0.3)

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

plt.show()

Output:

Example 2:

Python3

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


NUM = 100

ells = [Ellipse(xy = np.random.rand(2) * 10,
                width = np.random.rand(),
                height = np.random.rand(),
                angle = np.random.rand() * 360)
        for i in range(NUM)]

fig, ax = plt.subplots(subplot_kw ={'aspect': 'equal'})

for e in ells:
    ax.add_artist(e)
    e.set_clip_box(ax.bbox)
    Axis.set_alpha(e, np.random.rand())
    e.set_facecolor(np.random.rand(4))

ax.set_xlim(2, 8)
ax.set_ylim(2, 8)

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

plt.show()

Output: