Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Artist class contains Abstract base class for objects that render into a FigureCanvas. All visible elements in a figure are subclasses of Artist.
matplotlib.artist.Artist.set_alpha() method
The set_alpha() method in artist module of matplotlib library is used to set the alpha value used for blending.
Syntax: Artist.set_alpha(self, alpha)
Parameters: This method accepts the following parameters.
- alpha: This parameter is the contains float value or None.
 Returns: This method does not return any value.
Below examples illustrate the matplotlib.artist.Artist.set_alpha() function in matplotlib:
Example 1:
# Implementation of matplotlib function from matplotlib.artist import Artist   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('green')      Artist.set_alpha(i, 0.5)     fig.suptitle('matplotlib.artist.Artist.set_alpha()\ function Example', fontweight ="bold")    plt.show()  | 
Output:
Example 2:
# Implementation of matplotlib function from matplotlib.artist import Artist   import matplotlib.pyplot as plt  import numpy as np  from matplotlib.patches import Ellipse         NUM = 200     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)      Artist.set_alpha(e, np.random.rand())      e.set_facecolor(np.random.rand(4))       ax.set_xlim(3, 7)  ax.set_ylim(3, 7)    fig.suptitle('matplotlib.artist.Artist.set_alpha()\ function Example', fontweight ="bold")    plt.show()  | 
Output:

                                    