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Matplotlib.axes.Axes.set_alpha() in Python

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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_alpha() Function

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

Syntax: Axes.set_alpha(self, alpha)

Parameters: This method accepts only one parameters.

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

Returns: This method does not return any value.

Below examples illustrate the matplotlib.axes.Axes.set_alpha() function in matplotlib.axes:

Example 1:




# Implementation of matplotlib function
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')
    i.set_alpha(0.9
   
fig.suptitle('matplotlib.axes.Axes.set_alpha() \
function Example\n\n', fontweight ="bold")
  
plt.show()


Output:

Example 2:




# Implementation of matplotlib function
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)
    e.set_alpha(np.random.rand())
    e.set_facecolor(np.random.rand(4))
   
ax.set_xlim(3, 7)
ax.set_ylim(3, 7)
   
   
fig.suptitle('matplotlib.axes.Axes.set_alpha()\
 function Example\n\n', fontweight ="bold")
  
plt.show()


Output:



Last Updated : 30 Apr, 2020
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