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Matplotlib.artist.Artist.pickable() in Python

  • Last Updated : 10 May, 2020

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.pickable() method

The pickable() method in artist module of matplotlib library is used to return whether the artist is pickable or not.

Syntax: Artist.pickable(self)

Parameters: This method does not accept any parameters.

Returns: This method return whether the artist is pickable.

Below examples illustrate the matplotlib.artist.Artist.pickable() function in matplotlib:

Example 1:




# Implementation of matplotlib function
from matplotlib.artist import Artist
import numpy as np 
np.random.seed(19680801
import matplotlib.pyplot as plt 
     
  
volume = np.random.rayleigh(27, size = 40
amount = np.random.poisson(10, size = 40
ranking = np.random.normal(size = 40
price = np.random.uniform(1, 10, size = 40
     
fig, ax = plt.subplots() 
     
scatter = ax.scatter(volume * 2, amount * 3
                     c = ranking * 3,  
                     s = 0.3*(price * 3)**2
                     vmin = -4, vmax = 4,  
                     cmap = "Spectral"
    
legend1 = ax.legend(*scatter.legend_elements(num = 5), 
                    loc ="upper left"
                    title ="Ranking"
    
ax.add_artist(legend1) 
    
ax.text(60, 30, "Value return : "
        + str(Artist.pickable(ax)),  
        fontweight ="bold",  
        fontsize = 18
          
fig.suptitle('matplotlib.artist.Artist.pickable() function\
 Example', fontweight ="bold"
  
plt.show()

Output:

Example 2:




# Implementation of matplotlib function
from matplotlib.artist import Artist
import numpy as np 
import matplotlib.pyplot as plt 
import matplotlib.cbook as cbook 
     
  
np.random.seed(10**7
data = np.random.lognormal(size =(10, 4), 
                           mean = 4.5
                           sigma = 4.75
    
labels = ['G1', 'G2', 'G3', 'G4'
     
result = cbook.boxplot_stats(data,  
                             labels = labels,  
                             bootstrap = 1000
     
for n in range(len(result)): 
    result[n]['med'] = np.median(data) 
    result[n]['mean'] *= 0.1
    
fig, axes1 = plt.subplots() 
axes1.bxp(result) 
    
axes1.text(2, 30000
           "Value return : " 
           + str(Artist.pickable(axes1)),  
           fontweight ="bold"
          
fig.suptitle('matplotlib.artist.Artist.pickable()\
 function Example', fontweight ="bold"
  
plt.show()

Output:


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