Matplotlib.artist.Artist.set_picker() in Python

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_picker() method
The set_picker() method in artist module of matplotlib library is used to define the picking behavior of the artist.
Syntax: Artist.set_picker(self, picker)
Parameters: This method accept the following parameters as discussed below:
- picker : This parameter is used to set picking behavior. This can be None or bool or float or function.
Returns: This method the picking behavior of the artist.
Below examples illustrate the matplotlib.artist.Artist.set_picker() function in matplotlib:
Example 1:
| # Implementation of matplotlib function frommatplotlib.artist importArtist importnumpy as np  importmatplotlib.pyplot as plt         np.random.seed(19680801)   volume =np.random.rayleigh(27, size =40)  amount =np.random.poisson(7, size =40)  ranking =np.random.normal(size =40)  price =np.random.uniform(1, 7, size =40)        fig, ax =plt.subplots()        scatter =ax.scatter(volume *2,                        amount**3,                       c =ranking**3,                       s =price**3,                       vmin =-3,                       vmax =3,                       cmap ="Spectral")     Artist.set_picker(ax, picker =4)           fig.suptitle('matplotlib.artist.Artist.set_picker()\ function Example', fontweight ="bold")   plt.show()  | 
Output:
Example 2:
| # Implementation of matplotlib function frommatplotlib.artist importArtist importnumpy as np  importmatplotlib.pyplot as plt      X =np.random.rand(10, 200)  xs =np.mean(X, axis =1)  ys =np.std(X, axis =1)     fig =plt.figure()  ax =fig.add_subplot(111)  line, =ax.plot(xs, ys, 'go-')     Artist.set_picker(ax, picker =True)           fig.suptitle('matplotlib.artist.Artist.set_picker()\  function Example', fontweight ="bold")   plt.show()  | 
Output:
 
				 
					



