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Matplotlib.axis.Tick.get_picker() in Python

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  • Last Updated : 01 May, 2022
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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.Tick.get_picker() Function

The Tick.get_picker() function in axis module of matplotlib library is used to define the picking behavior of the artist.

Syntax: Tick.get_picker(self) 

Parameters: This method does not accepts any parameter. 

Return value: This method return the picking behavior of the artist.

Below examples illustrate the matplotlib.axis.Tick.get_picker() function in matplotlib.axis: 

Example 1: 

Python3




# Implementation of matplotlib function
from matplotlib.axis import Tick
import numpy as np
import matplotlib.pyplot as plt
  
  
np.random.seed(19680801)
  
volume = np.random.rayleigh(7, 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**3,
                     amount**3,
                     c=ranking**3,
                     s=price ** 4,
                     vmin=-3,
                     vmax=3,
                     cmap="Spectral")
  
ax.text(8, 8, "Value return : "
        + str(Tick.get_picker(ax)),
        fontweight="bold",
        fontsize=18)
  
fig.suptitle("""matplotlib.axis.Tick.get_picker()
function Example\n""", fontweight="bold")
  
plt.show()

Output: 

 

 Example 2: 

Python3




# Implementation of matplotlib function
from matplotlib.axis import Tick
import numpy as np
import matplotlib.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-', picker=5)
  
ax.set_picker(True)
  
ax.text(0.48, 0.3, "Value return : "
        + str(Tick.get_picker(ax)),
        fontweight="bold",
        fontsize=18)
  
fig.suptitle("""matplotlib.axis.Tick.get_picker()
function Example\n""", fontweight="bold")
  
plt.show()

Output: 

 


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