Matplotlib.axes.Axes.get_picker() in Python

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.get_picker() Function

The Axes.get_picker() function in axes module of matplotlib library is used to return the picking behavior of the artist.

Syntax: Axes.get_picker(self)

Parameters: This method does not accept any parameters.

Returns: This method the picking behavior of the artist.

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

Example 1:

#Implementation of matplotlib function
import numpy as np
np.random.seed(19680801)
import matplotlib.pyplot as plt


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,
                     amount,
                     c = ranking,
                     s = price*3,
                     vmin = -3,
                     vmax = 3,
                     cmap = "Spectral")

legend1 = ax.legend(*scatter.legend_elements(num=5),
                    loc = "upper left",
                    title = "Ranking")

ax.add_artist(legend1)

ax.text(8, 8,"Value return : " + str(ax.get_picker()),
        fontweight = "bold",
        fontsize=18)

fig.suptitle('matplotlib.axes.Axes.get_picker() function \
Example', fontweight="bold")

plt.show()

Output:

Example 2:

# Implementation of matplotlib function
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(ax.get_picker()),
        fontweight = "bold",
        fontsize = 18)

fig.suptitle('matplotlib.axes.Axes.get_picker()\
function Example', fontweight ="bold")

plt.show()

Output: