Matplotlib.axis.Tick.set_picker() function in Python
Last Updated :
10 Jun, 2020
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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.set_picker() Function
The Tick.set_picker() function in axis module of matplotlib library is used to define the picking behavior of the artist.
Syntax: Tick.set_picker(self, picker)
Parameters: This method accepts the following parameters.
- picker: This parameter is used to set picking behavior. This can be None or bool or float or function.
Return value: This method does not return any value.
Below examples illustrate the matplotlib.axis.Tick.set_picker() function in matplotlib.axis:
Example 1:
- Python3
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(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 * 3, amount**4, c = ranking**4, s = price**4, vmin = -3, vmax = 3, cmap ="Spectral") Tick.set_picker(ax, picker = 4) fig.suptitle('matplotlib.axis.Tick.set_picker() \ function Example', fontweight ="bold") plt.show() |
Output:
Example 2:
- Python3
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-') Tick.set_picker(ax, picker = True) fig.suptitle('matplotlib.axis.Tick.set_picker() \ function Example', fontweight ="bold") plt.show() |
Output:
