Matplotlib.axis.Tick.get_contains() in Python

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 is used for working with the broader SciPy stack.

matplotlib.axis.Tick.get_contains() Function

The Tick.get_contains() function in axis module of matplotlib library is used to get the custom containing the function of the artist.

Syntax: Tick.get_contains(self) 

Parameters: This method does not accepts any parameter. 

Return value: This method return the custom contains function of the artist.

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

Example 1:

Python3

# Implementation of matplotlib function
from matplotlib.axis import Tick
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
import numpy as np
from numpy.random import rand


fig, ax2 = plt.subplots()

ax2.bar(range(10), rand(10), picker=True)

for label in ax2.get_xticklabels():
    label.set_picker(True)


def onpick1(event):

    if isinstance(event.artist, Line2D):
        thisline = event.artist
        xdata = thisline.get_xdata()
        ydata = thisline.get_ydata()
        ind = event.ind
        print('onpick1 line:',
              np.column_stack([xdata[ind],
                               ydata[ind]]))

    elif isinstance(event.artist, Rectangle):
        patch = event.artist
        print('onpick1 patch:', patch.get_path())

    elif isinstance(event.artist, Text):
        text = event.artist
        print('onpick1 text:', text.get_text())


Tick.set_contains(ax2, picker=onpick1)

ax2.text(0.5, 0.8,
         "Value Return : "
         + str(Tick.get_contains(ax2)),
         fontweight="bold", fontsize=10)

fig.suptitle("""matplotlib.axis.Tick.get_contains()
function Example\n""", fontweight="bold")

plt.show()

Output:

Example 2:

Python3

# Implementation of matplotlib function
from matplotlib.axis import Tick
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
import numpy as np
from numpy.random import rand


fig, ax = plt.subplots()
ax.plot(rand(100), rand(100), 'o')


def line_picker(line, mouseevent):

    if mouseevent.xdata is None:
        return False, dict()

    xdata = line.get_xdata()
    ydata = line.get_ydata()
    maxd = 0.05
    d = np.sqrt(
        (xdata - mouseevent.xdata)**2 + (ydata - mouseevent.ydata)**2)

    ind, = np.nonzero(d <= maxd)

    if len(ind):

        pickx = xdata[ind]
        picky = ydata[ind]
        props = dict(ind=ind, pickx=pickx, picky=picky)
        return True, props

    else:
        return False, dict()


Tick.set_contains(ax, picker=line_picker)

ax.text(0.1, 0.8,
        "Value Return : "
        + str(Tick.get_contains(ax)),
        fontweight="bold", fontsize=10)

fig.suptitle("""matplotlib.axis.Tick.get_contains()
function Example\n""", fontweight="bold")

plt.show()

Output: