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_contains() Function
The Tick.set_contains() function in axis module of matplotlib library is used to define a custom contains test for the artist.
Syntax: Tick.Axis.set_contains(self, picker)
Parameters: This method accepts the following parameters.
- picker: This parameter is the custom picker function to evaluate if an event is within the artist.
Return value: This method does not return any value.
Below examples illustrate the matplotlib.axis.Tick.set_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 from matplotlib.patches import Rectangle from matplotlib.text import Text from matplotlib.image import AxesImage import numpy as np from numpy.random import rand fig, (ax1, ax2) = plt.subplots(2, 1) ax1.set_ylabel('ylabel', picker = True, bbox = dict(facecolor ='red')) line, = ax1.plot(rand(100), 'go-') 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) fig.canvas.mpl_connect('pick_event', onpick1) fig.suptitle('matplotlib.axis.Tick.set_contains() \ function Example', fontweight ="bold") plt.show() |
Output:
onpick1 text: ylabel
onpick1 patch: Path(array([[0., 0.],
[1., 0.],
[1., 1.],
[0., 1.],
[0., 0.]]), array([ 1, 2, 2, 2, 79], dtype=uint8))
onpick1 patch: Path(array([[0., 0.],
[1., 0.],
[1., 1.],
[0., 1.],
[0., 0.]]), array([ 1, 2, 2, 2, 79], dtype=uint8))
Example 2:
Python3
# Implementation of matplotlib function from matplotlib.axis import Tick import matplotlib.pyplot as plt from matplotlib.lines import Line2D from matplotlib.patches import Rectangle from matplotlib.text import Text from matplotlib.image import AxesImage import numpy as np from numpy.random import rand 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() def onpick2(event): print('Result :', event.pickx, event.picky) fig, ax = plt.subplots() ax.plot(rand(100), rand(100), 'o') Tick.set_contains(ax, picker = line_picker) fig.canvas.mpl_connect('pick_event', onpick2) fig.suptitle('matplotlib.axis.Tick.set_contains() \ function Example', fontweight ="bold") plt.show() |
Output:
