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.Axis.get_clip_on() Function
The Axis.get_clip_on() function in axis module of matplotlib library is used to get whether the artist uses clipping.
Syntax: Axis.get_clip_on(self)
Parameters: This method does not accepts any parameter.
Return value: This method return the whether the artist uses clipping.
Below examples illustrate the matplotlib.axis.Axis.get_clip_on() function in matplotlib.axis:
Example 1:
Python3
# Implementation of matplotlib function from matplotlib.axis import Axis import matplotlib.pyplot as plt import numpy as np from matplotlib.patches import Ellipse delta = 45.0 angles = np.arange( 0 , 360 + delta, delta) ells = [Ellipse(( 2 , 2 ), 5 , 2 , a) for a in angles] fig, ax = plt.subplots() for e in ells: e.set_alpha( 0.1 ) ax.add_artist(e) ax.set_xlim( - 1 , 5 ) ax.set_ylim( - 1 , 5 ) print ( "Value Return by get_clip_on() : " , Axis.get_clip_on(ax)) fig.suptitle( """matplotlib.axis.Axis.get_clip_on() function Example\n""" , fontweight = "bold") plt.show() |
Output:
Value Return by get_clip_on() : True
Example 2:
Python3
# Implementation of matplotlib function from matplotlib.axis import Axis import matplotlib.pyplot as plt import matplotlib.patches as mpatches import matplotlib.transforms as mtransforms x0 = - 0.1 arrow_style = "simple, head_length = 15 , \ head_width = 30 , tail_width = 10 " rect_style = "simple, tail_width = 25" line_style = "simple, tail_width = 1" fig, ax = plt.subplots() trans = mtransforms.blended_transform_factory(ax.transAxes, ax.transData) y_tail = 5 y_head = 80 arrow1 = mpatches.FancyArrowPatch((x0, y_tail), (x0, y_head), arrowstyle = arrow_style, transform = trans) Axis.set_clip_on(arrow1, False ) ax.add_patch(arrow1) ax.set_xlim( 0 , 30 ) ax.set_ylim( 0 , 80 ) print ( "Value Return by get_clip_on() : " , Axis.get_clip_on(arrow1)) fig.suptitle( """matplotlib.axis.Axis.get_clip_on() function Example\n""" , fontweight = "bold") plt.show() |
Output:
Value Return by get_clip_on() : False