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.is_transform_set() Function
The Tick.is_transform_set() function in axis module of matplotlib library is used to get whether the Artist has an explicitly set transform.
Syntax: Tick.is_transform_set(self)
Parameters: This method does not accepts any parameter.
Return value: This method return whether the Artist has an explicitly set transform.
Below examples illustrate the matplotlib.axis.Tick.is_transform_set() function in matplotlib.axis:
Example 1:
Python3
# Implementation of matplotlib function from matplotlib.axis import Tick import matplotlib.pyplot as plt import numpy as np # create test data np.random.seed( 10 * * 7 ) data = [ sorted (np.random.normal( 0 , std, 100 )) for std in range ( 1 , 4 )] fig, ax1 = plt.subplots() val = ax1.violinplot(data) ax1.set_title( "Is artist is explicitly set transform : " + str (Tick.is_transform_set(ax1))) fig.suptitle('matplotlib.axis.Tick.is_transform_set() \ function Example', fontweight = "bold" ) plt.show() |
Output:
Example 2:
Python3
# Implementation of matplotlib function from matplotlib.axis import Tick import matplotlib.pyplot as plt import numpy as np from matplotlib.patches import Ellipse delta = 15.0 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: Tick.set_clip_box(e, ax.bbox) e.set_facecolor( "green" ) e.set_alpha( 0.05 ) ax.add_artist(e) plt.xlim( - 1 , 5 ) plt.ylim( - 1 , 5 ) ax.set_title( "Is artist is explicitly set transform : " + str (Tick.is_transform_set(ax))) fig.suptitle('matplotlib.axis.Tick.is_transform_set() \ function Example', fontweight = "bold" ) plt.show() |
Output: