Matplotlib.axes.Axes.get_transform() in Python

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.
matplotlib.axes.Axes.get_transform() Function
The Axes.get_transform() function in axes module of matplotlib library is used to get the Transform instance used by this artist
Syntax: Axes.get_transform(self)
Parameters: This method does not accepts any parameter.
Returns: This method return the Transform instance used by this artist
Below examples illustrate the matplotlib.axes.Axes.get_transform() function in matplotlib.axes:
Example 1:
# Implementation of matplotlib function  import numpy as np  import matplotlib.pyplot as plt import matplotlib.transforms as mtransforms     fig, ax = plt.subplots()  l1, = ax.plot([0.1, 0.5, 0.9], [0.1, 0.9, 0.5], "bo-") l2, = ax.plot([0.1, 0.5, 0.9], [0.5, 0.2, 0.7], "ro-")    for l in [l1, l2]:     xx = l.get_xdata()     yy = l.get_ydata()     shadow, = ax.plot(xx, yy)     shadow.update_from(l)            ot = mtransforms.offset_copy(l.get_transform(),                                  ax.figure,                                  x = 4.0, y =-6.0,                                  units ='points')        shadow.set_transform(ot)     fig.suptitle('matplotlib.axes.Axes.get_transform() \ function Example', fontweight ="bold")    plt.show()   | 
Output:
Example 2:
# Implementation of matplotlib function   import matplotlib.pyplot as plt from matplotlib import collections, colors, transforms import numpy as np     nverts = 50npts = 100   r = np.arange(nverts) theta = np.linspace(0, 2 * np.pi, nverts)   xx = r * np.sin(theta) yy = r * np.cos(theta)   spiral = np.column_stack([xx, yy])    rs = np.random.RandomState(19680801)    xyo = rs.randn(npts, 2)    colors = [colors.to_rgba(c)           for c in plt.rcParams['axes.prop_cycle'].by_key()['color']]    fig, ax1 = plt.subplots()    col = collections.RegularPolyCollection(     7, sizes = np.abs(xx) * 10.0,      offsets = xyo,     transOffset = ax1.transData)   trans = transforms.Affine2D().scale(fig.dpi / 72.0) col.set_transform(trans)    ax1.add_collection(col, autolim = True) col.set_color(colors)   print("Value Return by get_transform() :\n",        col.get_transform())         fig.suptitle('matplotlib.axes.Axes.get_transform() \ function Example', fontweight ="bold")    plt.show()   | 
Output:
Value Return by get_transform() :
 Affine2D(
    [[1.38888889 0.         0.        ]
     [0.         1.38888889 0.        ]
     [0.         0.         1.        ]])
				
					



