Matplotlib.axes.Axes.get_transform() in Python

# 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() 

# Implementation of matplotlib function  
import matplotlib.pyplot as plt
from matplotlib import collections, colors, transforms
import numpy as np


nverts = 50
npts = 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()