Matplotlib.axes.Axes.get_transform() in Python
Last Updated :
12 Jul, 2025
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:
Python3
# 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()
Example 2:
Python3
# 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()
Value Return by get_transform() :
Affine2D(
[[1.38888889 0. 0. ]
[0. 1.38888889 0. ]
[0. 0. 1. ]])
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