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Matplotlib.axes.Axes.get_transform() in Python

  • Last Updated : 30 Apr, 2020

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

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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)
    ot = mtransforms.offset_copy(l.get_transform(),
                                 x = 4.0, y =-6.0,
                                 units ='points')
fig.suptitle('matplotlib.axes.Axes.get_transform() \
function Example', fontweight ="bold" 


Example 2:

# 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)
ax1.add_collection(col, autolim = True)
print("Value Return by get_transform() :\n",
fig.suptitle('matplotlib.axes.Axes.get_transform() \
function Example', fontweight ="bold" 


Value Return by get_transform() :
    [[1.38888889 0.         0.        ]
     [0.         1.38888889 0.        ]
     [0.         0.         1.        ]])

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