Matplotlib.axis.Axis.set_transform() function in Python

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.Axis.set_transform() Function

The Axis.set_transform() function in axis module of matplotlib library is used to set the artist transform. 

Syntax: Axis.set_transform(self, t) 

Parameters: This method accepts the following parameters. 

• t: This parameter is the Transform.

Return value: This method does not return any value. 

Below examples illustrate the matplotlib.axis.Axis.set_transform() function in matplotlib.axis:

Example 1:

Python3

# Implementation of matplotlib function
from matplotlib.axis import Axis
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms

delta = 0.5

x = y = np.arange(-2.0, 4.0, delta)
X, Y = np.meshgrid(x**2, y)

Z1 = np.exp(-X**2 - Y**2)
Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
Z = (Z1 - Z2)

transform = mtransforms.Affine2D().rotate_deg(30)
fig, ax = plt.subplots()

im = ax.imshow(Z, interpolation ='none',
               origin ='lower',
               extent =[-2, 4, -3, 2],
               clip_on = True)

trans_data = transform + ax.transData
Axis.set_transform(im, trans_data)

x1, x2, y1, y2 = im.get_extent()
ax.plot([x1, x2, x2, x1, x1],
        [y1, y1, y2, y2, y1],
        "ro-",
        transform = trans_data)

ax.set_xlim(-5, 5)
ax.set_ylim(-4, 4)

fig.suptitle('matplotlib.axis.Axis.set_transform() \
function Example\n', fontweight ="bold")

plt.show()

Output:

Example 2:

Python3

# Implementation of matplotlib function
from matplotlib.axis import Axis
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)
Axis.set_transform(col, trans)

ax1.add_collection(col, autolim = True)
col.set_color(colors)

fig.suptitle('matplotlib.axis.Axis.set_transform() \
function Example\n', fontweight ="bold")

plt.show()

Output: