Matplotlib.axes.Axes.set_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.set_transform() Function

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

Syntax: Axes.set_transform(self, t) Parameters: This method accepts only one parameters.

t : This parameter is the Transform.

Returns: This method does not return any value.

Below examples illustrate the matplotlib.axes.Axes.set_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

delta = 0.25
x = y = np.arange(-3.0, 3.0, delta)
X, Y = np.meshgrid(x, 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
im.set_transform(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.axes.Axes.set_transform() \
function Example\n\n', fontweight ="bold")

plt.show()

Output:

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

fig.canvas.draw()

plt.show()