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

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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.Tick.set_transform() Function

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

Syntax: Tick.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.Tick.set_transform() function in matplotlib.axis:
Example 1:

Python3

# Implementation of matplotlib function
from matplotlib.axis import Tick
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  
Tick.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(-3, 6)  
ax.set_ylim(-5, 5)
  
fig.suptitle('matplotlib.axis.Tick.set_transform() \
function Example', fontweight ="bold")  
     
plt.show() 

                    

Output: 
 


Example 2:

Python3

# Implementation of matplotlib function
from matplotlib.axis import Tick
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)  
Tick.set_transform(col, trans)   
       
ax1.add_collection(col, autolim = True)  
col.set_color(colors) 
  
fig.suptitle('matplotlib.axis.Tick.set_transform() \
function Example', fontweight ="bold")  
     
plt.show() 

                    

Output: 
 


 



Last Updated : 10 Jun, 2020
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