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Matplotlib.axis.Tick.get_transformed_clip_path_and_affine() in Python

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  • Last Updated : 01 May, 2022
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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.get_transformed_clip_path_and_affine() Function

The Tick.get_transformed_clip_path_and_affine() function in axis module of matplotlib library is used to get the clip path with the non-affine part of its transformation applied, and the remaining affine part of its transformation.

Syntax: Tick.get_transformed_clip_path_and_affine(self) Parameters: This method does not accepts any parameter. Return value: This method return the clip path with the non-affine part of its transformation applied, and the remaining affine part of its transformation.

Below examples illustrate the matplotlib.axis.Tick.get_transformed_clip_path_and_affine() function in matplotlib.axis: Example 1: Image Used  

Python3




# Implementation of matplotlib function
from matplotlib.axis import Tick
import matplotlib.pyplot as plt  
import matplotlib.patches as patches  
import matplotlib.cbook as cbook  
          
       
with cbook.get_sample_data('image.PNG') as image_file:  
    image = plt.imread(image_file)  
          
fig, ax = plt.subplots()  
im = ax.imshow(image)  
patch = patches.Rectangle((10, 10), 100, 100,   
                          transform = ax.transData)  
      
val = Tick.get_transformed_clip_path_and_affine(im) 
ax.set_title("Value Return by get_transformed_clip_path_and_affine(): "
             + str(val)) 
   
fig.suptitle("""matplotlib.axis.Tick.get_transformed_clip_path_and_affine()\n
function Example\n""", fontweight ="bold")  
     
plt.show() 

Output: Example 2: 

Python3




# Implementation of matplotlib function
from matplotlib.axis import Tick
import numpy as np  
import matplotlib.cm as cm  
import matplotlib.pyplot as plt  
from matplotlib.path import Path  
from matplotlib.patches import PathPatch  
          
       
delta = 0.025
       
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) * 2
          
path = Path([[0, 1], [1, 0], [0, -1], [-1, 0], [0, 1]])  
patch = PathPatch(path, facecolor ='none')  
          
fig, ax = plt.subplots()  
ax.add_patch(patch)  
im = ax.imshow(Z,  
               interpolation ='bilinear',   
               cmap = cm.gray,  
               origin ='lower',  
               extent =[-3, 3, -3, 3],  
               clip_path = patch,  
               clip_on = True
     
# use of get_transformed_clip_path_and_affine() method 
val = Tick.get_transformed_clip_path_and_affine(im) 
print("Value Return by get_transformed_clip_path_and_affine(): "
for i in val:  
    print(i)
   
fig.suptitle("""matplotlib.axis.Tick.get_transformed_clip_path_and_affine()\n
function Example\n""", fontweight ="bold")  
     
plt.show() 

Output:

Value Return by get_transformed_clip_path_and_affine(): 
Path(array([[ 0.,  1.],
       [ 1.,  0.],
       [ 0., -1.],
       [-1.,  0.],
       [ 0.,  1.]]), None)
Affine2D(
    [[ 82.66666667   0.         328.        ]
     [  0.          61.6        237.6       ]
     [  0.           0.           1.        ]])

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