Python中的 Matplotlib.axis.Tick.set_clip_path()函数

Matplotlib是Python中的一个库，它是 NumPy 库的数值数学扩展。它是Python中用于二维数组图的惊人可视化库，用于处理更广泛的 SciPy 堆栈。

Matplotlib.axis.Tick.set_clip_path()函数

matplotlib库的axis模块中的tick.set_clip_path()函数用于设置艺术家的剪辑路径。

Syntax: Tick.set_clip_path(self, path, transform=None) 
 

Parameters: This method accepts the following parameters. 

• path: This parameter is the clip path.
• transform: This parameter in which Path is converted to a TransformedPath using transform.

Return value: This method does not return any value. 

下面的示例说明了 matplotlib.axis 中的 matplotlib.axis.Tick.set_clip_path()函数：
示例 1：
输入图像

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('geeksforgeeks-logo1.PNG') as image_file:  
    image = plt.imread(image_file)  
        
fig, ax = plt.subplots()  
ax.imshow(image)  
patch = patches.Rectangle((10, 10),  
                          560,  
                          500,   
                          transform = ax.transData)  
     
ax.set_clip_path(patch) 
  
fig.suptitle('matplotlib.axis.Tick.set_clip_path() \
function Example', fontweight ="bold")  
     
plt.show()

输出：

示例 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)  
        
ax.imshow(Z,  
               interpolation ='bilinear',   
               cmap = cm.gray,  
               origin ='lower',   
               extent =[-3, 3, -3, 3],  
               clip_path = patch,   
               clip_on = True)  
ax.set_clip_path(patch)  
  
fig.suptitle('matplotlib.axis.Tick.set_clip_path() \
function Example', fontweight ="bold")  
     
plt.show() 

输出：