Matplotlib.axes.Axes.get_transformed_clip_path_and_affine()

Matplotlib是Python中的一个库，它是NumPy库的数值-数学扩展。Axes包含了大多数图形元素:Axis、Tick、Line2D、Text、Polygon等，并设置坐标系。Axes的实例通过callbacks属性支持回调。

Matplotlib.axes.Axes.get_transformed_clip_path_and_affine() 函数

matplotlib库的Axes模块中的Axes.get_transformed_clip_path_and_affine()函数用于获得剪辑路径，其中应用了其变换的非仿射部分，以及其变换的剩余仿射部分。

语法:Axes.get_transformed_clip_path_and_affine(self)

参数:该方法不接受任何参数。

返回:该方法返回应用了转换的非仿射部分和转换的其余仿射部分的剪辑路径。

下面的例子说明了matplotlib.axes.axes.get_transformed_clip_path_and_affine()函数在matplotlib.axes中的作用:

示例1

# Implementation of matplotlib function
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import matplotlib.cbook as cbook
     
  
with cbook.get_sample_data('loggf.PNG') as image_file:
    image = plt.imread(image_file)
     
fig, ax = plt.subplots()
im = ax.imshow(image)
patch = patches.Rectangle((0, 0), 260, 200, 
                          transform = ax.transData)
   
ax.set_title("Value Return by get_transformed_clip_path_and_affine(): "
             +str(im.get_transformed_clip_path_and_affine()))
       
fig.suptitle('matplotlib.axes.Axes.get_transformed_clip_path_and_affine()\
 function Example\n\n', fontweight ="bold")
  
plt.show()

输出:

示例2

# Implementation of matplotlib function
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)
  
print("Value Return by get_transformed_clip_path_and_affine(): ")
  
for i in im.get_transformed_clip_path_and_affine():
    print(i)
       
fig.suptitle('matplotlib.axes.Axes.get_transformed_clip_path_and_affine()\
 function Example\n\n', fontweight ="bold")
  
plt.show()

输出:

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.        ]])