Python中的 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 类包含大部分图形元素：Axis、Tick、Line2D、Text、Polygon 等，并设置坐标系。 Axes 的实例通过回调属性支持回调。

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()函数用于获取应用了其变换的非仿射部分以及其变换的剩余仿射部分的剪辑路径。

Syntax: Axes.get_transformed_clip_path_and_affine(self)

Parameters: This method does not accepts any parameter.

Returns: This method return the clip path with the non-affine part of its transformation applied, and the remaining affine part of its transformation.

下面的示例说明了 matplotlib.axes 中的 matplotlib.axes.Axes.get_transformed_clip_path_and_affine()函数：

示例 1：

使用的图像：

# 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.        ]])