Python中的 Matplotlib.artist.Artist.get_picker()

Matplotlib是Python中的一个库，它是 NumPy 库的数值数学扩展。 Artist 类包含呈现为 FigureCanvas 的对象的 Abstract 基类。图中所有可见元素都是 Artist 的子类。

matplotlib.artist.Artist.get_picker() 方法

matplotlib 库的艺术家模块中的get_picker() 方法用于定义艺术家的拾取行为。

Syntax: Artist.get_picker(self)

Parameters: This method does not accept any parameters.

Returns: This method the picking behavior of the artist.

以下示例说明了 matplotlib 中的 matplotlib.artist.Artist.get_picker()函数：

示例 1：

# Implementation of matplotlib function
from matplotlib.artist import Artist
import numpy as np 
import matplotlib.pyplot as plt 
  
  
np.random.seed(19680801) 
    
volume = np.random.rayleigh(7, size = 40) 
amount = np.random.poisson(7, size = 40) 
ranking = np.random.normal(size = 40) 
price = np.random.uniform(1, 7, size = 40) 
       
fig, ax = plt.subplots() 
       
scatter = ax.scatter(volume, 
                     amount, 
                     c = ranking, 
                     s = price * 3, 
                     vmin = -3,  
                     vmax = 3, 
                     cmap = "Spectral") 
     
legend1 = ax.legend(*scatter.legend_elements(num = 5), 
                    loc = "upper left", 
                    title = "Ranking") 
    
ax.add_artist(legend1) 
      
ax.text(8, 8, "Value return : "
        + str(Artist.get_picker(ax)), 
        fontweight = "bold", 
        fontsize = 18) 
          
fig.suptitle('matplotlib.artist.Artist.get_picker() \
function Example', fontweight ="bold") 
  
plt.show()

输出：

示例 2：

# Implementation of matplotlib function
from matplotlib.artist import Artist
import numpy as np 
import matplotlib.pyplot as plt 
      
  
X = np.random.rand(10, 200) 
xs = np.mean(X, axis = 1) 
ys = np.std(X, axis = 1) 
    
fig = plt.figure() 
ax = fig.add_subplot(111) 
line, = ax.plot(xs, ys, 'go-', picker = 5) 
    
ax.set_picker(True) 
     
ax.text(0.48, 0.3, "Value return : " 
        +  str(Artist.get_picker(ax)), 
        fontweight = "bold", 
        fontsize = 18) 
          
fig.suptitle('matplotlib.artist.Artist.get_picker() \
function Example', fontweight ="bold") 
  
plt.show()

输出：