Python中的 Matplotlib.artist.Artist.pickable()

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.pickable() 方法

matplotlib 库的艺术家模块中的pickable() 方法用于返回艺术家是否可挑选。

Syntax: Artist.pickable(self)

Parameters: This method does not accept any parameters.

Returns: This method return whether the artist is pickable.

下面的示例说明了 matplotlib 中的 matplotlib.artist.Artist.pickable()函数：

示例 1：

# Implementation of matplotlib function
from matplotlib.artist import Artist
import numpy as np 
np.random.seed(19680801) 
import matplotlib.pyplot as plt 
     
  
volume = np.random.rayleigh(27, size = 40) 
amount = np.random.poisson(10, size = 40) 
ranking = np.random.normal(size = 40) 
price = np.random.uniform(1, 10, size = 40) 
     
fig, ax = plt.subplots() 
     
scatter = ax.scatter(volume * 2, amount * 3, 
                     c = ranking * 3,  
                     s = 0.3*(price * 3)**2, 
                     vmin = -4, vmax = 4,  
                     cmap = "Spectral") 
    
legend1 = ax.legend(*scatter.legend_elements(num = 5), 
                    loc ="upper left", 
                    title ="Ranking") 
    
ax.add_artist(legend1) 
    
ax.text(60, 30, "Value return : "
        + str(Artist.pickable(ax)),  
        fontweight ="bold",  
        fontsize = 18) 
          
fig.suptitle('matplotlib.artist.Artist.pickable() 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 
import matplotlib.cbook as cbook 
     
  
np.random.seed(10**7) 
data = np.random.lognormal(size =(10, 4), 
                           mean = 4.5, 
                           sigma = 4.75) 
    
labels = ['G1', 'G2', 'G3', 'G4'] 
     
result = cbook.boxplot_stats(data,  
                             labels = labels,  
                             bootstrap = 1000) 
     
for n in range(len(result)): 
    result[n]['med'] = np.median(data) 
    result[n]['mean'] *= 0.1
    
fig, axes1 = plt.subplots() 
axes1.bxp(result) 
    
axes1.text(2, 30000, 
           "Value return : " 
           + str(Artist.pickable(axes1)),  
           fontweight ="bold") 
          
fig.suptitle('matplotlib.artist.Artist.pickable()\
 function Example', fontweight ="bold") 
  
plt.show()

输出：