Python中的 Matplotlib.axis.Axis.pickable()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.Axis.pickable()函数

matplotlib 库的轴模块中的Axis.pickable()函数用于返回艺术家是否可拾取。

Syntax: Axis.pickable(self) 

Parameters: This method does not accept any parameters. 

Return value: This method return whether the artist is pickable. 

下面的示例说明了 matplotlib.axis 中的 matplotlib.axis.Axis.pickable()函数：
示例 1：

Python3

# Implementation of matplotlib function
from matplotlib.axis import Axis
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(Axis.pickable(ax)),   
        fontweight ="bold",   
        fontsize = 18)
  
fig.suptitle('matplotlib.axis.Axis.pickable() \
function Example\n', fontweight ="bold")  
    
plt.show()

输出：

示例 2：

Python3

# Implementation of matplotlib function
from matplotlib.axis import Axis
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(Axis.pickable(axes1)),   
           fontweight ="bold")  
  
fig.suptitle('matplotlib.axis.Axis.pickable() \
function Example\n', fontweight ="bold")  
    
plt.show() 

输出：