Matplotlib.axes.axes.get_legend()

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。

函数:Matplotlib.axes.axes.get_legend()

matplotlib库的Axes模块中的Axes.get_legend()函数用于返回图例实例，如果没有定义图例，则为None。

语法:Axes.get_legend(self)

参数:该方法不接受任何参数。

Return:该函数返回图例实例，如果没有定义图例，则返回None。

下面的例子演示了matplotlib.axes.axes.get_legend()函数在matplotlib.axes中的作用:

示例1

# Implementation of matplotlib function  
import matplotlib.pyplot as plt
import numpy as np
     
fig, ax = plt.subplots()
ax.plot([1, 6, 3, 8, 34, 13, 56, 67], color ="green")
  
x = ax.get_legend()
text ="Legend is present"
if x == None:
    text ="No legend present"
      
ax.text(2.5, 60, text, fontweight ="bold")
fig.suptitle('matplotlib.axes.Axes.get_legend() function\
 Example\n', fontweight ="bold")
fig.canvas.draw()
plt.show()

输出:

示例2

# Implementation of matplotlib function
import matplotlib.pyplot as plt
   
fig, (ax, ax1) = plt.subplots(1, 2)
# axes1
line1, = ax.plot([1, 2, 3], label ="Line 1",
                 color ="black", linewidth = 4, 
                 linestyle =':')
  
line2, = ax.plot([3, 2, 1], label ="Line 2", 
                 color ="green",
                 linewidth = 4)
   
first_legend = ax.legend(handles =[line1], 
                         loc ='upper center')
   
ax.add_artist(first_legend)
   
ax.legend(handles =[line2], loc ='lower center')
ax.set_title("Without get_legend function")
# axes1
line1, = ax1.plot([1, 2, 3], label ="Line 1",
                  color ="black", linewidth = 4, 
                  linestyle =':')
line2, = ax1.plot([3, 2, 1], label ="Line 2",
                  color ="green",
                  linewidth = 4)
   
first_legend = ax1.legend(handles =[line1],
                          loc ='upper center')
   
ax1.add_artist(first_legend)
   
ax1.legend(handles =[line2], 
           loc ='lower center')
ax1.get_legend().set_visible(False)
ax1.set_title("Using get_legend function")
fig.suptitle('matplotlib.axes.Axes.get_legend()\
function Example\n', fontweight ="bold")
   
plt.show()

输出: