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

matplotlib 库的轴模块中的Axis.remove_overlapping_locs函数用于修剪与主要代码位置重叠的次要代码位置。

Syntax: Axis.remove_overlapping_locs
 

Parameters: This method accepts the following parameters. 

• formatter: This parameter is the locator.

Return value: This method does not returns any value. 

下面的示例说明了 matplotlib.axis 中的 matplotlib.axis.Axis.remove_overlapping_locs函数：

示例 1：

Python3

# Implementation of matplotlib function 
from matplotlib.axis import Axis
import matplotlib.pyplot as plt 
from matplotlib.ticker import MultipleLocator, ScalarFormatter 
     
fig, ax = plt.subplots() 
ax.plot([0, 5, 10, 15, 20], [3, 2, 1, 2, 4]) 
     
Axis.set_minor_locator(ax.xaxis, MultipleLocator(1)) 
Axis.set_minor_formatter(ax.xaxis, ScalarFormatter())
Axis.set_major_locator(ax.xaxis, MultipleLocator(4)) 
     
ax.tick_params(axis ='both', which ='major',  
               labelsize = 14, pad = 12,  
               colors ='g') 
     
ax.tick_params(axis ='both', which ='minor', 
               labelsize = 8, colors ='b')
ax.xaxis.remove_overlapping_locs
    
plt.title("Matplotlib.axis.Axis.remove_overlapping_locs \
Example", fontsize = 12, fontweight ='bold') 
  
plt.show()

输出：

示例 2：

Python3

# Implementation of matplotlib function 
from matplotlib.axis import Axis
import matplotlib.pyplot as plt 
import matplotlib.ticker as ticker
from matplotlib.ticker import MultipleLocator, ScalarFormatter
     
     
x = [0, 5, 9, 10, 15] 
y = [0, 1, 2, 3, 4] 
     
tick_spacing = 1
     
fig, ax = plt.subplots(1, 1) 
ax.plot(x, y)
  
Axis.set_major_locator(ax.xaxis, 
                       ticker.MultipleLocator(3))
Axis.set_minor_locator(ax.xaxis, 
                       ticker.MultipleLocator(tick_spacing))
Axis.set_minor_formatter(ax.xaxis, ScalarFormatter())
ax.xaxis.remove_overlapping_locs
    
plt.title("Matplotlib.axis.Axis.remove_overlapping_locs \
Example", fontsize = 12, fontweight ='bold') 
  
plt.show()

输出：