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Python Matplotlib.axes.Axes.get_xbound()用法及代码示例


Matplotlib是Python中的一个库,它是数字的-NumPy库的数学扩展。轴类包含大多数图形元素:Axis,Tick,Line2D,Text,Polygon等,并设置坐标系。 Axes实例通过callbacks属性支持回调。

matplotlib.axes.Axes.get_xbound()函数

matplotlib库的axiss模块中的Axes.get_xbound()函数用于按递增顺序返回x轴的上下数值边界

用法: Axes.get_xbound(self)


参数:此方法不接受任何参数。

返回:此方法返回以下内容

  • lower, upper:这将返回当前的x轴上下边界。

注意:可以在各种条件下代替get_xlim使用此函数。

以下示例说明了matplotlib.axes中的matplotlib.axes.Axes.get_xbound()函数:

范例1:

# Implementation of matplotlib function 
from matplotlib.widgets import Cursor 
import numpy as np 
import matplotlib.pyplot as plt 
    
fig, [ax, ax1] = plt.subplots(2, 1) 
t = 4*(np.random.rand(2, 100) - .5) 
x = np.cos(2 * np.pi * t) 
y = np.sin(2 * np.pi * t) 
   
ax.plot(x, y, 'g') 
lower, upper = ax.get_xbound() 
ax.set_title('matplotlib.axes.Axes.get_xbound()\ 
 Example\n Original Window', 
             fontsize = 14, fontweight ='bold') 
   
ax1.plot(x, y, 'g') 
ax1.set_xbound(1.5 * lower, 0.5 * upper) 
ax1.set_title('Window After Using get_xbound() function', 
             fontsize = 14, fontweight ='bold') 
plt.show()

输出:

范例2:

import numpy as np 
import matplotlib.pyplot as plt 
   
# Fixing random state for 
# reproducibility 
np.random.seed(19680801) 
   
# the random data 
x = np.random.randn(1000) 
y = np.random.randn(1000) 
   
# definitions for the axes 
left, width = 0.1, 0.65
bottom, height = 0.1, 0.65
spacing = 0.005
   
   
rect_scatter = [left, bottom, 
                width, height] 
  
rect_histx = [left, 
              bottom + height + spacing, 
              width, 0.2] 
  
rect_histy = [left + width + spacing, 
              bottom, 0.2, height] 
   
# start with a rectangular Figure 
plt.figure() 
   
ax_scatter = plt.axes(rect_scatter) 
ax_scatter.tick_params(direction ='in', 
                       bottom = True,  
                       right = True) 
  
ax_histx = plt.axes(rect_histx) 
ax_histx.tick_params(direction ='in', 
                     labeltop = True) 
  
ax_histy = plt.axes(rect_histy) 
ax_histy.tick_params(direction ='in', 
                     labelleft = True) 
  
   
# the scatter plot:
ax_scatter.scatter(2 * x, y * 2, color ="green") 
   
# now determine nice limits by hand:
binwidth = 0.05
lim = np.ceil(np.abs([x, y]).max() / binwidth) * binwidth 
ax_scatter.set_xbound((-0.5 * lim, 0.5 * lim)) 
ax_scatter.set_ybound((-0.25 * lim, 0.25 * lim)) 
   
bins = np.arange(-lim, lim + binwidth, binwidth) 
ax_histx.hist(x, bins = bins, 
              color ="green") 
ax_histy.hist(y, bins = bins,  
              color ="green",  
              orientation ='horizontal') 
   
ax_histx.set_xbound(ax_scatter.get_xbound()) 
ax_histy.set_ybound(ax_scatter.get_ybound()) 
   
plt.show()

输出:




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注:本文由纯净天空筛选整理自SHUBHAMSINGH10大神的英文原创作品 Matplotlib.axes.Axes.get_xbound() in Python。非经特殊声明,原始代码版权归原作者所有,本译文未经允许或授权,请勿转载或复制。