Matplotlib.axes.Axes.get_ybound() in Python

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Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.

matplotlib.axes.Axes.get_ybound() Function

The Axes.get_ybound() function in axes module of matplotlib library is used to return the lower and upper numerical bounds of the y-axis in increasing order

Syntax: Axes.get_ybound(self)

Parameters: This method does not accepts any parameters.

Returns:This method returns the following

lower, upper :This returns the current lower and upper y-axis bounds.

Note: This function can be used in place of get_ylim in various conditions.

Below examples illustrate the matplotlib.axes.Axes.get_ybound() function in matplotlib.axes:

Example 1:

# Implementation of matplotlib function 
import numpy as np 
import matplotlib.pyplot as plt 
     
fig, (ax, ax1) = plt.subplots(1, 2) 
t = 3*(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_ybound() 
ax.set_title('Original Window', 
             fontsize = 10, fontweight ='bold') 
    
ax1.plot(x, y, 'g') 
ax1.set_ybound(1.5 * lower, 0.5 * upper) 
ax1.set_title('Using get_ybound() function', 
             fontsize = 10, fontweight ='bold') 
fig.suptitle('matplotlib.axes.Axes.get_ybound() Example\n', 
             fontsize = 14, fontweight ='bold') 
plt.show() 

Output:

Example 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() 