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Matplotlib.figure.Figure.init_layoutbox() in Python

Last Updated : 03 May, 2020
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Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The figure module provides the top-level Artist, the Figure, which contains all the plot elements. This module is used to control the default spacing of the subplots and top level container for all plot elements.

matplotlib.figure.Figure.init_layoutbox() method

The init_layoutbox() method figure module of matplotlib library is used to initialize the layoutbox for use in constrained_layout.
Syntax: init_layoutbox(self) Parameters: This method does not accept any parameters. Returns: This method does not returns any value.
Below examples illustrate the matplotlib.figure.Figure.init_layoutbox() function in matplotlib.figure: Example 1: Python3 1==
# Implementation of matplotlib function 
import matplotlib.pyplot as plt 
import numpy as np 
import matplotlib.gridspec as gridspec 
  
fig = plt.figure() 
gs = gridspec.GridSpec(2, 2) 
  
for i in range(2): 
    ax = fig.add_subplot(gs[1, i]) 
    ax.set_ylabel('Y label') 
    ax.set_xlabel('X label') 
    if i == 0: 
        for tick in ax.get_xticklabels(): 
            tick.set_rotation(45) 
  
fig.init_layoutbox() 
  
fig.suptitle("""matplotlib.figure.Figure.init_layoutbox()
function Example\n\n""", fontweight ="bold") 
  
plt.show() 
Output: Example 2: Python3 1==
# Implementation of matplotlib function 
import numpy as np 
import matplotlib.pyplot as plt 
  
  
fig = plt.figure() 
fig.subplots_adjust(top = 0.8) 
ax1 = fig.add_subplot(211) 
  
t = np.arange(0.0, 1.0, 0.01) 
s = np.sin(2 * np.pi * t) 
line, = ax1.plot(t, s, color ='green', lw = 2) 
  
np.random.seed(19680801) 
  
ax2 = fig.add_axes([0.15, 0.1, 0.7, 0.3]) 
n, bins, patches = ax2.hist(np.random.randn(1000), 50, 
                            facecolor ='yellow', 
                            edgecolor ='yellow') 
  
fig.init_layoutbox() 
  
fig.suptitle("""matplotlib.figure.Figure.init_layoutbox()
function Example\n\n""", fontweight ="bold") 
  
plt.show() 
Output:

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