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.get_constrained_layout() method
The get_constrained_layout() method of figure module of matplotlib library is used to get whether the constrained layout is being used.
Syntax: get_constrained_layout(self)
Parameters: This method does not accept any parameters.
Returns: This method returns whether the constrained layout is being used.
Below examples illustrate the matplotlib.figure.Figure.get_constrained_layout() function in matplotlib.figure:
Example 1:
# Implementation of matplotlib function import matplotlib.pyplot as plt from matplotlib.lines import Line2D import numpy as np from numpy.random import rand fig, ax2 = plt.subplots() ax2.bar( range ( 10 ), rand( 10 ), picker = True ) for label in ax2.get_xticklabels(): label.set_picker( True ) def onpick1(event): if isinstance (event.artist, Line2D): thisline = event.artist xdata = thisline.get_xdata() ydata = thisline.get_ydata() ind = event.ind print ( 'onpick1 line:' , np.column_stack([xdata[ind], ydata[ind]])) elif isinstance (event.artist, Rectangle): patch = event.artist print ( 'onpick1 patch:' , patch.get_path()) elif isinstance (event.artist, Text): text = event.artist print ( 'onpick1 text:' , text.get_text()) print ( "Value return by get_constrained_layout() :" , fig.get_constrained_layout()) fig.suptitle('matplotlib.figure.Figure.get_constrained_layout() \ function Example\n\n', fontweight = "bold" ) plt.show() |
Output:
Value return by get_constrained_layout() : False
Example 2:
# Implementation of matplotlib function import matplotlib.pyplot as plt import numpy as np from matplotlib.patches import Ellipse NUM = 200 ells = [Ellipse(xy = np.random.rand( 2 ) * 10 , width = np.random.rand(), height = np.random.rand(), angle = np.random.rand() * 360 ) for i in range (NUM)] fig, ax = plt.subplots(subplot_kw = { 'aspect' : 'equal' }) for e in ells: ax.add_artist(e) e.set_clip_box(ax.bbox) e.set_alpha(np.random.rand()) e.set_facecolor(np.random.rand( 4 )) ax.set_xlim( 3 , 7 ) ax.set_ylim( 3 , 7 ) print ( "Value return by get_constrained_layout() :" , fig.get_constrained_layout()) fig.suptitle('matplotlib.figure.Figure.get_constrained_layout() \ function Example\n\n', fontweight = "bold" ) plt.show() |
Output:
Value return by get_constrained_layout() : False