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_pads() method
The get_constrained_layout_pads() method of figure module of matplotlib library is used to get the padding for constrained_layout.
Syntax: get_constrained_layout_pads(self, relative=False)
Parameters: This method does not accept any parameters.
Returns: This method returns a list of w_pad, h_pad in inches and wspace and hspace as fractions of the subplot.
Below examples illustrate the matplotlib.figure.Figure.get_constrained_layout_pads() 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_pads() " )
w = list (fig.get_constrained_layout_pads())
print ( "w_pad :" , w[ 0 ])
print ( "h_pad :" , w[ 1 ])
print ( "wspace :" , w[ 2 ])
print ( "hspace :" , w[ 3 ])
fig.suptitle('matplotlib.figure.Figure.get_constrained_layout_pads() \ function Example\n\n', fontweight = "bold" )
plt.show() |
Output:
Value return by get_constrained_layout_pads() w_pad : 0.04167 h_pad : 0.04167 wspace : 0.02 hspace : 0.02
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_pads() " )
w = list (fig.get_constrained_layout_pads())
print ( "w_pad :" , w[ 0 ])
print ( "h_pad :" , w[ 1 ])
print ( "wspace :" , w[ 2 ])
print ( "hspace :" , w[ 3 ])
fig.suptitle('matplotlib.figure.Figure.get_constrained_layout_pads() \ function Example\n\n', fontweight = "bold" )
plt.show() |
Output:
Value return by get_constrained_layout_pads() w_pad : 0.04167 h_pad : 0.04167 wspace : 0.02 hspace : 0.02