Matplotlib – Figure

The matplotlib.figure is a top-level container for all the plot elements.

Parameters:

• figsize: figure dimension (width, height) in inches.
• dpi : Dots per inch.
• facecolor : The figure patch facecolor. default – White
• edgecolor : The figure patch edge color. Default – White
• linewidth : The linewidth of the frame
• frameon : bool (True/False) Defalut-True. If False, suppress drawing the figure background patch.
• subplotpars : Subplot parameters. if not given the default subplot parameters are used.
• tight_layout : bool or dict. Defalut-False.
  • • If False use subplotpars.
    • If True adjust subplot parameters using tight_layout with default padding.
    • When providing a dict containing the keys pad, w_pad, h_pad, and rect, the default tight_layout paddings will be overridden.
• constrained_layout : bool(True/False). Default-False.
  • • If True, use constrained layout to adjust the positioning of plot elements

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Figure.add_subplot():

The figure.add_subplot() method add the subplot to figure. You can add subplot with different ways like:

add_subplot(nrows, ncols, index, **kwargs)
add_subplot(pos, **kwargs)
add_subplot(ax)
add_subplot()

Parameters:

• Either a 3-digit integer or three separate integers describing the position of the subplot.
  • • In the above first syntax nrows, ncols and index define the position of the subplot.
    • In the second syntax, pos defines the position of the subplot, which consists of 3 digit integer number, the first digit define the number of rows, the second digit defines the number of columns and the last digit define the index of the subplot.

Different ways to use add_subplot():

fig = plt.figure(figsize=(10,5))
fig.add_subplot(221)
 
# equivalent but more general
ax1 = fig.add_subplot(2, 2, 1)
 
# add a subplot with no frame
ax2 = fig.add_subplot(222, frameon=False)
 
# add a red subplot that share the x-axis with ax1
fig.add_subplot(223, sharex=ax1, facecolor='red')
 
fig.delaxes(ax2)  # delete x2 from the figure
 
fig.add_subplot(ax2) # add x2 to the figure again

Example

import numpy as np
import matplotlib.pyplot as plt
np.random.seed(12)
 
x = np.random.rand(10)
y = np.random.rand(10)
z = np.sqrt(x**2 + y**2)
 
fig = plt.figure(figsize=(10,8),facecolor='cyan')
fig.suptitle("Example of Subplot")
fig.add_subplot(221)
plt.scatter(x, y, s=80, c=z, marker=">")
plt.title("subplot-1")
fig.add_subplot(222)
plt.scatter(x, y, s=80, c=z, marker="+")
plt.title("subplot-2")
fig.add_subplot(223)
plt.scatter(x, y, s=80, c=z, marker='.')
plt.title("subplot-3")
fig.add_subplot(224)
plt.scatter(x, y, s=80, c=z, marker="*")
plt.title("subplot-4")
plt.show()

This produces the following result:

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Figure.Subplots()

The figure.subplots() method add a set of subplots to the figure. This method is convenient to create common layouts of subplots in a single call.

Example. You can generate the same above plot using figure.subplots() method.

import numpy as np
import matplotlib.pyplot as plt
np.random.seed(12)
 
x = np.random.rand(10)
y = np.random.rand(10)
z = np.sqrt(x**2 + y**2)
 
fig = plt.figure(figsize=(10,8),facecolor='cyan')
axs = fig.subplots(2,2)
fig.suptitle("Example of Subplot")
 
axs[0,0].scatter(x, y, s=80, c=z, marker=">")
axs[0,0].set_title('subplot-1')
axs[0,1].scatter(x, y, s=80, c=z, marker="+")
axs[0,1].set_title('subplot-2')
axs[1,0].scatter(x, y, s=80, c=z, marker='.')
axs[1,0].set_title('subplot-3')
axs[1,1].scatter(x, y, s=80, c=z, marker="*")
axs[1,1].set_title('subplot-4')
plt.show()

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