Matplotlib subplots and axes objects

Subplots

The subplot function of the matplotlib module is a tool for plotting several graphs on a single figure. By calling subplot(n,m,k) we subdidive the figure into n rows and m columns and specify that plotting should be done on the subplot number k. Subplots are numbered row by row, from left to right.

import matplotlib.pyplot as plt
import numpy as np
from math import pi

plt.figure(figsize=(8,4))       # set dimensions of the figure
x = np.linspace(0,2*pi, 100)
for i in range(1,7):
    plt.subplot(2,3, i)         # create subplots on a grid with 2 rows and 3 columns
    plt.xticks([])              # set no ticks on x-axis
    plt.yticks([])              # set no ticks on y-axis
    plt.plot(np.sin(x), np.cos(i*x))
    plt.title('subplot' + '(2,3,' + str(i) + ')')

plt.show()

Note. If the numbers i, j, k are all smaller than 10 we can specify a subplot by typing subplot(ijk) instead of subplot(i,j,k):

plt.figure(figsize=(8,4))
x = np.linspace(0,2*pi, 100)

plt.subplot(231)
plt.xticks([])
plt.yticks([])
plt.plot(np.sin(x), np.cos(x))
plt.title('subplot(231)')

plt.subplot(233)
plt.xticks([])
plt.yticks([])
plt.plot(np.sin(x), np.cos(3*x))
plt.title('subplot(233)')

plt.subplot(235)
plt.xticks([])
plt.yticks([])
plt.plot(np.sin(x), np.cos(5*x))
plt.title('subplot(235)')

plt.show()

It is possible to combine subplots of different sizes as long as they do not overlap:

plt.figure(figsize=(8,4))
x = np.linspace(0,2*pi, 200)

for i in [1, 2, 4, 5]:
    plt.subplot(2,3,i)    # create some subplots on a grid with 2 rows and 3 columns
    plt.xticks([])
    plt.yticks([])
    plt.plot(np.sin(3*x), np.cos(i*x))
    plt.title('subplot(2,3,' + str(i) + ')')


plt.subplot(1,3,3)       # create a subplot on a grid with 1 row and 3 columns
plt.xticks([])
plt.yticks([])
plt.plot(np.sin(10*x), x)
plt.title('subplot(1,3,3)')

plt.show()

Spacing between subplots can be controlled using the subplots_adjust function:

plt.figure(figsize=(8,4))
x = np.linspace(0,2*pi, 200)

plt.subplots_adjust(wspace=0.05, # wspace controls the width of space between subplots
                    hspace=0.5)  # hspace controls the hight of space between subplots

for i in [1, 2, 4, 5]:
    plt.subplot(2,3,i)
    plt.xticks([])
    plt.yticks([])
    plt.plot(np.sin(3*x), np.cos(i*x))
    plt.title('subplot(2,3,' + str(i) + ')')

plt.subplot(1,3,3)
plt.xticks([])
plt.yticks([])
plt.plot(np.sin(10*x), x)
plt.title('subplot(1,3,3)')

plt.show()

Axes objects

The subplot function returns an axes object. We can use it to specify which subplot is active at any time:

plt.figure(figsize=(8,4))
x = np.linspace(0,2*pi, 200)

plt.subplots_adjust(hspace=0.4)

ax1 = plt.subplot(2,1,1) # subplot(2,1,1) is active, plotting will be done there
plt.xlim(0, 2*pi)
plt.plot(x, np.sin(2*x))
plt.title('subplot(2,1,1)')

ax2 = plt.subplot(2,1,2) # subplot(2,1,2) is now active
plt.xlim(0, 2*pi)
plt.plot(x, np.sin(10*x), 'g')
plt.title('subplot(2,1,2)')

plt.axes(ax1) # we activate subplot(2,1,1) to do more plotting on this subplot
plt.plot(x, np.cos(2*x), 'r--')


plt.show()

The axes function that we used above to select an existing axes object can be also used to create such objects. This is a useful alternative to the subplot function since it gives more flexibility in setting the layout of the figure: while the subplot function creates an evenly spaced grid, using the axes function we can place graphs within the figure any way we want:

plt.figure(figsize=(8,4))

# we use the axes function to create an axes object
# coordinates of the object within the picture are numbers between 0 and 1.
# The point (0,0) is the lower left corner of the figure, the point (1,1)
# is the upper right corner
ax1 = plt.axes([
        0.1,      # x-coordinate of the lower left corner of the axes object
        0.1,      # y-coordinate of the lower left corner of the axes object
        0.5,      # width of the object
        0.4       # height of the object
    ])

#here we create another axes object
ax2 = plt.axes([0.5, 0.2, 0.4, 0.6])

x = np.linspace(0,2*pi, 300)

plt.axes(ax1) # select ax1 to do some plotting there
plt.title('This is ax1')
plt.xlim(0, 2*pi)
plt.plot(x, np.cos(20*x), 'g')
plt.xticks([])
plt.yticks([])

plt.axes(ax2) # switch to ax2
plt.title('This is ax2')
plt.xlim(0, 2*pi)
plt.plot(x, np.sin(2*x))
plt.plot(x, np.cos(2*x), 'r--')
plt.xticks([])
plt.yticks([])

plt.show()