Matplotlib different size subplots

Another way is to use the subplots function and pass the width ratio with gridspec_kw matplotlib Tutorial: Customizing Figure Layouts Using GridSpec and Other Functions matplotlib.gridspec.GridSpec has available gridspect_kw options

matplotlib Tutorial: Customizing Figure Layouts Using GridSpec and Other Functions

matplotlib.gridspec.GridSpec has available gridspect_kw options

import numpy as np
import matplotlib.pyplot as plt 

# generate some data
x = np.arange(0, 10, 0.2)
y = np.sin(x)

# plot it
f, (a0, a1) = plt.subplots(1, 2, gridspec_kw={'width_ratios': [3, 1]})
a0.plot(x, y)
a1.plot(y, x)

f.tight_layout()
f.savefig('grid_figure.pdf')

https://i.stack.imgur.com/aBJVa.png

Because the question is canonical, here is an example with vertical subplots.

# plot it
f, (a0, a1, a2) = plt.subplots(3, 1, gridspec_kw={'height_ratios': [1, 1, 3]})

a0.plot(x, y)
a1.plot(x, y)
a2.plot(x, y)

f.tight_layout()

https://i.stack.imgur.com/a2djk.png

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You can use gridspec and figure:

import numpy as np
import matplotlib.pyplot as plt 
from matplotlib import gridspec

# generate some data
x = np.arange(0, 10, 0.2)
y = np.sin(x)

# plot it
fig = plt.figure(figsize=(8, 6)) 
gs = gridspec.GridSpec(1, 2, width_ratios=[3, 1]) 
ax0 = plt.subplot(gs[0])
ax0.plot(x, y)
ax1 = plt.subplot(gs[1])
ax1.plot(y, x)

plt.tight_layout()
plt.savefig('grid_figure.pdf')

https://i.stack.imgur.com/hKVwB.png

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I used pyplot's axes object to manually adjust the sizes without using GridSpec:

import matplotlib.pyplot as plt
import numpy as np
x = np.arange(0, 10, 0.2)
y = np.sin(x)

# definitions for the axes
left, width = 0.07, 0.65
bottom, height = 0.1, .8
bottom_h = left_h = left+width+0.02

rect_cones = [left, bottom, width, height]
rect_box = [left_h, bottom, 0.17, height]

fig = plt.figure()

cones = plt.axes(rect_cones)
box = plt.axes(rect_box)

cones.plot(x, y)

box.plot(y, x)

plt.show()

https://i.stack.imgur.com/0xoSF.png

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Probably the simplest way is using subplot2grid, described in Customizing Location of Subplot Using GridSpec.

ax = plt.subplot2grid((2, 2), (0, 0))

is equal to

import matplotlib.gridspec as gridspec
gs = gridspec.GridSpec(2, 2)
ax = plt.subplot(gs[0, 0])

so bmu's example becomes:

import numpy as np
import matplotlib.pyplot as plt

# generate some data
x = np.arange(0, 10, 0.2)
y = np.sin(x)

# plot it
fig = plt.figure(figsize=(8, 6))
ax0 = plt.subplot2grid((1, 3), (0, 0), colspan=2)
ax0.plot(x, y)
ax1 = plt.subplot2grid((1, 3), (0, 2))
ax1.plot(y, x)

plt.tight_layout()
plt.savefig('grid_figure.pdf')

https://i.stack.imgur.com/Wqbsr.png

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In a simple way, different size sub plotting can also be done without gridspec:

plt.figure(figsize=(12, 6))
ax1 = plt.subplot(2,3,1)
ax2 = plt.subplot(2,3,2)
ax3 = plt.subplot(2,3,3)
ax4 = plt.subplot(2,1,2)
axes = [ax1, ax2, ax3, ax4]

https://i.stack.imgur.com/6W3aE.png

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A nice way of doing this was added in matplotlib 3.3.0, subplot_mosaic.

You can make a nice layout using an "ASCII art" style.

For example

fig, axes = plt.subplot_mosaic("ABC;DDD")

will give you three axes on the top row and one spanning the full width on the bottom row like below

https://i.stack.imgur.com/oHHL6.png

A nice thing about this method is that the axes returned from the function is a dictionary with the names you define, making it easier to keep track of what is what e.g.

axes["A"].plot([1, 2, 3], [1, 2, 3])

You can also pass a list of lists to subplot_mosaic if you want to use longer names

fig, axes = plt.subplot_mosaic(
    [["top left", "top centre", "top right"],
     ["bottom row", "bottom row", "bottom row"]]
)

axes["top left"].plot([1, 2, 3], [1, 2, 3])

will produce the same figure

https://i.stack.imgur.com/uuOMp.png

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