How do you change the size of figures drawn with matplotlib?

Question

How do you change the size of figure drawn with matplotlib?

Answer 1

Comparison of different approaches to set exact image sizes in pixels

This answer will focus on:

• savefig
• setting the size in pixels

Here is a quick comparison of some of the approaches I've tried with images showing what the give.

Baseline example without trying to set the image dimensions

Just to have a comparison point:

base.py

#!/usr/bin/env python3

import sys

import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl

fig, ax = plt.subplots()
print('fig.dpi = {}'.format(fig.dpi))
print('fig.get_size_inches() = ' + str(fig.get_size_inches())
t = np.arange(-10., 10., 1.)
plt.plot(t, t, '.')
plt.plot(t, t**2, '.')
ax.text(0., 60., 'Hello', fontdict=dict(size=25))
plt.savefig('base.png', format='png')

run:

./base.py
identify base.png

outputs:

fig.dpi = 100.0
fig.get_size_inches() = [6.4 4.8]
base.png PNG 640x480 640x480+0+0 8-bit sRGB 13064B 0.000u 0:00.000

My best approach so far: plt.savefig(dpi=h/fig.get_size_inches()[1] height-only control

I think this is what I'll go with most of the time, as it is simple and scales:

get_size.py

#!/usr/bin/env python3

import sys

import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl

height = int(sys.argv[1])
fig, ax = plt.subplots()
t = np.arange(-10., 10., 1.)
plt.plot(t, t, '.')
plt.plot(t, t**2, '.')
ax.text(0., 60., 'Hello', fontdict=dict(size=25))
plt.savefig(
    'get_size.png',
    format='png',
    dpi=height/fig.get_size_inches()[1]
)

run:

./get_size.py 431

outputs:

get_size.png PNG 574x431 574x431+0+0 8-bit sRGB 10058B 0.000u 0:00.000

and

./get_size.py 1293

outputs:

main.png PNG 1724x1293 1724x1293+0+0 8-bit sRGB 46709B 0.000u 0:00.000

I tend to set just the height because I'm usually most concerned about how much vertical space the image is going to take up in the middle of my text.

plt.savefig(bbox_inches='tight' changes image size

I always feel that there is too much white space around images, and tended to add bbox_inches='tight' from: Removing white space around a saved image in matplotlib

However, that works by cropping the image, and you won't get the desired sizes with it.

Instead, this other approach proposed in the same question seems to work well:

plt.tight_layout(pad=1)
plt.savefig(...

which gives the exact desired height for height equals 431:

Fixed height, set_aspect, automatically sized width and small margins

Ermmm, set_aspect messes things up again and prevents plt.tight_layout from actually removing the margins...

Asked at: How to obtain a fixed height in pixels, fixed data x/y aspect ratio and automatically remove remove horizontal whitespace margin in Matplotlib?

plt.savefig(dpi=h/fig.get_size_inches()[1] + width control

If you really need a specific width in addition to height, this seems to work OK:

width.py

#!/usr/bin/env python3

import sys

import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl

h = int(sys.argv[1])
w = int(sys.argv[2])
fig, ax = plt.subplots()
wi, hi = fig.get_size_inches()
fig.set_size_inches(hi*(w/h), hi)
t = np.arange(-10., 10., 1.)
plt.plot(t, t, '.')
plt.plot(t, t**2, '.')
ax.text(0., 60., 'Hello', fontdict=dict(size=25))
plt.savefig(
    'width.png',
    format='png',
    dpi=h/hi
)

run:

./width.py 431 869

output:

width.png PNG 869x431 869x431+0+0 8-bit sRGB 10965B 0.000u 0:00.000

and for a small width:

./width.py 431 869

output:

width.png PNG 211x431 211x431+0+0 8-bit sRGB 6949B 0.000u 0:00.000

So it does seem that fonts are scaling correctly, we just get some trouble for very small widths with labels getting cut off, e.g. the 100 on the top left.

I managed to work around those with Removing white space around a saved image in matplotlib

plt.tight_layout(pad=1)

which gives:

width.png PNG 211x431 211x431+0+0 8-bit sRGB 7134B 0.000u 0:00.000

From this, we also see that tight_layout removes a lot of the empty space at the top of the image, so I just generally always use it.

Fixed magic base height, dpi on fig.set_size_inches and plt.savefig(dpi= scaling

I believe that this is equivalent to the approach mentioned at: https://stackoverflow.com/a/13714720/895245

magic.py

#!/usr/bin/env python3

import sys

import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl

magic_height = 300
w = int(sys.argv[1])
h = int(sys.argv[2])
dpi = 80
fig, ax = plt.subplots(dpi=dpi)
fig.set_size_inches(magic_height*w/(h*dpi), magic_height/dpi)
t = np.arange(-10., 10., 1.)
plt.plot(t, t, '.')
plt.plot(t, t**2, '.')
ax.text(0., 60., 'Hello', fontdict=dict(size=25))
plt.savefig(
    'magic.png',
    format='png',
    dpi=h/magic_height*dpi,
)

run:

./magic.py 431 231

outputs:

magic.png PNG 431x231 431x231+0+0 8-bit sRGB 7923B 0.000u 0:00.000

And to see if it scales nicely:

./magic.py 1291 693

outputs:

magic.png PNG 1291x693 1291x693+0+0 8-bit sRGB 25013B 0.000u 0:00.000

So we see that this approach also does work well. The only problem I have with it is that you have to set that magic_height parameter or equivalent.

Fixed DPI + set_size_inches

This approach gave a slightly wrong pixel size, and it makes it is hard to scale everything seamlessly.

set_size_inches.py

#!/usr/bin/env python3

import sys

import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl

w = int(sys.argv[1])
h = int(sys.argv[2])
fig, ax = plt.subplots()
fig.set_size_inches(w/fig.dpi, h/fig.dpi)
t = np.arange(-10., 10., 1.)
plt.plot(t, t, '.')
plt.plot(t, t**2, '.')
ax.text(
    0,
    60.,
    'Hello',
    # Keep font size fixed independently of DPI.
    # https://stackoverflow.com/questions/39395616/matplotlib-change-figsize-but-keep-fontsize-constant
    fontdict=dict(size=10*h/fig.dpi),
)
plt.savefig(
    'set_size_inches.png',
    format='png',
)

run:

./set_size_inches.py 431 231

outputs:

set_size_inches.png PNG 430x231 430x231+0+0 8-bit sRGB 8078B 0.000u 0:00.000

so the height is slightly off, and the image:

The pixel sizes are also correct if I make it 3 times larger:

./set_size_inches.py 1291 693

outputs:

set_size_inches.png PNG 1291x693 1291x693+0+0 8-bit sRGB 19798B 0.000u 0:00.000

We understand from this however that for this approach to scale nicely, you need to make every DPI-dependant setting proportional to the size in inches.

In the previous example, we only made the "Hello" text proportional, and it did retain its height between 60 and 80 as we'd expect. But everything for which we didn't do that, looks tiny, including:

• line width of axes
• tick labels
• point markers

SVG

I could not find how to set it for SVG images, my approaches only worked for PNG e.g.:

get_size_svg.py

#!/usr/bin/env python3

import sys

import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl

height = int(sys.argv[1])
fig, ax = plt.subplots()
t = np.arange(-10., 10., 1.)
plt.plot(t, t, '.')
plt.plot(t, t**2, '.')
ax.text(0., 60., 'Hello', fontdict=dict(size=25))
plt.savefig(
    'get_size_svg.svg',
    format='svg',
    dpi=height/fig.get_size_inches()[1]
)

run:

./get_size_svg.py 431

and the generated output contains:

<svg height="345.6pt" version="1.1" viewBox="0 0 460.8 345.6" width="460.8pt"

and identify says:

get_size_svg.svg SVG 614x461 614x461+0+0 8-bit sRGB 17094B 0.000u 0:00.000

and if I open it in Chromium 86 the browser debug tools mouse image hover confirm that height as 460.79.

But of course, since SVG is a vector format, everything should in theory scale, so you can just convert to any fixed sized format without loss of resolution, e.g.:

inkscape -h 431 get_size_svg.svg -b FFF -e get_size_svg.png

gives the exact height:

I use Inkscape instead of Imagemagick's convert here because you need to mess with -density as well to get sharp SVG resizes with ImageMagick:

• https://superuser.com/questions/598849/imagemagick-convert-how-to-produce-sharp-resized-png-files-from-svg-files/1602059#1602059
• How to convert a SVG to a PNG with ImageMagick?

And setting <img height="" on the HTML should also just work for the browser.

Tested on matplotlib==3.2.2.

Answer 2

Please try a simple code as following:

from matplotlib import pyplot as plt
plt.figure(figsize=(1,1))
x = [1,2,3]
plt.plot(x, x)
plt.show()

You need to set the figure size before you plot.

Answer 3

Try commenting out the fig = ... line

%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt

N = 50
x = np.random.rand(N)
y = np.random.rand(N)
area = np.pi * (15 * np.random.rand(N))**2

fig = plt.figure(figsize=(18, 18))
plt.scatter(x, y, s=area, alpha=0.5)
plt.show()

Answer 4

This resizes the figure immediately even after the figure has been drawn (at least using Qt4Agg/TkAgg - but not MacOSX - with matplotlib 1.4.0):

matplotlib.pyplot.get_current_fig_manager().resize(width_px, height_px)

Answer 5

Generalizing and simplifying psihodelia's answer. If you want to change the current size of the figure by a factor sizefactor

import matplotlib.pyplot as plt

# here goes your code

fig_size = plt.gcf().get_size_inches() #Get current size
sizefactor = 0.8 #Set a zoom factor
# Modify the current size by the factor
plt.gcf().set_size_inches(sizefactor * fig_size) 

After changing the current size, it might occur that you have to fine tune the subplot layout. You can do that in the figure window GUI, or by means of the command subplots_adjust

For example,

plt.subplots_adjust(left=0.16, bottom=0.19, top=0.82)

Answer 6

You can simply use (from matplotlib.figure.Figure):

fig.set_size_inches(width,height)

As of Matplotlib 2.0.0, changes to your canvas will be visible immediately, as the forward keyword defaults to True.

If you want to just change the width or height instead of both, you can use

fig.set_figwidth(val) or fig.set_figheight(val)

These will also immediately update your canvas, but only in Matplotlib 2.2.0 and newer.

For Older Versions

You need to specify forward=True explicitly in order to live-update your canvas in versions older than what is specified above. Note that the set_figwidth and set_figheight functions don’t support the forward parameter in versions older than Matplotlib 1.5.0.