September 28 { Making Graphs with Python

September 28 ¨C Making Graphs with Python

Basics

There are three main ways to generate graphs with Python using the library matplotlib:

1. using a Jypyter notebook; this is the recommended way but does not work on noether. If

you want to use Jupyter on your home computer, you can find information on how to do it

at



2. by starting the Python interpreter using the command

python

and then typing in one-by-one the various commands.

3. by typing all commands in a file called, e.g., plot.py and then giving the command

python plot.py &

in the prompt. We will be using primarily this last method.

A good tutorial for creating simple graphs with Python can be found at



Making a basic plot

The following lines of code plot a single line between points with coordinates given in the two

arrays xarray and yarray.

import numpy as np

import matplotlib.pyplot as plt

xarray=[1,2,3,4]

yarray=[1,4,9,16]

plt.plot(xarray,yarray)

plt.xlabel(¡¯x-axis label¡¯)

plt.ylabel(¡¯y-axis label¡¯)

plt.show()

#

#

#

#

#

#

#

#

imports library for math

imports library for plots

array with x-coordinates

array with y-coordinates

plot xarray vs. yarray

label for x-axis

label for y-axis

show the plot

The output should look like:

16

14

12

y-axis label

10

8

6

4

2

0

1.0

1.5

2.0

2.5

x-axis label

3.0

3.5

4.0

Without giving any additional options, Python will generate a plot with a solid line connecting

the points and with the ranges of the axes chosen by the graphics algorithm.

In order to set a user-defined range for the axes (say the x-axis to go from 0 to 6 and the y-axis

to go from 0 to 20), we use the command

plt.axis([0, 6, 0, 20])

whereas to change the type of the plot, we give the command

plt.plot(xarray,yarray,¡¯ro¡¯)

# red circle

Our code then becomes

import numpy as np

import matplotlib.pyplot as plt

xarray=[1,2,3,4]

yarray=[1,4,9,16]

plt.axis([0, 6, 0, 20])

plt.plot(xarray,yarray,¡¯ro¡¯)

plt.xlabel(¡¯x-axis label¡¯)

plt.ylabel(¡¯y-axis label¡¯)

plt.show()

#

#

#

#

#

#

#

#

#

imports library for math

imports library for plots

array with x-coordinates

array with y-coordinates

set axes limits

plot with red circles

label for x-axis

label for y-axis

show the plot

and the output changes to

20

y-axis label

15

10

5

0

0

1

2

3

x-axis label

4

5

6

Finally, in order to export the plot to a PDF file called, e.g., plot.pdf, we change the last

command such that the code becomes

import numpy as np

import matplotlib.pyplot as plt

xarray=[1,2,3,4]

yarray=[1,4,9,16]

plt.axis([0, 6, 0, 20])

plt.plot(xarray,yarray,¡¯ro¡¯)

plt.xlabel(¡¯x-axis label¡¯)

plt.ylabel(¡¯y-axis label¡¯)

plt.savefig(¡¯plot.pdf¡¯)

plt.close()

#

#

#

#

#

#

#

#

#

#

imports library for math

imports library for plots

array with x-coordinates

array with y-coordinates

set axes limits

plot with red circles

label for x-axis

label for y-axis

save the graph as ¡¯plot.pdf¡¯

close the file

2

Changing the Plot Style

The plt.plot command takes a large number of options, which control how the data points

are plotted. We already saw how to change from the default (a solid line) to a sequence of red

circles. Other options we can play with include

plt.plot(xarray,yarray,¡¯bo¡¯)

# b: blue, o: circles

plt.plot(xarray,yarray,¡¯gs¡¯)

# g: green, s:square

plt.plot(xarray,yarray,¡¯r-¡¯)

# r: red, -:solid line

plt.plot(xarray,yarray,¡¯--¡¯)

# --: dashed line

plt.plot(xarray,yarray,¡¯:¡¯)

# : dotted line

plt.plot(xarray,yarray,¡¯go-¡¯)

# g: green, o: circles, -:line

As the above examples show, the various options can be combined to change, e.g., the style (line

vs. points), the color, or even to combine two styles, e.g., line and points.

The result of using this last command, i.e.,

import numpy as np

import matplotlib.pyplot as plt

xarray=[1,2,3,4]

yarray=[1,4,9,16]

plt.axis([0, 6, 0, 20])

plt.plot(xarray,yarray,¡¯go-¡¯)

plt.xlabel(¡¯x-axis label¡¯)

plt.ylabel(¡¯y-axis label¡¯)

plt.show()

#

#

#

#

#

#

#

#

#

imports library for math

imports library for plots

array with x-coordinates

array with y-coordinates

set axes limits

plot with green cirles+line

label for x-axis

label for y-axis

show the plot

looks like

20

y-axis label

15

10

5

0

0

1

2

3

x-axis label

4

5

6

3

The following are some of the options available to control the style and color of the plot.

Option

¡¯-¡¯

¡¯¨C¡¯

¡¯-.¡¯

¡¯:¡¯

¡¯o¡¯

¡¯s¡¯

¡¯p¡¯

¡¯*¡¯

¡¯+¡¯

¡¯x¡¯

¡¯D¡¯

Style

solid line style

dashed line style

dash-dot line style

dotted line style

circle marker

square marker

pentagon marker

star marker

plus marker

x marker

diamond marker

Option

b

g

r

c

m

y

k

w

Color

blue

green

red

cyan

magenta

yellow

black

white

We can also add the option lw to the plt.plot command to change the thickness (lineweight)

of the line and the option fontsize to the xlabel command to change the size of the font. For

example, the output of the following code

import numpy as np

#

import matplotlib.pyplot as plt

#

xarray=[1,2,3,4]

#

yarray=[1,4,9,16]

#

plt.axis([0, 6, 0, 20])

#

plt.plot(xarray,yarray,¡¯g-¡¯,lw=4)

#

plt.xlabel(¡¯x-axis label¡¯,fontsize=18)#

plt.ylabel(¡¯y-axis label¡¯,fontsize=18)#

plt.show()

imports library for math

imports library for plots

array with x-coordinates

array with y-coordinates

set axes limits

plot with thick green line

large label for x-axis

large label for y-axis

becomes

20

y-axis label

15

10

5

0

0

1

2

3

x-axis label

4

5

6

4

Changing the Plot Type

In physics, we often plot log- and log-log plots of different physical quantities. It is easy to

change the style of either the x- or the y-axes by giving the commands

plt.xscale(¡¯log¡¯)

plt.yscale(¡¯log¡¯)

For example, the following lines of code (don¡¯t forget to change the lower limits from zero to

something that has a real logarithm)

import numpy as np

import matplotlib.pyplot as plt

xarray=[1,2,3,4]

yarray=[1,4,9,16]

plt.xscale(¡¯log¡¯)

plt.yscale(¡¯log¡¯)

plt.axis([0.5, 20., 0.5, 20.])

plt.plot(xarray,yarray,¡¯g-¡¯)

plt.xlabel(¡¯x-axis label¡¯)

plt.ylabel(¡¯y-axis label¡¯)

plt.show()

#

#

#

#

#

#

#

#

#

#

imports library for math

imports library for plots

array with x-coordinates

array with y-coordinates

logarithmic x-axis

logarithmic y-axis

set axes limits

plot with green line

label for x-axis

label for y-axis

generate the following output

y-axis label

101

100

100

x-axis label

101

5

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