September 28 { Making Graphs with Python

September 28 ? 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()

The output should look like:

# 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

y-axis label

16

14

12

10

8

6

4

2

01.0

1.5

2.0

2.5

3.0

3.5

4.0

x-axis label

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()

and the output changes to

# 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

20

15

y-axis label

10

5

00

1

2

3

4

5

6

x-axis label

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()

looks like

# 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

20

15

y-axis label

10

5

00

1

2

3

4

5

6

x-axis label

3

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

Option '-' '?' '-.' ':' '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

# imports library for math

import matplotlib.pyplot as plt

# imports library for plots

xarray=[1,2,3,4]

# array with x-coordinates

yarray=[1,4,9,16]

# array with y-coordinates

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

# set axes limits

plt.plot(xarray,yarray,'g-',lw=4) # plot with thick green line

plt.xlabel('x-axis label',fontsize=18)# large label for x-axis

plt.ylabel('y-axis label',fontsize=18)# large label for y-axis

plt.show()

becomes

20

15

y-axis label

10

5

00

1

2

3

4

5

6

x-axis label

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()

generate the following output

# 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

101

y-axis label

100 100

101 x-axis label

5

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