# Introduction to gnuplot

Have you ever been frustrated in math classes due to lack of visual examples of abstract topics? Have you ever wanted to quickly visualize a dataset without going through cumbersome software like Excel?

If so, you should know about gnuplot.

Gnuplot is a command line based graphing and plotting utility. In this post, I’ll outline some practical applications of gnuplot as well as some tips.

# Install gnuplot⌗

Most distos should have gnuplot in their repositories. I installed gnuplot on Arch linux by running `sudo pacman -Syu gnuplot`

To start using gnuplot, fire up your favorite terminal and run `gnuplot`

. You should be faced with a prompt like so:

```
G N U P L O T
Version 5.2 patchlevel 7 last modified 2019-05-29
Copyright (C) 1986-1993, 1998, 2004, 2007-2018
Thomas Williams, Colin Kelley and many others
gnuplot home: http://www.gnuplot.info
faq, bugs, etc: type "help FAQ"
immediate help: type "help" (plot window: hit 'h')
Terminal type is now 'qt'
gnuplot>
```

# 2D Plotting⌗

Now we are ready to start graphing. Let’s start with the simple function.

To plot this in gnuplot, simply enter the following into your prompt:

```
plot x**3
```

\mathring{g}

This looks pretty much like we would expect it to. If we want to plot multiple functions to compare, we can simply add it to the plot command.

```
plot sin(x), cos(x)
```

$$f(x) = sin(x)$$

$$g(x) = cos(x)$$

# 3D plotting⌗

Plotting functions in two dimensions is great, but what about three dimensional functions? Let’s see what

$$ f(x) = sin(x)*cos(y) $$

looks like in 3D. Enter the following into gnuplot:

```
set isosamples 50
set hidden3d
splot [0:2*pi] [0:2*pi] sin(x)*cos(y)
```

- The
`set hidden3d`

command disables the wireframe, making it easier to see the contours of the 3D objects. Try it both ways with the`unset hidden3d`

command, use whichever you prefer. - Setting our isosamples to 50 gives us a much smoother plot.
- In gnuplot, the
`splot`

is identical to the`plot`

command, except it will make a 3-dimensional plot. - The
`[0:2*pi] [0:2*pi]`

section specifies a domain for each of these functions, which is zero to 2π (the period of the cosine and sine functions)

After running these commands, we get

$$ f(x) = sin(x)*cos(y) $$

I would recommend checking out the gnuplot demos page, which has tons of functions and scripts to play around with. There are many more features than I could ever hope to cover here, so this is a great place to explore.

# Plotting data⌗

Say that we ran some experiments and we wanted to quickly plot the results. To keep things simple, let’s start out with a 2D graph that might be commonplace on homework assignments and research projects.
First, we need our data file. Data files in gnuplot use the `.d`

extension by default. In the case of 2 dimensions, there will be two space-separated columns for our points, with two line breaks signifying a new data block.

For this example, I using a classic classroom experiment of tracking the growth of plants over time. The left column represents the day, and the right hand is the height in inches.

```
# Flower number one
1 1.3
2 1.8
3 2.1
4 2.4
5 2.4
6 2.9
7 3.2
# Flower number two
1 1.0
2 1.1
3 1.6
4 2.1
5 2.6
6 3.0
7 3.3
```

To plot this data, we can simply run

`plot 'flowers.d'`

This looks OK, but it doesn’t really tell the whole story and it certainly isn’t up to research (or even science fair) standards. Let’s spruce this plot up a bit!

```
set title font "Helvetica,14"
set title 'Flower Growth Over Seven Days'
set xlabel 'Time (Days Elapsed)'
set ylabel "Height (Inches)"
plot 'flowers.d' index 0 w lp lw 3 title 'Flower 1', 'flowers.d' index 1 w lp lw 3 title 'Flower 2'
```

`index`

chooses the block from the dataset to plot (each block is separated by two blank lines)`w lp`

: short for`with linepoints`

, which styles the lines`lw`

: short for`line width`

`title`

sets the key label for the corresponding data block

Looks much better!

# Conclusion⌗

We learned how to use gnuplot to quickly create a graph out of experimental data, as well as plot equations in two and three dimensions. I have barely scratched the surface of this program, and I will share my knowledge with you as I continue to learn. In the future, I want to explore more advanced gnuplot features such as parametric equations and data fitting. I also hope to develop an automatic gnuplot theming script, that would act like my Zathura-Pywal utility and automatically color gnuplot based on the system colors. Keep an eye out for updates!