GNU Octave - An Introduction

Originally published in the LinuxGazette.net, December 2004, Issue 109.

This is the first of a series of articles in which I will introduce GNU Octave and demonstrate some of its many features. GNU Octave is a high-level language for numerical computations. I use it every day in my PhD research which involves manipulating large vectors and matrices. It is very similar in syntax and function to a commercial application called Matlab. The biggest difference between the two is that Octave is released under the GNU General Public License, which means it can be freely distributed and/or modified, while a single-user academic license for the basic Matlab currently costs US$700.

I have convinced a few of my colleagues to give Octave a try instead of Matlab. In every case, once that person stops looking for the differences between the two and decides to give Octave a real chance, they begin to embrace its usefulness, its features and its free availability. They realise that they can install a copy of Octave onto every one of their simulation servers, their laptops and their home computers without having to purchase costly new licenses for each one.

Installing and Running Octave

The source code for Octave can be downloaded from http://www.octave.org/download.html. This site also contains information on where to get Octave in binary form for Apple's OS X and Windows. Most Linux distributions include Octave as standard and if it is not already installed on your system it should simply be a matter of installing the Octave package from your installation CDs or the Internet.

Starting the Octave interpreter under Linux is as simple as typing the `octave' command:

$ octave
GNU Octave, version 2.1.50 (i686-pc-linux-gnu).
Copyright (C) 1996,1997,1998,1999,2000,2001,2002,2003 John W. Eaton.
This is free software; see the source code for copying conditions.
There is ABSOLUTELY NO WARRANTY; not even for MERCHANTIBILITY or
FITNESS FOR A PARTICULAR PURPOSE.  For details, type `warranty'.

Please contribute if you find this software useful.
For more information, visit http://www.octave.org/help-wanted.html

Report bugs to <bug-octave@bevo.che.wisc.edu>.

octave:1>

Documentation

A 380 page manual is included with the Octave source code in HTML, DVI and PS format. This manual is also available on-line at Octave's home page. For those of you who installed via binary packages, you should be able to access the manual via the `info' command:
$ info octave
If you are unfamiliar with 'info', then try using KDE's interface to info by typing `info:octave' into Konqueror's location bar.

In this article I only intend to touch on the very basics of Octave to demonstrate just how easy it is to pick up and use effectively. I would strongly recommend, at the very least, skimming through the available documentation to get a fuller flavor of what Octave has to offer.

First Steps by Example

Let's look at the problem of solving a system of n linear equations in n unknowns: 
         x + 3y - 2z = -3
         
        3x - 4y + 3z = 28
        
        5x - 5y + 4z =  7
Such a system of linear equations can be written as the single matrix equation Ax = b, where A is the coefficient matrix, b is the column vector containing the right-hand side of the linear equations and x is the column vector representing the solution. If you've forgotten your linear algebra then don't worry - this will all become at lot clearer as we use Octave to solve this for us: 
octave:1> A = [ 1, 3, -2; 3, -4, 3; 5, 5, -4 ]
A =

   1   3  -2
   3  -4   3
   5   5  -4

octave:2> b = [ -3; 28; 7 ]
b =

   -3
   28
    7

octave:3> A \ b
ans =

  5.0000
  2.0000
  7.0000

octave:4>
You will notice that each line of the interpreter is numbered sequentially; I will use these line numbers when referring to particular commands. On line 1 I defined A as a 3x3 matrix containing the coefficients of the linear system above (a coefficient is the number to the left of the unknown variables x, y and z). The rows are delimited with a semi-colon and the individual elements on each row are delimited by a comma. Each of these is recommended but optional: a space is all that is needed to delimit elements in a row and the return key could have been used instead of semi-colons. I defined the column vector b on line 2 in the same way.

Line 3 computes the solution of the linear system using the `left division' operator which, for the mathematicians among you, is conceptually equivalent to A-1b. By solution, I mean that x = 5, y = 2 and z = 7 will satisfy all three equations of the linear system.

Plotting the solution to a problem in mathematics is often the key to fully understanding that problem. Octave has a number of functions for plotting two- and three-dimensional graphs which use Gnuplot to handle the actual graphics themselves. As a simple example, let's plot the sin( x ):

octave:9> x = [ -pi:0.01:pi ];
octave:10> plot( x, sin(x) )
octave:11>
Which produces:

[Plot of a sine wave]

Let's examine line 9 above in more detail:

Data Types, Simple Arithmetic and Standard Functions

Octave's built-in data types are real and complex scalars and matrices, character strings and a data structure type. All of the standard arithmetic functions are available for scalars and matrices:
a + b
(a - b) 		Addition (Subtraction). If both operands are matrices then the number of rows and columns must both agree. If one operand is a scalar and the other is a matrix, then that scalar will be added (subtracted) to (from) every element of the matrix.
a .+ b
  (a .- b)   		Component-wise addition (subtraction) (also known as element-by-element addition).
x * y Multiplication. If both operands are matrices then the number of columns of x must agree with the number of rows or y.
x .* y Component-wise multiplication.
x / y Right division. Conceptually equivalent to ( (yT)-1 * xT )T
x ./ y Component-wise right division
x \ y Left division. Conceptually equivalent to x-1 * y
x .\ y Component-wise left division.
x ^ y
x ** y 		Power operator. See the manual for definitions when x and/or y is a matrix.
x .** y Component-wise power operation.
-x Negation
x' Complex conjugate transpose.
x.' Transpose.

There are many standard functions built-in to Octave and these include the scalar functions:

sin() asin() log() abs()
cos() acos() log2() sqrt()
tan() atan() log10() sign()
 round()   floor()   ceil()    mod()  

the vector functions:

  max()     sum()    median()    any()  
min() prod() mean() all()
sort() var() std()

and the matrix functions:

eig() - eigenvalues and eigenvectors
inv() - inverse
poly() - characteristic polynomial
det() - determinant
size() - return the size of a matrix
  norm(,p)   - compute the p-norm of a matrix
rank() - the rank of a matrix

Strings can be declared with either single or double quotes:
> fname = "Barry";
> sname = "O'Donovan";
 Strings can be concatenated using the same notation as matrix definitions:
> [ fname, " ", sname ]
ans = Barry O'Donovan

There are many string functions available as standard, including functions for converting strings to numbers and vice-versa. There are also a number of functions for printing strings to the screen such as disp() and printf(), and for reading data from the user such as input().

The Octave Environment

In all the cases above where we had an assignment command such as A = ..., the variable A is created or overwritten with the information on the right-hand side of the assignment operator (=). Variable names are case sensitive and made up of letters, digits and underscores but must begin with a letter or underscore. Variables remain in the interpreter's environment until you either exit the interpreter or clear the variable:
> clear A
deletes the variable A, while:
> clear
deletes all variables currently stored. The who command can be used to list all variables currently stored in the environment.

We would often like to save the current environment to disk as a backup or to come back to it later and continue on from where we left off. We can use the following two commands for this:
> save filename
to save all of the currently defined variables to filename and:
> load filename
to load them again at a later point.

Loops and Conditional Statements

Just like any other programming language, Octave has its loop and conditional constructs. The following example demonstrates how to generate the first 10 values of Fibonacci's sequence using a for loop: 
octave:11> fib = [ 0, 1 ];
octave:12> for i = 3:10
> fib = [ fib, fib( i-2 ) + fib( i-1 ) ];
> endfor
octave:13> fib
fib =

   0   1   1   2   3   5   8  13  21  34

octave:14>
Fibonacci's sequence is described by Fk = Fk-1 + Fk-2 with F0 = 0 and F1 = 1. It is often used to describe the population growth of rabbits: suppose that a newly born pair of rabbits produce no offspring in the first month of their lives and one new pair on each subsequent month. Starting with F1 = 1 pairs in the first month, Fk is the number of pairs in the kth month assuming that none of the rabbits die. Fibonacci's sequence occurs naturally in a variety of places and it is one of those rare occurrences in mathematics where a simple formula can be truly fascinating.

Notice that in the above code:

The following example evaluates the randomness of Octave's rand() function and demonstrates it's conditional statements:

octave:14> a = b = c = d = 0;
octave:15> for i = 1:100000
> r = rand(1);
> if ( r < 0.25 )
>     a++;
> elseif ( r < 0.5 )
>     b++;
> elseif ( r < 0.75 )
>     c++;
> else
>     d++;
> endif
> endfor
octave:16> a,b,c,d
a = 25115
b = 24870
c = 25045
d = 24970
octave:17>
Line 14 sets the scalar variables a, b, c and d to zero. We then generate 100,000 random numbers between 0 and 1 and increase a by one if it falls between 0 and 0.25, b if it falls between 0.25 and 0.5, and so forth. Once the loop completes, we would expect the values of a, b, c and d to be approximately 25,000 if rand() generates truly random numbers, which, as can be seen above, it does.

A Brief Overview of the Features of Octave

Octave was originally written and is still maintained by John W. Eaton who made the first public release in 1993. Since then many other people have contributed to it as they found it lacked features they needed. As it stands, Octave comes with many built-in functions grouped into related packages.

Matrix manipulation is at the heart of Octave and it includes all the operators you would expect for matrix arithmetic including addition, subtraction, multiplication (matrix and component-wise), division, transposition, etc. It also has a number of functions for generating common matrices including:

The groups of specialised functions include:

Some of these are complete and some only contain a few functions. Each is added by various people when and as needed. Over the next couple of months we will look at creating new functions with Octave as well as writing new functions in C++. The Octave developers welcome new additions and hopefully by the end of this series you might be writing and contributing your own Octave functions.

Final Words

Hopefully this article will have demonstrated just how easy it is to pick up the basics of Octave. For any teachers or lecturers trying to teach their students matrices and/or linear algebra, why not introduce Octave into your course as a teaching tool? And for the lecturers or students of university departments such as maths, mathematical physics, physics, engineering, computer science, etc. - it's often difficult to have to come up with new and exciting final year projects every year. Why not have a student implement some mathematical functionality that Octave lacks from your own area of research that might be of interest to others?

Next month: Writing new Octave functions and writing Octave scripts that can be executed from the command line.

Copyright © 2004, Barry O'Donovan. Released under the Open Publication license.