AMATH 352
Autumn Quarter, 2008

Applied Linear Algebra and Numerical Analysis

Computing for this course and beyond

Matlab

The official computer language for this course is Matlab.

I encourage you to purchase the student edition of Matlab, available at the University Bookstore for around $100.

You may use the computers in the College of Arts and Sciences Instructional Computing Lab (A&S LAB), located in Communications B022. See the AS Lab webpage for hours of operation and other information.

You can use Matlab remotely via a terminal server:

Most other computer labs on campus do not have Matlab.

Some Matlab resources available on the web:

The Matlab help desk where you can find useful introductory information under "Learning MATLAB"
Matlab Hypertext Reference, Portland State University
Henri Gavin's list of tutorials
Many other Matlab tutorials can be found on the web with any search engine, e.g. search with Google.

Free alternatives

Several free packages have been developed that mimic many of the features of Matlab. Beware, however, that not all features of Matlab we need this quarter are available in these versions, and the syntax differs in enough ways that most Matlab codes will not run directly in these languages. But they are worth knowing about...

Python

Python is an object-oriented scripting language that is used for many purposes, including scientific computing.

Several Python modules provide much of the same functionality as Matlab, often with very similar syntax. In particular, NumPy provides array handling similar to Matlab's and Matplotlib provides graphics routines with Matlab-like syntax. The SciPy module contains many other numerical and scientific computing functions.

Most unux-like operating systems (linux and OSX) include Python by default, but you will probably need to install the packages mentioned above. With Debian or Ubuntu you get get these with apt-get.

On Windows, OSX, or Redhat Linux I recommend using the Enthought Python Distribution which includes the modules above and many additional useful tools.

Some references:

Tutorial
Dive Into Python
NumPy for Matlab users
Python Scripting for Computational Science, by H. P. Langtangen
- Intro on slides

Sage

Sage is an open source project started by Prof. William Stein in the UW Mathematics Department that is based on Python and includes many mathematical computing tools as well as a nice web-based notebook interface to many other mathematics packages.

You can download and install it to easily obtain all these packages (including NumPy and SciPy) or try it out on the web without downloading anything.