UW AMath

AMath 584, Autumn Quarter, 2011

Applied Linear Algebra and

Introductory Numerical Analysis

Table Of Contents

Software for the course

You can use either Matlab or Python. The language R might also be possible but not recommended.


Matlab is available on the Applied Mathematics computing system for students in this department. It is also available in the Arts and Sciences Instructional Computing Lab located in Communications B-022, and also available via their terminal server.

The Student Version of Matlab is available at the bookstore for about $100. This is worth buying if you think you will use Matlab regularly.


All the functionality of Matlab that is needed for this course is also available as open source software in the NumPy and SciPy Python modules, along with matplotlib for plotting purposes. Together with the IPython shell this provides an interactive computing environment very similar to Matlab’s.

See NumPy for Matlab Users for some handy tips on the correspondence between the two (tips that are also useful for users of either system to see some commands you may not know).

Python is a standard language that is probably on your computer already. For tips on installing NumPy, SciPy, matplotlib, and IPython, see these notes from AMath 583. The Enthought Python Distribution (EPD) includes all the tools we need and is fairly easy to install on most computers. Note that it is free for academic users, see the bottom of the pricing page.

Virtual machine

You might also find the virtual machine from 583 useful since it includes all the Python tools we’ll need and lots of other stuff.


Both Matlab and NumPy provide convenient wrappers for LAPACK (Linear Algebra Package), which is an open source package written in Fortran 90 for solving linear algebra problems. So under the hood, you are using the same software whether you use Matlab or Python.

For large scale computing projects you may want to call LAPACK routines directly from a Fortran or C code.