Available Software and Reading Material

This collection is maintained as a resource for students in all courses. Not all of the items mentioned here will be used as part of MECH2700, however, they might prove to be useful for later-year students doing thesis or just need a reminder of some of their Engineering Analysis methods.

Numerical Methods

The text for MECH2700 and MECH3750 is:

• Curtis F. Gerald and Patrick O. Wheatley Applied Numerical Analysis (Library call number QA297.G47 2004)

• R.J. Schilling & S.L. Harris Applied Numerical Methods for Engineers Brooks/Cole, Thompson Learning, ISBN 0-534-37014-4

There are also online texts, notes and software:

• Dr McAree's Lecture Notes on MATLAB and Numerical Methods
• NETLIB numerical methods library http://netlib2.cs.utk.edu/
• Numerical Recipes http://www.nr.com
• A Python module for optimization using the nonlinear simplex method nelmin.py
• A Python module for matrix operations where the matrices are stored as lists of lists matrix.py. It implements some of the linear algebra methods described in Schilling and Harris' text.
• A Python module for integration of a system of firts-order differential equations ode.py

Python

Python is the new-comer to the field of scientific/engineering computing although it is well established for more general computing activities. Resources for Python include:

• The home of Python http://www.python.org. This is the centre of the Python world and is one of the sites where you can find distributions of the Python interpreter and its extension software.
• We shall use the ActiveState Python distribution for class work.
• We will also use the Python extensions numpy and matplotlib. Beware that, in the nature of the Python system, some self-assembly may be required, however, MS-Windows users will usually be able to find installable packages. Please read the installation instructions.
• The "batteries-included" distribution from Enthought http://code.enthought.com/ is also suggested as a good distribution for MS-Windows users.
• Linux and Mac-OSX users will probably find Python already installed on their computers.

Sources of information on Python programming include:

• The best book for beginners is:
  Mark Lutz & David Ascher Learning Python 2nd Ed. O'Reilly, 2003
• The Python Tutorial. Note that this tutorial is also part of the installed Python environment in the Lab computers.
• The Python Quick Reference.
• The Python Learning Foundation http://www.awaretek.com/plf.html has a list of the available books and links to many tutorials.
• The older Numeric documentation in PDF and HTML

MATLAB/Octave

MATLAB is a well-established environment for numerical analysis, especially when matrix notation is appropriate. The Lab computers have MATLAB installed and you may purchase a student edition from the University bookshop (but you may have to order it). Octave is a free programming environment that works much like MATLAB. If you want to use MATLAB syntax but not have to pay for a MATLAB licence, try Octave.

• Mathworks, the home of MATLAB http://www.mathworks.com
• The home of Octave http://www.octave.org

There are several good text books that introduce MATLAB and/or use it as an implementation language. Online sources of information for MATLAB/Octave include:

• Ross McAree's tutorial notes in PDF format.
• Graeme Chandler's Introduction to Matlab

C programming

• comp.lang.c Frequently Asked Questions http://www.eskimo.com/~scs/C-faq/top.html
• C reference card http://www.refcards.com
• Borland offer version 5.5 of their C/C++ compiler for free download. This is a command-line driven compiler that can be used from a DOS window. It is an 8Mb download and about 40Mb installed.
• Borland's museum contains the Turbo-C 2.01 compiler for download. This is a nice, self-contained C compiler and development environment that can be used from a DOS window.
• Tutorial notes on programming in C.
• More tutorial notes on C programming
• The C9X draft specification.
• Less serious note on the C programming language.