Code

Tutorials
When learning a new language, once you've memorized the words, you need to start conversing. Unfortunately, source code is not spoken. It's a stillborn language. One of the best ways to code well is to study and modify other, good code. For code, this means reading and tweaking tutorials first, then design patterns, then large-scale projects next.


 * Bash By Example
 * Data Structures in Python
 * Linear Algebra in Numpy

Remember that it's not enough to just read them. It's actually a positive waste of time. Rather, you have to do some run-tweak-run-debug development cycles with them.

C Libraries
With the exception of the standard libraries and the GNU Scientific Library, there are surprisingly few of these about. Here are some generics that we've implemented and are sharing under the GPL.

Robust map and red/black tree code has recently been published to github.

Python Libraries

 * libnwchem A patch against Nwchem 6.5 to build its functionality as a shared library, along with glue code for access using python ctypes.
 * Networkx a quick guide.

Geometric Algebra
The Multivector class implements geometric algebra using Python's operator overloading. It works with minimal space for any number of spatial dimensions, since it's not based on the matrix / spinor representation of Clifford algebra. Instead, it takes the basis blade approach recommended by Dorst, Fondijne, and Mann. It's really just as easy as ordering all the basis vectors, and keeping track of the commutator (+/- $$\hat 1$$).

Templates
The real world has forms, computation has templates. Pick one up, fill in the blanks, and send it down the chute.
 * NWChem Jobs
 * Slurm (USF Circe)
 * SGE (USF Circe)
 * Text conversion using text2pdf

Efficiencies
To chop a tree quickly, spend twice the time sharpening your axe.
 * vimrc files

Code Humor
Put this into your makefile: