Welcome to McCode Academy!
We hope that this is a nice stepping stone between learning basic python and jumping into research! (or a nice introduction into the tools we use to problem solve in the group) Working through these samples will introduce you to (what we have deemed) helpful functions and tricky tricks for commonly addressed problems in the group. If you’d like an introduction to the kind of mindset we use when figuring out how to solve problems in quantum chemistry, we have that here.
Here’s a basic road map we think you might find useful:
- Getting Started: introduction to programs, scripts, and common pitfalls
- NumPy and SciPy: working with big blocks of numbers
- Data/IO: getting data into your programs and writing it back out
- Plotting: finding ways to plot what you’ve done
- Git + Github: using version control software to help yourself and others
- Programming Tips: writing code that other people can read and reuse
- Supercomputing at UW: logging in and using Supercomputing Resources available to the McCoy Group
Exercises
There’s no better way to get good at something than practice, so we’ve created a number of exercises that you can work through that’ll hopefully help you build up your self-confidence and prepare you for tackling your own research problems. We’ve written them to follow good programming practices (remember: comments are your friends) that’ll help make your code easier to debug, share with others, or revisit after a few weeks. »
Feel free to let us know if you run into any issues or if you want to contribute.
Got questions? Ask them on the McCoy Group Stack Overflow