https://github.com/kylermurphy/astr288p_2018, our github repo (code, lectures, homework, etc.)
The goal is for the student to be comfortable using the UNIX environment and introduce students to scientific programming in Python and C (with emphasis on Python). Students will learn how to operate within an UNIX environment and run commands within a Linux, Mac, or Windows Bash terminal (lab machines run Scientific Linux 6.7). Students will learn the basics of scientific programming including, code correctness and good programming style, numerical methods/analysis, and visualizing results.
Students will also be made comfortable installing and using open source software, which includes collaborating and sharing their own code. Exact details of the material covered will depend on existing level of experience of the class participants.
A more advanced version of this class is
ASTR415 (Computational Astrophysics).
After successfully completing this course you will be able to:
- Work within a Unix and terminal environment.
- Work with basic scripts and python coding.
- Install open source software.
- Visualize scientific data.
- Analyze scientific data.
- Week 1: Jan 21 – Jan 27: No Class
- Week 2: Jan 28 – Feb 3: Introduction and Assessments
- Week 3: Feb 4 – Feb 10: Unix (shells, files and directories), GIT
- Week 4: Feb 11 – Feb 17: More on Unix (file commands, scripting, permissions)
- Week 5: Feb 18 – Feb 24: Unix/Python (remote access, paths, variables, miniconda)
- Week 6: Feb 25 – Mar 3: Python (jupyter, variable types, control flow)
- Week 7: Mar 4 – Mar 10: Python (arrays, plotting) Guest Lecture
- Week 8: Mar 11 – Mar 17: Python scientific programming and numerical methods
- Week 9: Mar 18 – Mar 24: Spring Break, no lecture
- Week 10: Mar 25 – Mar 31: Python scientific programming and numerical methods
- Week 11: Apr 1 – Apr 7: Python scientific programming and numerical methods
- Week 12: Apr 8 – Apr 14: Python scientific programming and numerical methods
- Week 13: Apr 15 – Apr 21: Python scientific programming and numerical methods
- Week 14: Apr 22 – Apr 28: Python scientific programming and numerical methods
- Week 15: Apr 29 – May 5: Final Presentations
- Week 16: May 6 – May 12: Last class, recapping (continued presentations if required).
For each topic below there are more references than would fit on a page.
- Unix/Linux references:
- Python references:
- C references: