Python and SymPy
Getting started
- TM Quest has 11 nice videos to learn the basics of SymPy. The playlist is here: https://youtube.com/playlist?list=PLSE7WKf_qqo1T5VV1nqXTj2iNiSpFk72T
- Introductory tutorial to give an introduction to SymPy: https://docs.sympy.org/latest/tutorials/intro-tutorial/index.html
- VS Code has a nice introduction to using Jupyter Notebooks in VS Code: https://youtu.be/DA6ZAHBPF1U
Documentation
Giver SymPy fejl eller kan du ikke huske en kommandos navn? Tjek dokumentationen: https://docs.sympy.org/latest/index.html. Hvis man fx vil løse en diff lign, kan man blot google solve differential equation site:https://docs.sympy.org. Husk at bruge site:https://docs.sympy.org hvis du kun vil søge i dokumentationen. Der findes i øvrigt mange gode tutorials der. Dokumentationen til det generelle Python findes her: https://docs.python.org/3/
Lecture Notes
- Hvis man ønsker lærebogsnoter, har Niels Bohr Instituttet skrevet en Jupyter Notebook der bruges i et fysik og et mat-kursus på KU. Hele noten kan være brugbar, men kun afsnit 5 handler om SymPy: https://python-intro.nbi.ku.dk/notebooks/sympy/Notebook2.html
Textbooks on Python
If you are after an introduction to Python (not SymPy) for scientific application: Uni of Olso uses in their programmering course Introduction to programming for scientific applications (IN1900):
- Joakim Sundnes: Introduction to Scientific Programming with Python (150 pages) https://findit.dtu.dk/en/catalog/5f31372fd9001d01776f3d9a which is a short version of:
- Langtangen, Hans Petter: A Primer on Scientific Programming with Python (900 pages): https://findit.dtu.dk/en/catalog/5e57be22d9001d01917e1e90
Both books are free to download for DTU students.
Python resources for teaching at NBI
Python resources for teaching at NBI, including many Jupyter Notebooks, can be found here: https://cholmcc.gitlab.io/nbi-python/
VS Code
VS Code has many useful tutorials on the youtube channel: https://www.youtube.com/c/Code/videos