A (personal) collection of implementations of various computational science/scientific computing concepts and algorithms. Comments/improvements/criticisms are welcome! This is a part of my self-directed learning journey on various topics in the field of computational science so there will be A LOT of mistakes and errors. Please feel free to point them you if you happen to any!
These are the topics that I've finished working on but some haven't been compiled into their own notebooks yet, so I'll upload them when they're properly organized.
- ✔ Floating point numbers and computational errors
- ✔ Computational Linear Algebra
- ✔ Iterative methods for non-linear equations
- ❓ Dynamical systems - Differential equations & Non-linear coupled differential models
- ❓ Stochastic modelling and simulation
- ❓ Monte Carlo simulation: Buffon's needle, probabilistic dice game, function approximation
- ❓ Monte Carlo simulation for Stochastic SIR modelling
- ❓ Rejection sampling
- ❓ Markov chain models
- ❓ Heuristic simulation & optimization
- ❓ Simulated annealing
- ❓ Genetic algorithm
- ❓ Game theory
- ❓ Iterated dominance
- ❓ Best-response strategy
- ❓ Non-degenerate game Nash equilibria
- ❓ Monte Carlo approximation for unique Nash equilibria
All the scripts for this collection is written in Jupyter/IPython notebooks for ease of use and sharing! If you are new to Python and/or IPython notebooks, please see the following quick guide on how to get Jupyter installed and running: https://realpython.com/jupyter-notebook-introduction/.
As mentioned above, anyone can make contributions (adding new contents/topics or adding/fixing existing ones), simply put in a PR or contact me via lennemo09@gmail.com.
Please be aware of plagiarism policies if you plan to use/reference the code for university assignments or academic works and also it is very likely that I have made (a lot of) mistakes since it is purely written and reviewed by me and no one else.