This repository contains the report, final presentation and code for my first semester project in my Computational Science and Engieering master's degree at EPFL.
The code contains the model definitions, training and evaluation scripts for the neural networks used in the project. Everything is written in Python 3.10 and is based on Pytorch, Lightning Fabric and Wandb. It was designed to be very clear (although poorly documented), modular and extensible, and can be used for other projects as well. The data is available in the latest release of the repository.
To setup the workspace you can run the following commands:
git clone https://github.com/tudoroancea/math_591_project
cd math_591_project
mamba env create --file env.yml # or conda env create --file env.yml if you don't use mamba, but it's a shame not to use it since it's simply much MUCH faster
conda activate math_591_project
wget https://github.com/tudoroancea/math_591_project/releases/download/untagged-d3fb9058dc258922e9bc/dataset_v2.0.0.zip
unzip dataset_v2.0.0.zip -d .Then you can use the training scripts for the system identification and control tasks, and finally obtain again all the plots in my report using the evaluation scripts for the system identification and control.