This project aims on making the algorithms covered in the corresponding lecture at LMU Munich easier to understand by providing step-by-step logging and result visualization.

You can run the scripts without installing anything on your computer by clicking at the green "Code" button in the top right corner, then on the tab "Codespaces" and then "Create Codespace on Main". Don't worry about the "Codespace usage for this repository is paid by..." note - nothing will be charged without explicit consent of users and the storage and compute requirements of this repository are very unlikely to exceed the limits of the free plan.

This repository provides a convenient way to use a VS Code development container. To get started, make sure you have the following installed:

• Docker
• VS Code
• The Remote-Containers extension of VS Code

Once you have these dependencies installed, you can open the repository in VS Code and click the green button in the bottom left corner. This action will launch the repository within a Docker container that includes all the necessary dependencies.

If you are using Linux, you can simply run the setup.sh script. For other operating systems, you can examine the script to determine the dependencies and install them manually.

If you encounter a bug or have a feature request, please feel free to open an issue in this repository.

If you would like to contribute to this repository, please submit a pull request. Here's how you can do it:

1. Fork this repository to create your own copy.
2. Make the necessary changes in your fork.
3. Open a pull request from your fork to this repository. If you're planning on making substantial changes, it's recommended to first open an issue to discuss the proposed modifications. If you would like to contribute regularly, you can request to be added as a collaborator to this repository.

If you have any questions, please don't hesitate to reach out to the maintainer of this repository at [email protected].