MUSE2 data analysis

⚠️ Note that this repository is currently a work in progress. ⚠️

This repository contains Python scripts and Jupyter notebooks for analysing and visualising MUSE2 data files.

We recommend using uv for installing dependencies and managing your virtual environment.

Usage

To get started:

1. Download and install uv following the instructions for your OS.

2. Install the package and dependencies and set up the virtual environment:

   uv sync

3. Activate the virtual environment, or just preface your commands with uv run to use the virtual environment (see uv docs for more info).

   To activate on Linux/macOS:

   source .venv/bin/activate
   <command>

   To activate on Windows:

   .venv\Scripts\activate

   Or run the command directly:

   uv run <command>

4. Make sure the Python code can find your MUSE2 installation. (If you have not yet installed MUSE2, follow the instructions here.)

   There are two ways you can do this:

   1. Make sure the muse2 executable is on your PATH:

      • Instructions for Windows
      • Instructions for Linux
      • Instructions for macOS

      (If you installed MUSE2 with cargo, it should already be on your PATH.)

   2. Set the MUSE2_PATH environment variable to the full path of the muse2 executable file.

      You can either do this by setting the environment variable from within Jupyter or from your shell before you launch Jupyter notebook.

There are some example notebooks in the notebooks folder to get you started. You can view these with Jupyter notebook, like so:

uv run jupyter notebook

If you are using Visual Studio Code, you can also view them directly in your IDE with the Jupyter extension.

Copyright

Copyright © 2026 Imperial College London