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Code for analyzing and evaluating stellarator plasma shapes

Project description

A dark Proxima logo in light color mode and a light one in dark color mode.

ConStellaration: A dataset of QI-like stellarator plasma boundaries and optimization benchmarks

ConStellaration is a dataset of diverse QI-like stellarator plasma boundary shapes, paired with their ideal-MHD equilibria and performance metrics.
The dataset is available on Hugging Face.
The repository contains a suite of tools and notebooks for exploring the dataset, including a forward model for plasma simulation and scoring functions for optimization evaluation.

Installation

The following instructions have been tested on Ubuntu 22.04. Other platforms may require additional steps and have not been validated.

The system dependency libnetcdf-dev is required for running the forward model. On Ubuntu, please ensure it is installed before proceeding, by running:

sudo apt-get install libnetcdf-dev

Install from PyPI

The package can be installed directly from PyPI:

pip install constellaration

Install by cloning the repository

  1. Clone the repository:
git clone https://github.com/proximafusion/constellaration.git
cd constellaration
  1. Install the required Python dependencies:
pip install .

Running with Docker

If you prefer not to install system dependencies, you can use the provided Dockerfile to build a Docker image and run your scripts in a container.

  1. Build the Docker image:
docker build -t constellaration .
  1. Run your scripts by mounting a volume to the container:
docker run --rm -v $(pwd):/workspace constellaration python relative/path/to/your_script.py

Replace your_script.py with the path to your script. The $(pwd) command mounts the current directory to /workspace inside the container.

Explanation Notebook

You can explore the functionalities of the repo through the Boundary Explorer Notebook.

Citation

If you find this work useful, please cite us:

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