micromagneticdata

Marijan Beg^1,2, Martin Lang², Samuel Holt^2,3, Swapneel Amit Pathak^2,4, and Hans Fangohr^2,4,5

¹ Department of Earth Science and Engineering, Imperial College London, London SW7 2AZ, UK
² Faculty of Engineering and Physical Sciences, University of Southampton, Southampton SO17 1BJ, UK
³ Department of Physics, University of Warwick, Coventry CV4 7AL, UK
⁴ Max Planck Institute for the Structure and Dynamics of Matter, Luruper Chaussee 149, 22761 Hamburg, Germany
⁵ Center for Free-Electron Laser Science, Luruper Chaussee 149, 22761 Hamburg, Germany

Description	Badge
Tests
Linting
Releases
Coverage
Documentation
YouTube
Binder
Platforms
Downloads
License
DOI

About

micromagneticdata is a Python package, integrated with Jupyter, providing:

• The analysis of computational magnetism data.

It is available on Windows, MacOS, and Linux. It requires Python 3.8+.

Documentation

APIs and tutorials are available in the documentation. To access the documentation, use the badge in the table above.

Installation, testing, and upgrade

We recommend installation using conda package manager. Instructions can be found in the documentation.

Binder

This package can be used in the cloud via Binder. To access Binder, use the badge in the table above.

YouTube

YouTube video tutorials are available on the Ubermag channel.

Support

If you require support, have questions, want to report a bug, or want to suggest an improvement, please raise an issue in ubermag/help repository.

Contributions

All contributions are welcome, however small they are. If you would like to contribute, please fork the repository and create a pull request. If you are not sure how to contribute, please contact us by raising an issue in ubermag/help repository, and we are going to help you get started and assist you on the way.

Contributors:

• Sergii Mamedov

License

Licensed under the BSD 3-Clause "New" or "Revised" License. For details, please refer to the LICENSE file.

How to cite

1. M. Beg, M. Lang, and H. Fangohr. Ubermag: Towards more effective micromagnetic workflows. IEEE Transactions on Magnetics 58, 7300205 (2022).

2. M. Beg, R. A. Pepper, and H. Fangohr. User interfaces for computational science: A domain specific language for OOMMF embedded in Python. AIP Advances 7, 56025 (2017).

3. Marijan Beg, Martin Lang, Samuel Holt, Swapneel Amit Pathak, and Hans Fangohr. micromagneticdata: Python tools for the analysis of computational magnetism data DOI: 10.5281/zenodo.4624869 (2025).

Acknowledgements

• OpenDreamKit – Horizon 2020 European Research Infrastructure project (676541)

• EPSRC Programme Grant on Skyrmionics (EP/N032128/1)