Skip to main content

Testing package for computational magnetism tools.

Project description

micromagnetictests

Marijan Beg1,2, Martin Lang2, Samuel Holt2,3, and Hans Fangohr2,4,5

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 Build status
conda
Linting pre-commit.ci status
Releases PyPI version
Anaconda-Server Badge
Coverage codecov
Documentation Documentation
YouTube YouTube
Binder Binder
Platforms Platforms
Downloads Downloads
License License
DOI DOI

About

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

  • A collection of computational magnetism tests for testing different calculators

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:

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, and Hans Fangohr. micromagnetictests: Testing package for computational magnetism tools. DOI: 10.5281/zenodo.3707736 (2022).

Acknowledgements

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

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

micromagnetictests-0.61.0.tar.gz (19.9 kB view details)

Uploaded Source

Built Distribution

micromagnetictests-0.61.0-py3-none-any.whl (34.2 kB view details)

Uploaded Python 3

File details

Details for the file micromagnetictests-0.61.0.tar.gz.

File metadata

  • Download URL: micromagnetictests-0.61.0.tar.gz
  • Upload date:
  • Size: 19.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.12

File hashes

Hashes for micromagnetictests-0.61.0.tar.gz
Algorithm Hash digest
SHA256 0cd817becd55ef73a8965963b849138d4ab63fddd3d5cac58a998e3c4d1d19c9
MD5 6b00532a3b6a98dc0374cae62c83b90b
BLAKE2b-256 6b41666721c0feff988ce814077d12703a7d33c493c874cdb597c6d1d2758c62

See more details on using hashes here.

File details

Details for the file micromagnetictests-0.61.0-py3-none-any.whl.

File metadata

  • Download URL: micromagnetictests-0.61.0-py3-none-any.whl
  • Upload date:
  • Size: 34.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.12

File hashes

Hashes for micromagnetictests-0.61.0-py3-none-any.whl
Algorithm Hash digest
SHA256 ac6faa6f0d849e18da177a88d95098f413ff73fcf4a0a8691f686c183a2f144d
MD5 3193885b21f82a207a8a7ab3b3ded7fb
BLAKE2b-256 15eed38447d50708b1bac6e4806a9cfdbdb745a3dacbd465de8b581d62e98b78

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page