Python-based domain-specific language for computational magnetism
Project description
micromagneticmodel
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 |  |
 |
|
| Linting |  |
 |
|
| Releases |  |
 |
|
| Coverage |  |
| Documentation |  |
| YouTube |  |
| Binder |  |
| Platforms |  |
| Downloads |  |
| License |  |
| DOI |  |
About
micromagneticmodel is a Python package, integrated with Jupyter, providing:
- Domain-specific language for computational magnetism.
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
-
M. Beg, M. Lang, and H. Fangohr. Ubermag: Towards more effective micromagnetic workflows. IEEE Transactions on Magnetics 58, 7300205 (2022).
-
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).
-
Marijan Beg, Martin Lang, Samuel Holt, and Hans Fangohr. micromagneticmodel: Python-based domain-specific language for computational magnetism DOI: 10.5281/zenodo.3539479 (2022).
Acknowledgements
-
OpenDreamKit – Horizon 2020 European Research Infrastructure project (676541)
-
EPSRC Programme Grant on Skyrmionics (EP/N032128/1)
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file micromagneticmodel-0.61.1.tar.gz.
File metadata
- Download URL: micromagneticmodel-0.61.1.tar.gz
- Upload date:
- Size: 30.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.10.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.8.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | bca481fe9a528deba378a32ba7ca0a015c84c697bf08859d1382cc617baf5de3 |
|
| MD5 | 3857871bc137ee0e86a8e00a6aead1a0 |
|
| BLAKE2b-256 | 506c17d1120f5073bd63d821d3e0328a0187ef7c55891bf88f84139c7a297ca9 |
File details
Details for the file micromagneticmodel-0.61.1-py3-none-any.whl.
File metadata
- Download URL: micromagneticmodel-0.61.1-py3-none-any.whl
- Upload date:
- Size: 49.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.62.3 importlib-metadata/4.10.1 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.8.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | f8f3ac1feb5654e227ce5166d07590788560e93e4fc49271f966cce7a0c8787b |
|
| MD5 | 3d34b9981ebb8cc2674d847574ebdc3e |
|
| BLAKE2b-256 | 5c12a73144cdd7c3f987bb7d0afe373772d33077a899ea4e24dac33c66102059 |
