Python package for definition, reading, and visualisation of finite-difference fields.
Project description
discretisedfield
Marijan Beg1,2, Martin Lang1, Ryan A. Pepper1, Thomas Kluyver1,2, and Hans Fangohr1,2,3
1 Faculty of Engineering and Physical Sciences, University of Southampton, Southampton SO17 1BJ, United Kingdom
2 European XFEL GmbH, Holzkoppel 4, 22869 Schenefeld, Germany
3 Max Planck Institute for the Structure and Dynamics of Matter, Luruper Chaussee 149, 22761 Hamburg, Germany
| Description | Badge |
|---|---|
| Tests |  |
 |
|
| Releases |  |
 |
|
| Coverage |  |
| Documentation |  |
| YouTube |  |
| Binder |  |
| Platforms |  |
| Downloads |  |
| License |  |
| DOI |  |
About
discretisedfield is a Python package, integrated with Jupyter, providing:
-
definition of finite-difference regions, meshes, lines, and fields,
-
analysis of finite-difference fields,
-
visualisation using
matplotlibandk3d, and -
manipulation of different file types (OVF, VTK, and HDF5).
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 (@sergii-mamedov), European XFEL, Germany
- Natalie Downing (@gamdow), University of Southampton, United Kingdom
- Min RK (@minrk), Simula Research Laboratory, Norway
- Rebecca Carey (@rlc2v07), University of Southampton, United Kingdom
License
Licensed under the BSD 3-Clause "New" or "Revised" License. For details, please refer to the LICENSE file.
How to cite
-
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).
-
M. Beg, M. Lang, R. A. Pepper, T. Kluyver, and H. Fangohr. discretisedfield: Python package for the analysis and visualisation of finite-difference fields. DOI: 10.5281/zenodo.3539461 (2021).
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 discretisedfield-0.10.tar.gz.
File metadata
- Download URL: discretisedfield-0.10.tar.gz
- Upload date:
- Size: 1.9 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.25.1 setuptools/51.0.0.post20201207 requests-toolbelt/0.9.1 tqdm/4.55.1 CPython/3.8.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | f9545131b912f9a8a44edb23c4483ff2459990627063f11ee5336c86e868bfcc |
|
| MD5 | d7ff2b07bef30fa1719293d3e90794f1 |
|
| BLAKE2b-256 | 10cdfbba285f8b9127cb4ad5ee32ae90a0678fb3c718054a08297468792466ed |
File details
Details for the file discretisedfield-0.10-py3-none-any.whl.
File metadata
- Download URL: discretisedfield-0.10-py3-none-any.whl
- Upload date:
- Size: 1.9 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.25.1 setuptools/51.0.0.post20201207 requests-toolbelt/0.9.1 tqdm/4.55.1 CPython/3.8.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 97c29dd1870a675347c2eecfd8d45202acf1f3a667e31c2848d4e8d623877350 |
|
| MD5 | 64b9f0817a4ead2cf815dc621584d090 |
|
| BLAKE2b-256 | 01c85c7b8e4885426c8b422740e55bd7a209425cd0375bd35ae53c8f2d403f66 |
