Skip to main content

Python package for manipulating tabular data.

Project description

ubermagtable

Marijan Beg1,2, Martin Lang1, Ryan A. Pepper1, Thomas Kluyver2, 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 workflow
conda
Releases PyPI version
Anaconda-Server Badge
Coverage codecov
Documentation Documentation Status
YouTube YouTube
Binder Binder
Platforms Platforms
Downloads Downloads
License License
DOI DOI

About

ubermagtable is a Python package providing:

  • reading scalar data files (OOMMF .odt and mumax3 .txt),

  • merging multiple tables, and

  • visualisation of scalar table 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:

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, 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).

  2. M. Beg, R. A. Pepper, M. Lang, T. Kluyver, and H. Fangohr. ubermagtable: Python package for manipulating tabular data. DOI: 10.5281/zenodo.3539492 (2021).

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

ubermagtable-0.4.tar.gz (165.4 kB view details)

Uploaded Source

Built Distribution

ubermagtable-0.4-py3-none-any.whl (180.4 kB view details)

Uploaded Python 3

File details

Details for the file ubermagtable-0.4.tar.gz.

File metadata

  • Download URL: ubermagtable-0.4.tar.gz
  • Upload date:
  • Size: 165.4 kB
  • 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/4.55.0 CPython/3.8.5

File hashes

Hashes for ubermagtable-0.4.tar.gz
Algorithm Hash digest
SHA256 675fdf7e25d7514e3b132127433312bd0d757a1b88d9aca1f57d05e7abdcb5de
MD5 595fdffc99caa4a8560756222cf5ea8c
BLAKE2b-256 1a9a40d90620e878b3a0c8c716eb05ceea234eccd2f135be492ff9f2e5cd92c7

See more details on using hashes here.

File details

Details for the file ubermagtable-0.4-py3-none-any.whl.

File metadata

  • Download URL: ubermagtable-0.4-py3-none-any.whl
  • Upload date:
  • Size: 180.4 kB
  • 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/4.55.0 CPython/3.8.5

File hashes

Hashes for ubermagtable-0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 b34f24f615a3c3eaec094e69a33fdfb62452eee284957daa6d00fd1e281bbdcd
MD5 2385094b5eaccd6761ab4a53ebbfbb5f
BLAKE2b-256 65ee3f74b63e3c1c40f57257f86c363fde3f65e4848c288f93115da3240449bb

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