.. riccipy
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:Name: RicciPy :Website: https://riccipy.einsteinpy.org/ :Version: 0.1.dev0
|mailing| |gitter| |riotchat| |license| |docs|
|circleci| |travisci| |appveyor| |codecov| |codeclimate|
RicciPy is an open source package that exists as part of The EinsteinPy Project for the purpose of providing a API that makes tensor algebra as easy as possible on arbitrary manifolds. RicciPy implements the use of Sympy for representing tensor equations and expressions symbolically with automatic applications of a metric when contracting indices. Lastly, the Library also provides a means for converting the results of tensor equations to numpy-like functions for use in numerical calculations. It is released under the MIT license.
|docs|
Complete documentation, including a user guide and an API reference, can be read on
the wonderful Read the Docs_.
https://doc.riccipy.einsteinpy.org/
.. _Read the Docs: https://readthedocs.org/
RicciPy requires the following Python packages:
The easiest and fastest way to get the package up and running is to
install EinsteinPy using conda <http://conda.io>_::
$ conda install einsteinpy --channel conda-forgeOr for Debian/Ubuntu/Mint users, the package is installable from apt <https://packages.debian.org/sid/python3-einsteinpy>_::
$ sudo apt install python3-einsteinpyPlease note that the package version in Debian Repositories might not be the latest. But it will be definitely the most stable version of EinsteinPy available till date.
Please check out the guide for alternative installation methods_.
.. _guide for alternative installation methods: https://einsteinpy.github.io/installation/
|codecov|
If installed correctly, the tests can be run using pytest::
$ python -c "import einsteinpy.testing; einsteinpy.testing.test()"
============================= test session starts ==============================
platform linux -- Python 3.7.1, pytest-4.3.1, py-1.8.0, pluggy-0.9.0
rootdir: /home/shreyas/Local Forks/einsteinpy, inifile: setup.cfg
plugins: remotedata-0.3.1, openfiles-0.3.1, doctestplus-0.3.0, cov-2.5.1, arraydiff-0.3
collected 56 items
[...]
==================== 56 passed, 1 warnings in 28.19 seconds ====================
$If the installation fails or you find something that doesn't work as expected,
please open an issue in the issue tracker_.
.. _issue tracker: https://github.com/einsteinpy/riccipy/issues
RicciPy is a community project, hence all contributions are more than
welcome! For more information, head to CONTRIBUTING.rst_.
.. _CONTRIBUTING.rst: https://github.com/einsteinpy/riccipy/blob/master/CONTRIBUTING.rst
Developers Documentation can be found here.
|mailing|
Release announcements and general discussion take place on our mailing list_.
Feel free to join!
.. _mailing list: https://groups.io/g/einsteinpy-dev
https://groups.io/g/einsteinpy-dev
Please join our [matrix] channel or gitter chat room for further queries.
.. _[matrix]: https://matrix.to/#/#einsteinpy:matrix.org
.. _gitter: https://gitter.im/EinsteinPy-Project/EinsteinPy
If you still have a doubt, write a mail directly to developers@einsteinpy.org <mailto:developers@einsteinpy.org>_.
If you use EinsteinPy on your project, please
drop us a line <mailto:developers@einsteinpy.org>_.
You can also use the DOI to cite it in your publications. This is the latest one:
|doi|
And this is an example citation format::
Shreyas Bapat et al.. (2019). EinsteinPy: riccipy 0.1.0. Zenodo. 10.5281/zenodo.2582388
|license|
RicciPy is released under the MIT license, hence allowing commercial
use of the library. Please refer to COPYING_.
.. _COPYING: https://github.com/einsteinpy/riccipy/blob/master/COPYING
EinsteinPy comes from the name of the famous physicist, Nobel laureate, revolutionary person, Prof. Albert Einstein. This is a small tribute from our part for the amazing work he did for the humanity!
EinsteinPy is focused on general relativity. One can always discuss probable features on the mailing list and try to implement it. We welcome every contribution and will be happy to include it in EinsteinPy.
EinsteinPy is actively maintained and we hope to receive an influx of new contributors.
The best way to get an idea of the roadmap is to see the Milestones_ of
the project.
.. _Milestones: https://github.com/einsteinpy/einsteinpy/milestones
The whole documentation and code structure is shamelessly inspired by poliastro_ . We really thank the poliastro
developers to make this possible. EinsteinPy is nothing without it's supporters.
.. _poliastro: https://docs.poliastro.space/