Skip to main content
Join the official 2019 Python Developers SurveyStart the survey!

Python package for General Relativity

Project description

EinsteinPy logo
Name:EinsteinPy
Website:https://einsteinpy.org/
Version:0.2.1

astropy mailing Join the chat at https://gitter.im/EinsteinPy-Project/EinsteinPy riotchat license docs

circleci travisci appveyor codecov Maintainability

EinsteinPy is an open source pure Python package dedicated to problems arising in General Relativity and gravitational physics, such as geodesics plotting for Schwarzschild, Kerr and Kerr Newman space-time model, calculation of Schwarzschild radius, calculation of Event Horizon and Ergosphere for Kerr space-time. Symbolic Manipulations of various tensors like Metric, Riemann, Ricci, Ricci Scalar, Weyl, Schouten, Stress-Energy-Momentum, Einstein and Christoffel Symbols is also possible using the library. EinsteinPy also features Hypersurface Embedding of Schwarzschild space-time, which will soon lead to modelling of Gravitational Lensing! It is released under the MIT license.

Documentation

docs

Complete documentation, including a user guide and an API reference, can be read on the wonderful Read the Docs.

https://docs.einsteinpy.org/

Examples

mybinder

In the examples directory, you can find several Jupyter notebooks with specific applications of einsteinpy. You can consider theses Jupyter Notebooks as tutorials for einsteinpy. You can launch a cloud Jupyter server using binder to edit the notebooks without installing anything. Try it out!

https://beta.mybinder.org/v2/gh/einsteinpy/einsteinpy/master?filepath=index.ipynb

Requirements

EinsteinPy requires the following Python packages:

  • NumPy, for basic numerical routines
  • Astropy, for physical units and time handling
  • Matplotlib, for static geodesics plotting and visualizations.
  • Plotly, for interactive geodesics plotting and visualizations.
  • SciPy, for solving ordinary differential equations.
  • SymPy, for symbolic calculations related to GR.
  • Numba (optional), for accelerating the code

EinstienPy is usually tested on Linux, Windows and OS X on Python 3.5, 3.6 and 3.7 against latest NumPy.

Platform Site Status
Linux CircleCI circleci
OS X Travis CI travisci
Windows x64 Appveyor appveyor

Installation

The easiest and fastest way to get the package up and running is to install EinsteinPy using conda:

$ conda install einsteinpy --channel conda-forge

Or for Debian/Ubuntu/Mint users, the package is installable from apt:

$ sudo apt install python3-einsteinpy

Please 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.

Testing

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 ====================
$

Problems

If the installation fails or you find something that doesn’t work as expected, please open an issue in the issue tracker.

Contributing

EinsteinPy is a community project, hence all contributions are more than welcome! For more information, head to CONTRIBUTING.rst.

Developers Documentation can be found here.

Support

mailing

Release announcements and general discussion take place on our mailing list. Feel free to join!

https://groups.io/g/einsteinpy-dev

Please join our [matrix] channel or gitter chat room for further queries.

If you still have a doubt, write a mail directly to developers@einsteinpy.org.

Citing

If you use EinsteinPy on your project, please drop us a line.

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: einsteinpy 0.2.1 Zenodo. 10.5281/zenodo.2582388

License

license

EinsteinPy is released under the MIT license, hence allowing commercial use of the library. Please refer to COPYING.

FAQ

Why Einstein-Py?

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!

Can I do <insert nerdy thing> with EinsteinPy?

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.

What’s the future of the project?

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.

Inspiration

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.

Project details


Download files

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

Files for einsteinpy, version 0.2.1
Filename, size File type Python version Upload date Hashes
Filename, size einsteinpy-0.2.1-py3-none-any.whl (91.1 kB) File type Wheel Python version py3 Upload date Hashes View hashes
Filename, size einsteinpy-0.2.1.tar.gz (5.4 MB) File type Source Python version None Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page