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Name:poliastro
Website:https://poliastro.github.io/
Author:Juan Luis Cano Rodríguez orcid
Version:0.9.dev0

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docs license doi astropy mailing Join the chat at https://gitter.im/poliastro/poliastro

poliastro is an open source pure Python package dedicated to problems arising in Astrodynamics and Orbital Mechanics, such as orbit propagation, solution of the Lambert's problem, conversion between position and velocity vectors and classical orbital elements and orbit plotting, focusing on interplanetary applications. It is released under the MIT license.

from poliastro.examples import molniya
from poliastro.plotting import plot

plot(molniya)

https://github.com/poliastro/poliastro/raw/master/docs/source/examples/molniya.png

Documentation

docs

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

http://docs.poliastro.space/en/latest/

Examples

mybinder

In the examples directory you can find several Jupyter notebooks with specific applications of poliastro. 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/poliastro/poliastro/master?filepath=index.ipynb

Requirements

poliastro requires the following Python packages:

  • NumPy, for basic numerical routines
  • Astropy, for physical units and time handling
  • numba (optional), for accelerating the code
  • jplephem, for the planetary ephemerides using SPICE kernels
  • matplotlib, for orbit plotting
  • SciPy, for root finding and numerical propagation

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

Platform Site Status
Linux & 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 poliastro using conda:

$ conda install poliastro --channel conda-forge

Please check out the documentation for alternative installation methods.

Testing

codecov

If installed correctly, the tests can be run using pytest:

$ python -c "import poliastro.testing; poliastro.testing.test()"
Running unit tests for poliastro
[...]
OK
$

Problems

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

Contributing

'Stories in Ready'

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

Support

mailing

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

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

Citing

If you use poliastro on your project, please drop me 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:

Juan Luis Cano Rodríguez et al.. (2015). poliastro: poliastro 0.4.0. Zenodo. 10.5281/zenodo.17462

License

license

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

FAQ

What's up with the name?

poliastro comes from Polimi, which is the shortened name of the Politecnico di Milano, the Italian university where I was studying while writing this software. It's my tiny tribute to a place I came to love. Grazie mille!

Can I do <insert awesome thing> with poliastro?

poliastro is focused on interplanetary applications. This has two consequences:

  • It tries to be more general than other Flight Dynamics core libraries more focused on Earth satellites (see Related software for a brief list), allowing the algorithms to work also for orbits around non-Earth bodies.
  • It leaves out certain features that would be too Earth-specific, such as TLE reading, SGP4 propagation, groundtrack plotting and others.

Keep that in mind when asking for a feature. For a software package focused on Earth applications please refer to the Python Astrodynamics Project, a still in progress joint effort between several developers.

What's the future of the project?

poliastro is actively maintained and will receive bug fixes and releases in 2017, maintaining its focus on interplanetary applications. Expect better algorithms, easier 3D plotting and optimization techniques. The best way to get an idea of the roadmap is to check the Kanban board at Waffle.io (see Contributing).

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poliastro - 🚀 Astrodynamics in Python

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