Name: | poliastro |
---|---|
Website: | https://poliastro.github.io/ |
Author: | Juan Luis Cano Rodríguez |
Version: | 0.7.dev0 |
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)
Complete documentation, including a user guide and an API reference, can be read on the wonderful Read the Docs.
http://poliastro.readthedocs.io/en/latest/
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!
http://mybinder.org/repo/poliastro/poliastro
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 | |
Windows x64 | Appveyor |
The easiest and fastest way to get the package up and running is to install poliastro using conda:
$ conda install poliastro --channel conda-forge
You can also install poliastro from PyPI using pip, given that you already have all the requirements:
$ pip install poliastro
You can also download poliastro source from GitHub and type:
$ pip install .
Development installations are also supported:
$ pip install -e .
Warning
It is recommended that you never ever use sudo with distutils, pip, setuptools and friends in Linux because you might seriously break your system [1][2][3][4]. Options are per user directories, virtualenv or local installations.
If installed correctly, the tests can be run using pytest:
$ python -c "import poliastro.testing; poliastro.testing.test()" Running unit tests for poliastro [...] OK $
poliastro is a community project, hence all contributions are more than welcome! For more information, head to CONTRIBUTING.rst.
Release announcements and general discussion take place on our mailing list. Feel free to join!
https://groups.io/g/poliastro-dev
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:
And this is an example citation format:
Juan Luis Cano Rodríguez et al.. (2015). poliastro: poliastro 0.4.0. Zenodo. 10.5281/zenodo.17462
poliastro is released under the MIT license, hence allowing commercial use of the library. Please refer to the COPYING file.
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!
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.
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).