Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/esa/pykep
PyKEP is a scientific library providing basic tools for research in interplanetary trajectory design.
https://github.com/esa/pykep
aerospace astrodynamics interplanetary mission-analysis
Last synced: about 6 hours ago
JSON representation
PyKEP is a scientific library providing basic tools for research in interplanetary trajectory design.
- Host: GitHub
- URL: https://github.com/esa/pykep
- Owner: esa
- License: gpl-3.0
- Created: 2013-03-12T20:11:29.000Z (almost 12 years ago)
- Default Branch: master
- Last Pushed: 2023-04-17T15:04:13.000Z (over 1 year ago)
- Last Synced: 2024-04-14T10:15:28.242Z (8 months ago)
- Topics: aerospace, astrodynamics, interplanetary, mission-analysis
- Language: C++
- Homepage: http://esa.github.io/pykep/
- Size: 56.8 MB
- Stars: 324
- Watchers: 38
- Forks: 91
- Open Issues: 21
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
Awesome Lists containing this project
- awesome-robotic-tooling - pykep - A scientific library providing basic tools for research in interplanetary trajectory design. (Planning and Control / Vector Map)
README
pykep
=====[![Join the chat at https://gitter.im/esa/pykep](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/esa/pykep?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
[![Build Status](https://api.travis-ci.org/esa/pykep.svg?branch=master)](https://travis-ci.org/esa/pykep) [![Code Health](https://landscape.io/github/esa/pykep/master/landscape.svg?style=flat)](https://landscape.io/github/esa/pykep/master)
pykep is a scientific library providing basic tools for astrodynamics research. Algorithmic efficiency is
a main focus of the library, which is written in C++ and exposed to Python using the boost::python library. At the library core
is the implementation of an efficient solver for the multiple revolutions Lambert's problem, objects representing
direct (Sims-Flanagan), indirect (Pontryagin) and hybrid methods to represent low-thrust optimization problems,
efficient keplerian propagators, Taylor-integrators, a SGP4 propagator, TLE and SATCAT support and more.Check the official documentation at https://esa.github.io/pykep/