# boinor - Astrodynamics in Python

```{image} _static/logo_text.png
--- 
width: 675px
align: center
---
```
**boinor** is an open source ([MIT](https://opensource.org/licenses/MIT)) pure Python library
for interactive Astrodynamics and Orbital Mechanics,
with a focus on ease of use, speed, and quick visualization.
It provides a simple and intuitive {ref}`API <api-reference>`,
and handles physical quantities with units.

View the [source code](https://github.com/boinor/boinor) of boinor!

Some of its awesome features are:

- Analytical and numerical orbit propagation
- Conversion between position and velocity vectors and classical
  orbital elements
- Coordinate frame transformations
- Hohmann and bielliptic maneuvers computation
- Trajectory plotting
- Initial orbit determination (Lambert problem)
- Planetary ephemerides (using [SPICE kernels](https://naif.jpl.nasa.gov/naif/data.html) via [Astropy](https://www.astropy.org/))
- Computation of Near-Earth Objects (NEOs)

And more to come!

boinor is developed by an open, international community. Release
announcements and general discussion take place on our [mailing
list](https://groups.io/g/boinor-dev) and
[chat](http://chat.boinor.space/).

```{eval-rst}
.. raw:: html

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          position: relative;
          top: -15px;
      }
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    <form action="https://groups.io/g/boinor-dev/signup?u=3341734695881558152" method="post" id="groupsio-embedded-subscribe-form" name="groupsio-embedded-subscribe-form" target="_blank">
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```
```{figure} _static/molniya.png
---
align: right
width: 300px
alt: Molniya Orbit
---
Plot of a [Molniya orbit](https://en.wikipedia.org/wiki/Molniya_orbit) around the Earth <br />
({math}`a = 26600~\mathrm{km}, e = 0.75, i = 63.4\mathrm{^\circ}`).
```

The [source code](https://github.com/boinor/boinor), [issue
tracker](https://github.com/boinor/boinor/issues) and
[wiki](https://github.com/boinor/boinor/wiki/) are hosted on
GitHub, and all contributions and feedback are more than welcome. You
can test boinor in your browser using [Binder](https://mybinder.org/), a cloud Jupyter
notebook server:

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/boinor/boinor/main?labpath=index.ipynb)

See [benchmarks](https://benchmarks.boinor.space/) for the
performance analysis of boinor.

boinor works on the recent Python versions and is released under the
MIT license, allowing commercial use of the library.

```python
from boinor.examples import molniya
molniya.plot()
```

## Success stories

> *\"My team and I used Poliastro for our final project in our Summer
> App Space program. This module helped us in plotting asteroids by
> using the data provided to us. It was very challenging finding a
> module that can take orbits from the orbital elements, plot planets,
> and multiple ones. This module helped us because we were able to
> understand the code as most of us were beginners and make some changes
> the way we wanted our project to turn out. We made small changes such
> as taking out the axis and creating a function that will create
> animations. I am happy we used Poliastro because it helped us directs
> us in a direction where we were satisfied of our final product.\"*
>
> \-- Nayeli Ju (2017)
>
> *\"We are a group of students at University of Illinois at
> Urbana-Champaign, United States. We are currently working on a student
> AIAA/AAS satellite competition to design a satellite perform some
> science missions on asteroid (469219) 2016 HO3. We are using your
> boinor python package in designing and visualizing the trajectory
> from GEO into asteroid's orbit. Thank you for your work on boinor,
> especially the APIs that are very clear and informational, which helps
> us significantly.\"*
>
> \-- Yufeng Luo (University of Illinois at Urbana-Champaign, United
> States, 2017)
>
> *\"We, at the Institute of Space and Planetary Astrophysics (ISPA,
> University of Karachi), are using Poliastro as part of Space Flight
> Dynamics Text Book development program. The idea is to develop a book
> suitable for undergrad students which will not only cover theoretical
> background but will also focus on some computational tools. We chose
> Poliastro as one of the packages because it was very well written and
> provided results with good accuracy. It is especially useful in
> covering some key topics like the Lambert\'s problem. We support the
> use of Poliastro and open source software because they are easily
> accessible to students (without any charges, unlike some other tools).
> A great plus point for Poliastro is that it is Python based and Python
> is now becoming a very important tool in areas related to Space
> Sciences and Technologies.\"*
>
> \-- Prof. Jawed iqbal, Syed Faisal ur Rahman (ISPA, University of
> Karachi, 2016)

------------------------------------------------------------------------

## Contents

```{toctree}
---
maxdepth: 2
caption: Tutorials
---
installation
quickstart
```

```{toctree} 
---
maxdepth: 2
caption: How-to guides & Examples
---
gallery
contributing
```

```{toctree} 
---
maxdepth: 2 
caption: Reference
---
api
bibliography
changelog
```

```{toctree}
---
maxdepth: 2
caption: Background
---
history
related
background
```

```{note}
Older versions of boinor relied on some Fortran subroutines written
by David A. Vallado for his book \"Fundamentals of Astrodynamics and
Applications\" and available on the Internet as the [companion software
of the book](http://celestrak.com/software/vallado-sw.asp). The author
explicitly gave permission to redistribute these subroutines in this
project under a permissive license.
```