Generate and manipulate semi-analytic models of planet wakes
Project description
Generate and manipulate semi-analytic models of planet wakes
Quickstart tutorial »
Documentation »
Overview
wakeflow
is a Python package primarily for calculating tidally-induced perturbations resulting from a planet embedded in a gas disk. It is an implementation of both the linear theory for planet wake generation (Goldreich and Tremaine 1979) and the non-linear theory of wake propagation (Rafikov 2002) in 2D. wakeflow
lets you generate these models by specifying disk and system properties as typically parameterised in the planet formation literature. It also contains additional tools allowing you to:
- Visualise your results
- Create 3D models under some assumptions
- Interface directly with the radiative transfer code MCFOST to generate synthetic images of these models
- (Planned) Rotate and project your models to create line-of-sight maps of velocity perturbations at some emitting layer
- (Planned) Create analytic predictions for peak velocity maps as found in Calcino et al. 2022
Installation
wakeflow
may be most easily installed from the Python Package Index (PyPI), or can also be installed from the GitHub repository if you wish make contributions. Dependencies for wakeflow
consist mostly of standard python libraries. We recommend using a package manager such as Anaconda to make your life easier, but this is not required.
Dependencies
Python packages:
PyPI (pip)
The easiest way to install wakeflow
is via PyPI, using pip
:
pip install wakeflow
that's it!
From source (GitHub)
If you want to contribute to, or modify wakeflow
, you should install it from the GitHub repository. Simply fork the repo using the button in the top right, and then clone it:
git clone https://github.com/<replace-by-your-username>/wakeflow.git
Alternatively, you may install from source even if you do not with to edit wakeflow
, in which case I would recommend skipping the fork and simply cloning the repo directly:
git clone https://github.com/TomHilder/wakeflow.git
Navigate to the directory it is installed in:
cd wakeflow
You can verify that you are in the correct directory by checking that you see README.md
when you run:
ls
Now we use pip
to create a local and editable install of wakeflow
:
python -m pip install -e .
Do not forget the dot (.) in the above command, as it tells pip
to look in the current working directory (where wakeflow
is). The advantage of installing this way is that it places a link to wakeflow
in your site-packages
folder instead of moving it there. Now when you edit the code in wakeflow/src/wakeflow/
it will edit your installation!
Usage
Please refer to the Quickstart tutorial for the most typical usage of wakeflow
including generating models and reading the results. Additional examples of more advanced usage can be found in the Documentation.
Contributing
Contributions to wakeflow
are welcome. If you would like to implement a new feature, please:
- Install using the above installation from source instructions
- Create your Feature Branch (
git checkout -b feature/NewFeature
) - Commit your Changes (
git commit -m 'Added some NewFeature'
) - Push to the Branch (
git push origin feature/NewFeature
) - Open a Pull Request
If you have a suggestion that would improve wakeflow
but do not have the time or means to implement it yourself, please simply open an issue with the tag "enhancement". If you would like to report a bug, please open an issue with the tag "bug".
Don't forget to give the project a star!
License
Distributed under the MIT License. See LICENSE.txt
for more information.
Citing
Please cite Hilder et al. (in prep) in any work where wakeflow
has been used. Please contact us if wakeflow
is useful to you, we welcome any collaboration opportunities.
Contact
If you are having difficulties installing or using wakeflow
, please let us know! We are happy to answer any questions or provide assistance.
Thomas Hilder - thil0004@student.monash.edu
Project Link: https://github.com/TomHilder/wakeflow
Acknowledgments
wakeflow
is based on the semi-analytic theory of planets wakes described in Rafikov (2002) and Bollati et al. (2021). The code is partially adapted from analytical kinks
which was written by Francesco Bollati, Daniele Fasano and Thomas Hilder, and can be found here.
Additional acknowledgements:
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.