APOLLO (bAyesian Pipeline for sOLar Like Oscillators) is a fully integrated, automated pipeline that can detect solar
like oscillations in a given star using model Bayesian model comparison. For a full description of the pipeline,
check the paper Muellner et al. (2020). For the documentation check either here or run it locally
usingmkdocs serve.
APOLLO is tested and used under Linux as well as under MacOS, which are the operating systems supported by APOLLO. It is also assumed that Python3.6, pip, git, cmake and the gcc chain are installed on your system. If they are not installed, please do so using your favourite packet manager, for example brew on MacOS or apt on Debian systems.
Note: On MacOS you will need to install the OMP library, if you haven't done so yet
brew install libomp
In the first step, clone the repository do your computer using
git clone https://github.com/MarcoMuellner/APOLLO
cd APOLLO
The project also makes use of submodules. These need to be initialized and updated
git submodule init
git submodule update
It is recommended to use a virtual environment for all python projects. Create and activate one using
python3.6 -m venv venv/
source venv/bin/activate
In the next step, simply install everything using
python setup.py install
This will install all necessary python packages, build DIAMONDS and Background and sets the apollo file
as executable.
And you are done.
APOLLO includes a couple of little demo files, to give you a feel on how the pipeline runs. To run the minimal example simply call
./apollo demo/1_mini_example.json
The results files are than available under demo_results/1_mini_example/ and consists of the light curve, the
power spectral density, a config file and a result file.
Further examples are shown in the documentation.
If you have any problems installing or using our code, don't hesitate to open an issue here on the github. We will try to help you as soon as possible.
If you use our pipeline for scientific purposes, please cite Muellner et al. (2020).