A brief tutorial on hierarchical Bayesian analysis of gravitational wave source populations, made for the ICERM workshop "Scientific Machine Learning for Gravitational Wave Astronomy." The tutorial is contained within this notebook: intro_HBA_tutorial.ipynb, and all the data you need is in inputs/.

To run this tutorial on your local machine, clone this repository and set up the conda environment with

git clone https://github.com/afarah18/HBA-for-GWs-tutorial.git
cd HBA-for-GWs-tutorial
conda env create -f environment.yml

Then, open the notebook and select the icerm_population_tutorial conda environenment as your kernel.

Note: you have everything in requirements.txt installed in a different environment, you can skip the conda environment creation and just use your own environment.

Alternatively, you can run on google colab and potentially make use of GPU or TPU speedups. Open the notebook in google colab here:

Then, connect to a runtime (try to get a GPU or TPU!) and uncomment the lines in the first cell.

Once you're done, you can check your work by looking at intro_HBA_tutorial_filled_in.ipynb