This was a notebook for a tutorial that I gave on fitting populations to catalogs with selection effects for our GW group meeting on 2025-05-14. The tutorial worked up to the result in the Callister, et al. (2021) "Who Ordered That?" paper that found a correlation between the mass ratio and the mean effective spin ("chi effective") in the LIGO catalog. The tutorial is in the notebook notebooks/SelectionTutorial.ipynb and is written in Julia. You should be able to run the notebook in colab, though you will have to download a bunch of data from Zenodo, and I haven't tried it myself.

The canonical way to install Julia is via juliaup. Once you have it installed, and have cloned this repo, fire up a julia interpreter (via the command line, in VSCode, or whatever), and install the dependencies for this project via:

> using Pkg # Activate the package model that manages dependencies
> Pkg.activate("path/to/this/repo") # Activate the package for this repo
> Pkg.instantiate() # Install the dependencies for this repo (you only have to run this the first time)

Now the dependencies are installed, and you can run the notebook. If you are using VSCode, you can just open the notebook, and it will automatically use a Julia kernel; if running from the command line, you will have to install IJulia run the notebook manually:

> Pkg.add("IJulia") # Install the IJulia package
> using IJulia # Load the IJulia package
> IJulia.jupyterlab() # Start the JupyterLab server