Getting started
Setting up your environment
To make it as easy as possible to reproduce our results and/or figures, the environment.yaml file can be used to build a conda environment containing all the packages needed to run the code in this repository. To set up this environment, do the following:
Step 0. Make sure you have conda installed. If not, see e.g. https://docs.conda.io/en/latest/miniconda.html
Step 1. Do the following:
$ conda env create -f environment.yaml
This will create a new conda environment named gwtc3-spin-studies
Step 2. To activate the new environment, do
$ conda activate gwtc3-spin-studies
You can deactivate the environment using conda deactivate
Downloading input files and inference results
Datafiles containing the output of our inference codes are hosted on Zenodo at https://doi.org/10.5281/zenodo.6505272, along with the input files loaded in by our inference code. If you want to regenerate figures or rerun any of our analyses, you’ll need to download this input/output data locally. You can do this via
$ cd data/
$ . download_data_from_zenodo.sh
This script will populate the data/ directory with datafiles containing the output of our analyses.
These output files can be inspected by running the jupyter notebooks also appearing in the data/ directory; see Effective spin models and Component spin models for some additional information.
The script will also place several files in the code/input/ directory, which are needed to rerun analyses and/or regenerate figures.
Some of our figures also contain data produced by Galaudage+ (2021) 1 and hosted at https://github.com/shanikagalaudage/bbh_spin.
If you want to regenerate figures, you’ll want to clone this repository locally (making sure to check out files stored in git-lfs) and create a link to this repository in the code/input/ folder:
$ cd [.../desired/filepath/...]
$ git clone git@github.com:shanikagalaudage/bbh_spin.git
$ cd [.../path/to/gwtc3-spin-studies]/code/input
$ ln -s [.../path/to/bbh_spin] galaudage-data