ml4gw-buoy 0.2.0

Deploy Aframe and AMPLFI models over open data

Installation

This library is pip installable with

pip install ml4gw-buoy

It is recommended that you install buoy in a virtual environment such as conda.

Usage

The function of this library is to run trained Aframe and AMPLFI models over a gravitaional wave event reported by the LIGO-Virgo-KAGRA collaboration during their third observing run, O3.

Note: the trained models will be downloaded from HuggingFace and require about 320 MB of space.

To product model outputs, first identify an event of interest (e.g., from GWTC-3), and then run

buoy --events <EVENT_NAME> --outdir <OUTPUT_DIRECTORY>

The output directory is structured as follows will contain a directory matching the name of the event. Inside, there will be a data directory containing data created during the analysis, and a plots directory containing Aframe's response to the event as well as a skymap and corner plot from AMPLFI.

Multiple events can be specified at once, e.g.:

buoy --events '["GW190828_063405", "GW190521"]' --outdir <OUTPUT_DIRECTORY>

About 10 MB of space is required for each event.