vitamin-b 0.2.3

A user-friendly machine learning Bayesian inference library

VItamin_B: A Machine Learning Library for Fast Gravitational Wave Posterior Generation

Welcome to VItamin_B, a python toolkit for producing fast gravitational wave posterior samples.

This repository is the official implementation of Bayesian Parameter Estimation using Conditional Variational Autoencoders for Gravitational Wave Astronomy.

Hunter Gabbard, Chris Messenger, Ik Siong Heng, Francesco Tonlini, Roderick Murray-Smith

Official Documentation can be found at https://hagabbar.github.io/vitamin_b.

Check out our Blog (to be made), Paper and Interactive Demo.

Note: This repository is a work in progress. No official release of code just yet.

Requirements

VItamin requires python3.6. You may use python3.6 by initializing a virtual environment.

virtualenv -p python3.6 myenv
source myenv/bin/activate
pip install --upgrade pip

Make sure to install basemap prior to installing all other packages.

For installing basemap:

• Install geos-3.3.3 from source
• Once geos is installed, install basemap using pip install git+https://github.com/matplotlib/basemap.git

For other required packages:

pip install -r requirements.txt

Install VItamin using pip:

pip install vitamin-b