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A PyCBC-based library used by myself to work on binary neutron star or binary black hole gravitational wave data in the context of machine learning.

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MarlinSchaefer/BnsLib

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BnsLib

This repository contains code to aid the application of deep learning algorithms to gravitational-wave data analysis. It is based on PyCBC and Tensorflow and contains useful functions to generate training data, train neural networks, and evaluate their peormance. The main focus lies on signal detection.

The functions and classes defined in this library focus on providing an easy to use high-performance interface. Much of this code has been used at the base of a lot of the work I've done on deep learning gravitational-wave search algorithms.

Installation

Clone this git repository by running

git clone <link>

Afterwards change into the downloaded directory and and install the package via

pip install -e .

Usage

There currently exists no real documentation for the functionality contained in the package. I will try to add some over the coming weeks to months.

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A PyCBC-based library used by myself to work on binary neutron star or binary black hole gravitational wave data in the context of machine learning.

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