https://github.com/aneeshnaik/missingrvsdr3
Science Score: 13.0%
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○CITATION.cff file
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○.zenodo.json file
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○Scientific vocabulary similarity
Low similarity (8.9%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: aneeshnaik
- License: mit
- Language: Python
- Default Branch: main
- Size: 64 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
MissingRVsDR3
Summary
This repository contains the code and the trained model used to generate the results in the article Naik & Widmark (2023; arXiv link to be added soon): "The missing radial velocities of Gaia: a catalogue of Bayesian estimates for DR3."
The code includes the data queries used to obtain the raw Gaia data, the scripts used to train the Bayesian neural network, the scripts to generate the catalogue, and the scripts used to generate the plots in the paper.
The Bayesian neural network source code is available as the package banyan.
Citation
Our code is freely available for use under the MIT License. For details, see LICENSE.
If using our code, please cite our paper: arXiv link to be added soon.
Structure
This code is structured as follows:
- /src contains all of the 'source code', including utility functions (utils.py), coordinate conversions (coords.py), global constants (constants.py), run parameters (params.py), and various functions relating to the Gaussian mixture models (gmm.py).
- /EDR3_match contains a script used to match stars contained in our previous EDR3-derived catalogue to stars with measured radial velocities in DR3.
- /data contains a directory of data queries, as well as various scripts used to parse and manage the downloaded data.
- /models contains the script used to train the BNN model, as well as the ensemble of trained BNNs itself (*.pth).
- /predictions contains the scripts used to generate predictions from the trained BNN model, as well as scripts to fit the prediction distributions with Gaussian mixture models.
- /figures contains the plotting scripts used for the paper.
Owner
- Name: Aneesh Naik
- Login: aneeshnaik
- Kind: user
- Website: https://aneeshnaik.github.io/
- Repositories: 3
- Profile: https://github.com/aneeshnaik
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