Metadata-Version: 2.4
Name: Taweret
Version: 1.2.0
Summary: A python package for Bayesian model mixing
Author-email: Kevin Ingles <kingles@illinois.edu>, "Dananjaya (Dan) Liyanage" <liyanage@osu.edu>, Alexandra Semposki <as727414@ohio.edu>, John Yannotty <yannotty.1@buckeyemail.osu.edu>
License: MIT License
        
        Copyright (c) 2022 Dananjaya Liyanage, Alexandra Semposki, John Yannotty, Kevin Ingles
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
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        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
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        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.21.1
Requires-Dist: scipy>=1.10.0
Requires-Dist: bilby>=2.5.0
Requires-Dist: openbtmixing
Requires-Dist: matplotlib
Requires-Dist: pytest
Dynamic: license-file



# Taweret
[![codecov](https://codecov.io/gh/bandframework/Taweret/graph/badge.svg?token=BQ7ZAD5ONP)](https://codecov.io/gh/bandframework/Taweret)
[![DOI](https://joss.theoj.org/papers/10.21105/joss.06175/status.svg)](https://doi.org/10.21105/joss.06175)

<img align="right" width="200" src="logos/taweret_logo.PNG">

Welcome to the GitHub repo for Taweret, the state of the art Python package for applying Bayesian Model Mixing! 

## About
Taweret is a new generalized package to help with applying Bayesian model mixing methods, developed by members of the [BAND](https://bandframework.github.io/) collaboration, to a wide variety of problems in physics. 

## Features
At present, this package possesses the following BMM methods:
- Linear model mixing ( With simultaneous model mixing and calibration)
- Multivariate BMM 
- Bayesian Trees

## Documentation
See Taweret's docs webpage [here](https://taweretdocs.readthedocs.io).

## Cloning
This repository uses submodules. 
To clone this repository and automatically checkout all the submodules, use
```terminal
git clone --recursive https://github.com/bandframework/Taweret.git 
```

If you want to limit the size of the repository (this or the submodules), you can use the `depth` flag
```terminal
git clone --depth=1 https://github.com/bandframework/Taweret.git
```
Inside the directory containing the cloned repository, you then run
```terminal
git submodule update --init --depth=1
```

## Running on Codespaces
GitHub's Codespaces is a great place to test using Taweret. Right now, you can try out Taweret's Bivariate Linear BMM and Multivariate BMM methods there, by following the instructions below. 

1. Click the dropdown arrow on the green 'code' button found at the top of this page.
2. Click on the tab there that says 'codespaces'.
3. Click the button for 'create Codespace on main'.
4. Wait for the terminal to be finish spinning up a virtual environment and loading all needed variables (this can take a few minutes).
5. Once that is done, navigate on the file tree to a notebook you wish to run. To run a file, you need to set a kernel for the Jupyter notebook, so click on 'choose a kernel' in the upper right hand corner of the notebook. If you haven't gotten this message already, a message will pop up that says 'install preferred Python extension?', and you should click 'yes'.
6. When you click 'choose a kernel' it will offer a preferred Python version or a base version (usually a newer Python version). Choose whichever you prefer, and then you can run the notebook!

## Citing Taweret
If you have benefited from Taweret, please cite our software using the following format:

```
@inproceedings{Taweret,
    author = "Liyanage, Dan and Semposki, Alexandra and Yannotty, John and Ingles, Kevin",
    title  = "{{Taweret: A Python Package for Bayesian Model Mixing}}",
    year   = "2023",
    url    = {https://github.com/bandframework/Taweret}
}
```

and our explanatory paper:

```
@article{Ingles:2023nha,
    author = "Ingles, Kevin and Liyanage, Dananjaya and Semposki, Alexandra C. and Yannotty, John C.",
    title = "{Taweret: a Python package for Bayesian model mixing}",
    eprint = "2310.20549",
    archivePrefix = "arXiv",
    primaryClass = "nucl-th",
    doi = "10.21105/joss.06175",
    journal = "J. Open Source Softw.",
    volume = "9",
    number = "97",
    pages = "6175",
    year = "2024"
}
```

Please also cite the BAND collaboration software suite using the format [here](https://github.com/bandframework/bandframework#citing-the-band-framework).

## BAND SDK compliance
Check out our SDK form [here](https://github.com/bandframework/Taweret/blob/main/Taweretbandsdk.md).

## Contact
To contact the Taweret team, please submit an issue through the Issues page. 

Authors: Kevin Ingles, Dan Liyanage, Alexandra Semposki, and John Yannotty.


