Metadata-Version: 2.1
Name: sgvb_psd
Version: 0.0.2
Summary: A python package for estimating the power spectral density (PSD) of correlated multivariate detector noise using variational inference (VI).
Author-email: Jianan Liu <jliu812@aucklanduni.ac.nz>, Avi Vajpeyi <avi.vajpeyi@gmail.com>
Project-URL: Homepage, https://github.com/nz-gravity/sgvb_psd
Project-URL: Bug Reports, https://github.com/nz-gravity/sgvb_psd
Project-URL: Source, https://github.com/nz-gravity/sgvb_psd
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: tensorflow-probability>=0.24.0
Requires-Dist: tf-keras
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: matplotlib
Requires-Dist: hyperopt
Requires-Dist: colorama
Provides-Extra: dev
Requires-Dist: pytest>=6.0; extra == "dev"
Requires-Dist: pytest-cov>=4.1.0; extra == "dev"
Requires-Dist: pre-commit; extra == "dev"
Requires-Dist: flake8>=5.0.4; extra == "dev"
Requires-Dist: black>=22.12.0; extra == "dev"
Requires-Dist: jupyter-book; extra == "dev"
Requires-Dist: sphinx-inline-tabs; extra == "dev"

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# SGVB PSD Estimator

This repository contains the code for the paper 
"Fast PSD estimation for correlated multivariate detector noise using VI" by Jianan Liu at al. 2024

Documentation is available at https://nz-gravity.github.io/sgvb_psd/




## Development

Install in editable mode with dev dependencies
```
pip install -e ".[dev]"
pre-commit install
```

Ensure unit tests are passing locally and on the CI!
```
pytest tests/
```

*Releasing to PyPI*

1. Manually change the version number in `pyproject.toml`  (has to be higher than previous)
1. Create a tagged commit with the version number
2. Push the tag to GitHub

```
git tag -a v0.1.0 -m "v0.1.0"
git push origin v0.1.0
```
