semvec/pypi-packages huggingface dataset:
xtce2py 0.1.0
A generator for creating a Python package from an XTCE file.
Requires Python: >=3.11

# xtce2py
Generates a Python package from a source XTCE file.

**Alpha Software:** This package is currently in the alpha stage of development. The API is not stable and is subject to breaking changes in future releases. Please use with caution and report any bugs or issues you find.
dynesty 3.0.0
A dynamic nested sampling package for computing Bayesian posteriors and evidences.
Requires Python: >=3.8
Keywords: nested sampling, dynamic, monte carlo, bayesian, inference, modeling

[![Build Status](https://github.com/joshspeagle/dynesty/actions/workflows/test.yml/badge.svg)](https://github.com/joshspeagle/dynesty/actions/)
[![Documentation Status](https://readthedocs.org/projects/dynesty/badge/?version=latest)](https://dynesty.readthedocs.io/en/latest/?badge=latest)
[![Coverage Status](https://coveralls.io/repos/github/joshspeagle/dynesty/badge.svg?branch=master)](https://coveralls.io/github/joshspeagle/dynesty?branch=master)[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3348367.svg)](https://doi.org/10.5281/zenodo.3348367)


dynesty
=======

![dynesty in action](https://github.com/joshspeagle/dynesty/blob/master/docs/images/title.gif)

A Dynamic Nested Sampling package for computing Bayesian posteriors and
evidences. Pure Python. MIT license.

### Documentation
Documentation can be found [here](https://dynesty.readthedocs.io).

### Installation
The most stable release of `dynesty` can be installed
through [pip](https://pip.pypa.io/en/stable) via
```
pip install dynesty
```
The current (less stable) development version can be installed by running
```
pip install .
```
from inside the repository.

### Demos
Several Jupyter notebooks that demonstrate most of the available features
of the code can be found 
[here](https://github.com/joshspeagle/dynesty/tree/master/demos).

### Attribution

If you use this package in your research, please cite **both** of these references:
* The original paper [Speagle (2020)](https://ui.adsabs.harvard.edu/abs/2020MNRAS.493.3132S/abstract)
* The Python implementation [Koposov et al. (2024)](https://doi.org/10.5281/zenodo.3348367) (the citation information is at the bottom right of the linked page)

Please also consider citing papers describing the underlying methods (see the [documentation](https://dynesty.readthedocs.io/en/latest/references.html) for more details)

### Reporting issues

If you want to report issues, or have questions, please do that on [github](https://github.com/joshspeagle/dynesty/issues).

### Contributing

Patches and contributions are very welcome! Please see [CONTRIBUTING.md](https://github.com/joshspeagle/dynesty/blob/master/CONTRIBUTING.md) for more details.