Metadata-Version: 2.4
Name: stacie
Version: 1.2.2
Summary: STACIE is the STable AutoCorrelation Integral Estimator for time-correlated data.
Author-email: Gözdenur Toraman <gozdenur.toraman@ugent.be>, Toon Verstraelen <toon.verstraelen@ugent.be>
License: LGPL-3.0-or-later OR CC-BY-SA-4.0 (for documentation)
Project-URL: Documentation, https://molmod.github.io/stacie/
Project-URL: Issues, https://github.com/molmod/stacie/issues/
Project-URL: Source, https://github.com/molmod/stacie/
Keywords: ACF,autocorrelation function,autocorrelation integral,characteristic timescales,data analysis,exponential correlation time,integrated correlation time,molecular dynamics,open source,post-processing,power spectral distribution,PSD,Python package,scientific computing,STACIE,time correlation,transport properties,uncertainty quantification
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 or later (LGPLv3+)
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
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Dynamic: license-file

# STACIE

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[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.15744667.svg)](https://doi.org/10.5281/zenodo.15744667)

<p align="center">
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<!-- snipwise.md BEGIN abstract -->
STACIE is a Python package and algorithm that computes time integrals of autocorrelation functions.
It is primarily designed for post-processing molecular dynamics simulations.
However, it can also be used for more general analysis of time-correlated data.
Typical applications include estimating transport properties
and the uncertainty of averages over time-correlated data,
as well as analyzing characteristic timescales.
<!-- snipwise.md END abstract -->

All information about STACIE can be found in the [documentation](https://molmod.github.io/stacie).

## Citation

If you use STACIE in your research, please cite the following paper:

> <!-- snipwise.md BEGIN stacie-ref-markdown -->
> Gözdenur Toraman, Dieter Fauconnier, and Toon Verstraelen
> "STable AutoCorrelation Integral Estimator:
> Robust and Accurate Transport Properties from Molecular Dynamics Simulations"
> *Journal of Chemical Information and Modeling* **2025**, 65 (19), 10445–10464,
> <https://doi.org/10.1021/acs.jcim.5c01475>,
> <https://arxiv.org/abs/2506.20438>.
> <!-- snipwise.md END stacie-ref-markdown -->
>
> <!-- snipwise.md BEGIN stacie-ref-bib -->
>
> ```bibtex
> @article{Toraman2025,
>  author = {G\"{o}zdenur Toraman and Dieter Fauconnier and Toon Verstraelen},
>  title = {STable AutoCorrelation Integral Estimator:
>   Robust and Accurate Transport Properties from Molecular Dynamics Simulations},
>  journal = {Journal of Chemical Information and Modeling},
>  volume = {65},
>  number = {19},
>  pages = {10445--10464},
>  year = {2025},
>  month = {sep},
>  url = {https://doi.org/10.1021/acs.jcim.5c01475},
>  doi = {10.1021/acs.jcim.5c01475},
> }
> ```
>
> <!-- snipwise.md END stacie-ref-bib -->

When using the Lorentz model or performing shear viscosity calculations with STACIE,
please also cite the following paper:

> <!-- snipwise.md BEGIN lorentz-ref-markdown -->
> Gözdenur Toraman, Dieter Fauconnier, and Toon Verstraelen
> "Reliable Viscosity Calculation from High-Pressure Equilibrium Molecular Dynamics: Case Study of 2,2,4-Trimethylhexane"
> *Journal of Chemical Theory and Computation* **2026**, 22 (15), 7496–7511,
> <https://doi.org/10.1021/acs.jctc.6c00506>,
> <https://arxiv.org/abs/2603.11247>.
> <!-- snipwise.md END lorentz-ref-markdown -->
>
> <!-- snipwise.md BEGIN lorentz-ref-bib -->
>
> ```bibtex
> @article{Toraman2026,
>  author = {G\"{o}zdenur Toraman and Dieter Fauconnier and Toon Verstraelen},
>  title = {Reliable Viscosity Calculation from High-Pressure Equilibrium Molecular Dynamics:
>   Case Study of 2,2,4-Trimethylhexane},
>  journal = {Journal of Chemical Theory and Computation},
>  volume = {22},
>  number = {15},
>  pages = {7496--7511},
>  year = {2026},
>  month = {jul},
>  url = {https://doi.org/10.1021/acs.jctc.6c00506},
>  doi = {10.1021/acs.jctc.6c00506},
> }
> ```
>
> <!-- snipwise.md END lorentz-ref-bib -->

## License

STACIE is free software: you can redistribute it and/or modify it
under the terms of the GNU Lesser General Public License
as published by the Free Software Foundation,
either version 3 of the License, or (at your option) any later version.

STACIE is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY;
without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
See the GNU Lesser General Public License for more details.

STACIE's documentation is located in the `docs/` directory of its source tree
and files under this directory are distributed under a choice of license:
either the Creative Commons Attribution-ShareAlike 4.0 International license (CC BY-SA 4.0)
or the GNU Lesser General Public License, version 3 or later (LGPL-v3+).
The SPDX License Expression for the documentation is `CC-BY-SA-4.0 OR LGPL-3.0-or-later`.

You should have received a copy of the CC BY-SA 4.0 and LGPL-v3+ licenses along with the source code.
If not, see:

- <https://creativecommons.org/licenses/by-sa/4.0/>
- <https://www.gnu.org/licenses/>

## Installation

Assuming you have Python and Pip installed,
the following shell command will install STACIE in your Python environment.

```bash
python -m pip install stacie
```

If you have a Conda environment, you can also install STACIE from the `conda-forge` channel:

```bash
conda install -c conda-forge stacie
```
