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https://github.com/fjosw/pyerrors

Error propagation and statistical analysis for Markov chain Monte Carlo simulations in lattice QCD and statistical mechanics using autograd
https://github.com/fjosw/pyerrors

autocorrelation autograd automatic-differentiation condensed-matter correlation data-analysis error-propagation lattice-field-theory lattice-qcd markov-chain monte-carlo particle-physics physics python qcd statistical-analysis statistical-mechanics

Last synced: 14 days ago
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Error propagation and statistical analysis for Markov chain Monte Carlo simulations in lattice QCD and statistical mechanics using autograd

Host: GitHub
URL: https://github.com/fjosw/pyerrors
Owner: fjosw
License: mit
Created: 2020-10-13T14:51:45.000Z (about 4 years ago)
Default Branch: develop
Last Pushed: 2024-10-14T21:29:59.000Z (26 days ago)
Last Synced: 2024-10-14T21:44:49.784Z (26 days ago)
Topics: autocorrelation, autograd, automatic-differentiation, condensed-matter, correlation, data-analysis, error-propagation, lattice-field-theory, lattice-qcd, markov-chain, monte-carlo, particle-physics, physics, python, qcd, statistical-analysis, statistical-mechanics
Language: Python
Homepage: https://fjosw.github.io/pyerrors/pyerrors.html
Size: 21.4 MB
Stars: 36
Watchers: 10
Forks: 13
Open Issues: 2
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Citation: CITATION.cff
- Codeowners: .github/CODEOWNERS

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README

        [![pytest](https://github.com/fjosw/pyerrors/actions/workflows/pytest.yml/badge.svg)](https://github.com/fjosw/pyerrors/actions/workflows/pytest.yml) [![](https://img.shields.io/badge/python-3.9+-blue.svg)](https://www.python.org/downloads/) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [![arXiv](https://img.shields.io/badge/arXiv-2209.14371-b31b1b.svg)](https://arxiv.org/abs/2209.14371) [![DOI](https://img.shields.io/badge/DOI-10.1016%2Fj.cpc.2023.108750-blue)](https://doi.org/10.1016/j.cpc.2023.108750)

# pyerrors

`pyerrors` is a python framework for error computation and propagation of Markov chain Monte Carlo data from lattice field theory and statistical mechanics simulations.

- **Documentation:** https://fjosw.github.io/pyerrors/pyerrors.html

- **Examples:** https://github.com/fjosw/pyerrors/tree/develop/examples

- **Ask a question:** https://github.com/fjosw/pyerrors/discussions/new?category=q-a

- **Changelog:** https://github.com/fjosw/pyerrors/blob/develop/CHANGELOG.md

- **Bug reports:** https://github.com/fjosw/pyerrors/issues

## Installation

Install the most recent release using pip and [pypi](https://pypi.org/project/pyerrors/):

```bash

python -m pip install pyerrors     # Fresh install

python -m pip install -U pyerrors  # Update

```

Install the most recent release using conda and [conda-forge](https://anaconda.org/conda-forge/pyerrors):

```bash

conda install -c conda-forge pyerrors  # Fresh install

conda update -c conda-forge pyerrors   # Update

```

## Contributing

We appreciate all contributions to the code, the documentation and the examples. If you want to get involved please have a look at our [contribution guideline](https://github.com/fjosw/pyerrors/blob/develop/CONTRIBUTING.md).

## Citing pyerrors

If you use `pyerrors` for research that leads to a publication we suggest citing the following papers:

- Fabian Joswig, Simon Kuberski, Justus T. Kuhlmann, Jan Neuendorf, *pyerrors: a python framework for error analysis of Monte Carlo data*. Comput.Phys.Commun. 288 (2023) 108750.

- Ulli Wolff, *Monte Carlo errors with less errors*. Comput.Phys.Commun. 156 (2004) 143-153, Comput.Phys.Commun. 176 (2007) 383 (erratum).

- Alberto Ramos, *Automatic differentiation for error analysis of Monte Carlo data*. Comput.Phys.Commun. 238 (2019) 19-35.

- Stefan Schaefer, Rainer Sommer, Francesco Virotta, *Critical slowing down and error analysis in lattice QCD simulations*. Nucl.Phys.B 845 (2011) 93-119.