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Error propagation and statistical analysis for Markov chain Monte Carlo simulations in lattice QCD and statistical mechanics using autograd

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

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Fabian Joswig e72949b69b [chore] Stricter ruff rules (#282 ) * [chore] Stricter ruff rules * [chore] Furture lint rules and removal of flake8 * [ci] Bump github action versions * [chore] Add additional test coverage * Revert RNG switch to np.random.default_rng() Restore use of the global np.random state in pseudo_Obs (misc.py) and the prior id generation (fits.py), keeping seed behavior unchanged. The switch to a module-local generator is out of scope for this lint-focused PR. * Silence NPY002 on intentional legacy np.random calls The RNG migration was reverted to keep np.random.seed() behavior, so add per-line noqa: NPY002 on the three legacy np.random calls instead of the Generator API. * [Fix] Fix exception messages		2026-07-06 11:04:28 +02:00
.github	[chore] Stricter ruff rules (#282 )	2026-07-06 11:04:28 +02:00
examples	Fixed index in GEVP example (#261 )	2025-04-22 10:26:20 +02:00
pyerrors	[chore] Stricter ruff rules (#282 )	2026-07-06 11:04:28 +02:00
tests	[chore] Stricter ruff rules (#282 )	2026-07-06 11:04:28 +02:00
.gitignore	build: .hypothesis added to gitignore.	2023-03-17 17:56:40 +00:00
CHANGELOG.md	[release] Bump version to 2.17, append CHANGELOG	2026-03-29 20:48:23 +02:00
CITATION.cff	docs: citation file corrected.	2023-04-29 10:59:45 +01:00
conftest.py	tests: conftest.py added	2022-01-20 13:56:56 +00:00
CONTRIBUTING.md	[chore] Stricter ruff rules (#282 )	2026-07-06 11:04:28 +02:00
LICENSE	Initial public release	2020-10-13 16:53:00 +02:00
pyproject.toml	[chore] Stricter ruff rules (#282 )	2026-07-06 11:04:28 +02:00
README.md	[chore] Remove support for python 3.9 and bump python versions in runners (#273 )	2025-10-19 12:59:20 +02:00
setup.py	[chore] Stricter ruff rules (#282 )	2026-07-06 11:04:28 +02:00

README.md

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:

python -m pip install pyerrors     # Fresh install
python -m pip install -U 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.

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.