Error propagation and statistical analysis for Markov chain Monte Carlo simulations in lattice QCD and statistical mechanics using autograd
Find a file
2025-01-09 09:25:57 +00:00
.github [CI] Add E252 to flake8 exceptions 2025-01-03 19:06:26 +01:00
examples Feature/corr matrix and inverse cov matrix as input in least squares function for correlated fits (#223) 2024-09-13 08:35:10 +02:00
pyerrors add typehints for other util functions 2025-01-09 09:25:57 +00:00
tests Fix/sfcf ensname (#253) 2025-01-06 10:46:49 +01:00
.gitignore build: .hypothesis added to gitignore. 2023-03-17 17:56:40 +00:00
CHANGELOG.md [Release] Updated changelog and bumped version 2024-11-03 17:03:06 +01:00
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 docs: Contributing guidelines clarified. 2023-07-10 16:11:25 +01:00
LICENSE Initial public release 2020-10-13 16:53:00 +02:00
pyproject.toml [Fix] Fix type hints in misc.py and remove strict zips for python 3.9 2025-01-03 18:39:34 +01:00
README.md [docs] Simplify README 2024-12-18 13:00:06 +01:00
setup.py [ci] Add python 3.13 to pytest workflow. (#242) 2024-10-14 23:27:24 +02:00

License: MIT arXiv DOI

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.

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.