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.
Release files for pyerrors 2.17.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pyerrors-2.17.0.tar.gz | 106.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pyerrors-2.17.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 220.5 kB
Release files / pyerrors-2.17.0.tar.gz
| Download URL | pyerrors-2.17.0.tar.gz |
|---|---|
| Size | 106.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
079935574bc97151f382353f121175598194973830be55a02ea96cbc7d170493
|
|
BLAKE2b-256 checksum How to use checksums |
9a15b65b7ebffb1a650ea38c6d41970f5d151ddb545e13df8f0d956df51f81ff
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Mar 29, 2026.
Transparency logRelease files / pyerrors-2.17.0-py3-none-any.whl
| Download URL | pyerrors-2.17.0-py3-none-any.whl |
|---|---|
| Size | 114.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
7889b1b9de65ed413bb4b6acfb7aba02a30e1fcf54389423507662b11a55479c
|
|
BLAKE2b-256 checksum How to use checksums |
fe5d46bdddcec2086d3daa62119539b86242cffb930b2f0d029da7c52825c15d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Mar 29, 2026.
Transparency log