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Error propagation and statistical analysis for Markov chain Monte Carlo simulations in lattice QCD and statistical mechanics using autograd
autocorrelationautogradautomatic-differentiationcondensed-mattercorrelationdata-analysiserror-propagationlattice-field-theorylattice-qcdmarkov-chainmonte-carloparticle-physicsphysicspythonqcdstatistical-analysisstatistical-mechanics
* fix: Fixed range detection in gamma_method * Corrected test in dobsio * Changed expansion paradigm in gamma_method * Extended tests * Updated docstrings * Removed unnecessary intermediate variable * Removed unnecessary code * Fixed previously introduced bug in output in obs.details() * Fixed previously introduced bug in window determination * New criterion for matching gapped replica, fixed determination of w_max and fixed tau_exp analysis with gaps * tests: split up consistency test for gamma method. --------- Co-authored-by: Fabian Joswig <fabian.joswig@ed.ac.uk> |
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examples | ||
pyerrors | ||
tests | ||
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CHANGELOG.md | ||
CITATION.cff | ||
conftest.py | ||
CONTRIBUTING.md | ||
LICENSE | ||
pyproject.toml | ||
README.md | ||
setup.py |
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
- Bug reports: https://github.com/fjosw/pyerrors/issues
Installation
Install the most recent release using pip and pypi:
pip install pyerrors # Fresh install
pip install -U pyerrors # Update
Install the most recent release using conda and conda-forge:
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.