alchemlyb makes alchemical free energy calculations easier to do by leveraging the full power and flexibility of the PyData stack. It includes:
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Parsers for extracting raw data from output files of common molecular dynamics engines such as GROMACS, AMBER, NAMD and other simulation codes.
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Subsamplers for obtaining uncorrelated samples from timeseries data (including extracting independent, equilibrated samples Chodera2016 as implemented in the pymbar package).
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Estimators for obtaining free energies directly from this data, using best-practices approaches for multistate Bennett acceptance ratio (MBAR) Shirts2008 and BAR (from pymbar) and thermodynamic integration (TI).
The documentation is hosted on Read the Docs.
Install via pip
from PyPi (alchemlyb):
pip install alchemlyb
or as a conda
package from the conda-forge (alchemlyb) channel:
conda install -c conda-forge alchemlyb
Update with pip
:
pip install --update alchemlyb
or with conda
run:
conda update -c conda-forge alchemlyb
to get the latest released version.
Contributions of all kinds are very welcome.
If you have questions or want to discuss alchemlyb please post in the alchemlyb Discussions.
If you have bug reports or feature requests then please get in touch with us through the Issue Tracker.
We also welcome code contributions: have a look at our Developer Guide. Open an issue with the proposed fix or change in the Issue Tracker and submit a pull request against the alchemistry/alchemlyb GitHub repository.
- Shirts, M.R., and Chodera, J.D. (2008). Statistically optimal analysis of samples from multiple equilibrium states. The Journal of Chemical Physics 129, 124105.
- Chodera, J.D. (2016). A Simple Method for Automated Equilibration Detection in Molecular Simulations. Journal of Chemical Theory and Computation 12, 1799–1805.