Data to Reproduce "Robust Automated Equilibration Detection for Molecular Simulations"
Description
Data to reproduce the results from "Robust Automated Equilibration Detection for Molecular Simluations" (see https://github.com/michellab/Robust-Equilibration-Detection-Paper and the work linked there). These data are too large to host on GitHub, but are automatically downloaded by the workflow supplied at the above GitHub repository.
All data were generated using the code given in the GitHub repository, other than the original free energy gradient data gradient_arrays_30ns.pkl
which were generated as described in https://doi.org/10.1021/acs.jctc.4c00806 (to regenerate, see the code available at: https://github.com/michellab/Automated-ABFE-Paper).
The synthetic data used to test all equilibration detection heuristics are given in the compute_equil_times
output directories (for example synthetic_data_bound_vanish_with_equil_times.pkl
. These are supplied as pickled Python dictionaries with the structures data[dataset_type][system][trace_index]["data"]
. For example, to access the first synthetic trace for the T4L system from the "standard" synthetic ensemble, use data["standard"]["T4L"][0]["data"]
. For all directories, _free
denotes the free vanish multi-window data and _single
denotes the bound vanish single-window data - otherwise these are the standard bound vanish multi-window data. However, it is recommended that these data are used as part of the workflow given at https://github.com/michellab/Robust-Equilibration-Detection-Paper, which allows the study to be reproduced from scratch.
Files
Files
(2.2 GB)
Name | Size | Download all |
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md5:b19bbf2ee9f0a3f97845344e7c3ebbbf
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2.2 GB | Download |
Additional details
Software
- Repository URL
- https://github.com/michellab/Robust-Equilibration-Detection-Paper
- Programming language
- Python