This is a forked repo from DicksonLab’s wepy software to run weighted ensemble simulation for QM and QMMM dynamics.
Here you can find specific runners and architecture required for running QM or QM/MM simulations in weighted ensemble formalism.
The installation and documentation is same as main wepy repo:
Modular implementation and framework for running weighted ensemble (WE) simulations in pure python, where the aim is to have simple things simple and complicated things possible. The latter being the priority.
If you have specific queiries regarding the qm or qmmm runners, please contact Samik Bose at bosesami@msu.edu
Comes equipped with support for OpenMM molecular dynamics, parallelization using multiprocessing, the WExplore and REVO (Resampling Ensembles by Variance Optimization) resampling algorithms, and an HDF5 file format and library for storing and querying your WE datasets that can be used from the command line.
The deeper architecture of wepy is intended to be loosely coupled,
so that unforeseen use cases can be accomodated, but tightly
integrated for the most common of use cases, i.e. molecular dynamics.
This allows freedom for fast development of new methods.
Full introduction.
Also see: Installation Instructions
We recommend running this version of `wepy` in a conda environment using `python=3.10` or greater:
conda create -n wepy python=3.10
conda activate wepyThe latest version of `wepy_dev` can be installed from the git repo source:
git clone https://github.com/SamikBose/wepy_dev.git
cd wepy_dev
pip install -e . Please install pyscf and gpuscf via conda (or pip) from here: https://pyscf.org/user/install.html#install-with-conda
Cite wepy software as:
Samuel D. Lotz, Nazanin Donyapour, Alex Dickson, Tom Dixon, Nicole Roussey, & Rob Hall. (2020, August 4). ADicksonLab/wepy: 1.0.0 Major version release (Version v1.0.0). Zenodo. http://doi.org/10.5281/zenodo.3973431
Accompanying journal article:
- ACS Omega article