Workflow is a Python toolkit for building interatomic potential creation and atomistic simulation workflows.
The main functions of Workflow is to efficiently parallelise operations over a set of atomic configurations (Atomic Simulation Environment's "Atoms" objects). Given an operation that is defined to act on a single configuration (e.g. evaluate energy of a structure with CASTEP ASE calculator), Workflow may apply the operation to multiple configurations in parallel. Workflow also interfaces with ExPyRe to manage evaluation of (autoparallelized) Python functions via a queueing system on a (remote) cluster.
For examples and more information see documentation
wfl and its dependendensies may be installed via pip install wfl.
NOTE: (as of 14 June 2024) wfl is only tested against the latest ASE pip release, currently v3.23.0.
For the time being, v3.22.1 is the mininum version listed as a (pip) prerequisite of wfl, because
it at least mostly works, but it may not be fully compatible and is not actively tested.
v0.2.3:
-
Add wfl.generate.neb, with required improved support for passing ConfigSet.groups() to autoaparallelized functions
-
Improved handling of old and new style ase.calculators.espresso.Espresso initialization
v0.2.2:
- Improve checking of DFT calculator convergence
v0.2.1:
- Fix group iterator
v0.2.0:
- Change all wfl operations to use explicit random number generator pull 285, to improve reproducibility of scripts and reduce the chances that on script rerun, cached jobs will not be recognized due to uncontrolled change in random seed (as in issue 283 and issue 284). Note that this change breaks backward compatibility because many functions now require an
rngargument, for examplerng = np.random.default_rng(1) md_configs = md.md(..., rng=rng, ...)
v0.1.0:
- make it possible to fire off several remote autoparallellized ops without waiting for their jobs to finish
- multi-pass calclation in
Vasp, to allow for things like GGA followed by HSE - MACE fitting, including remote jobs
- various bug fixes