Add DynamicOpenMMFlowMaker for dynamic OpenMM Simulations
#1115
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added 7 commits
January 30, 2025 15:16
…of TYPE_CHECKING to use as callable in default_factory
…id shared mutable defaults
…d placeholder should_continue function
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Summary
DynamicOpenMMFlowMakerinsrc/atomate2/openmm/flows/core.pydefault_should_continuefunctions insrc/atomate2/openmm/flows/core.pytest_dynamic_flow_makerintests/openmm_md/flows/test_core.pyThis PR resolves the final enhancement proposed in #1102. Currently, subclasses to
BaseOpenMMMakerincludeEnergyMinimizationMaker,NPTMaker,NVTMaker, andTempChangeMaker. This PR adds theDynamicOpenMMFlowMakerclass, suitable for high-throughput classical MD workflows. Equilibration timescales are highly system- and model-dependent for condensed-phase systems even with notable structural or compositional similarities (see ionic liquids, polymers, etc.). Now there is support for on-the-fly OpenMM trajectory propagation. Below is a simple water equilibration:Based on
default_should_continue, equilibration is deemed complete once the potential energy vs time's rate of change plateaus. A newNPTMakeris instantiated dynamically, creating equilibration stages. The water test case below, the simulation converges once the decay rate falls below thethreshold=1e-3:DynamicOpenMMFlowMaker Job Logs Output
TODO (if any)
pre-commit run --allwith only the following issue unresolved:Ideally,
should_continueshould be aDynamicOpenMMFlowMakerCallable attribute that can take user-defined keyword arguments, like in the test case above. Currently, I'm not sure of the best fix without resorting to purely positional arguments. Sinceshould_continueis meant to be flexible and allow for bespoke modifications, replacing the current signature on line 370 withCallable[..., Response]may work?Edit: Having looked into this some more, I think mypy_extensions would work fine so long as it is an allowable new dependency.
Future Work
The scope of this PR is a straightforward, extensible DynamicOpenMMFlowMaker. For more complex workflows, future enhancements would include:
traj_intervalatcollect_jobPhaseclasses to easily stitch together intentionally separate, dynamic flows (i.e.,EquilibrationPhase,ProductionPhase, etc.)default_should_continuewith broader physical parameter support (e.g., integrate with pymbar, RED, etc.)Checklist
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