EXESS Optimization

EXESS geometry optimization for the Rush Python client.

Quick Links

• rush.exess.optimization()

• rush.exess.OptimizationResult

Submission

rush.exess.optimization(mol, max_iters, optimization_keywords=OptimizationKeywords(), method='RestrictedKSDFT', basis='cc-pVDZ', aux_basis=None, standard_orientation=None, force_cartesian_basis_sets=None, scf_keywords=None, ksdft_keywords=_KSDFTDefault.DEFAULT, qm_fragments=None, mm_fragments=None, system=None, run_spec=RunSpec(gpus=1), run_opts=RunOpts())

Submit a geometry optimization for the topology at topology_path.

Returns a RushRun handle. Call .fetch() to get the parsed trajectory and optimization steps, or .save() to write them to disk.

Parameters:

• mol (TRC | TRCRef | tuple[Path | str | RushObject | Topology, Path | str | RushObject | Residues] | Path | str | RushObject | Topology)

• max_iters (int)

• optimization_keywords (OptimizationKeywords)

• method (MethodT)

• basis (BasisT)

• aux_basis (AuxBasisT | None)

• standard_orientation (StandardOrientationT | None)

• force_cartesian_basis_sets (bool | None)

• scf_keywords (SCFKeywords | None)

• ksdft_keywords (KSDFTKeywords | _KSDFTDefault | None)

• qm_fragments (list[int] | None)

• mm_fragments (list[int] | None)

• system (System | None)

• run_spec (RunSpec)

• run_opts (RunOpts)

Return type:

RushRun[OptimizationResultRef]

Input Types

class rush.exess.OptimizationKeywords(convergence_criteria: OptimizationConvergenceCriteria | None = None, optimizer_reset_interval: int | None = None, coordinate_system: CoordinateSystemT | None = None, constraints: list[list[int]] | None = None, hessian_guess: HessianGuessTypeT | None = None, algorithm: OptimizationAlgorithmTypeT | None = None, lbfgs_keywords: LBFGSKeywords | None = None, frozen_distance_slippage_tolerance_angstroms: float | None = None, frozen_angle_slippage_tolerance_degrees: float | None = None, trust_region_keywords: TrustRegionKeywords | None = None, fixed_atoms: list[int] | None = None, free_atoms: list[int] | None = None, fixed_fragments: list[int] | None = None, free_fragments: list[int] | None = None, fix_heavy: bool | None = None)

Parameters:

• convergence_criteria (OptimizationConvergenceCriteria | None)

• optimizer_reset_interval (int | None)

• coordinate_system (CoordinateSystemT | None)

• constraints (list[list[int]] | None)

• hessian_guess (HessianGuessTypeT | None)

• algorithm (OptimizationAlgorithmTypeT | None)

• lbfgs_keywords (LBFGSKeywords | None)

• frozen_distance_slippage_tolerance_angstroms (float | None)

• frozen_angle_slippage_tolerance_degrees (float | None)

• trust_region_keywords (TrustRegionKeywords | None)

• fixed_atoms (list[int] | None)

• free_atoms (list[int] | None)

• fixed_fragments (list[int] | None)

• free_fragments (list[int] | None)

• fix_heavy (bool | None)

algorithm: OptimizationAlgorithmTypeT | None = None

constraints: list[list[int]] | None = None

convergence_criteria: OptimizationConvergenceCriteria | None = None

coordinate_system: CoordinateSystemT | None = None

fix_heavy: bool | None = None

fixed_atoms: list[int] | None = None

fixed_fragments: list[int] | None = None

free_atoms: list[int] | None = None

free_fragments: list[int] | None = None

frozen_angle_slippage_tolerance_degrees: float | None = None

frozen_distance_slippage_tolerance_angstroms: float | None = None

hessian_guess: HessianGuessTypeT | None = None

lbfgs_keywords: LBFGSKeywords | None = None

optimizer_reset_interval: int | None = None

trust_region_keywords: TrustRegionKeywords | None = None

class rush.exess.OptimizationConvergenceCriteria(metric: str | None = None, gradient_threshold: float | None = None, delta_energy_threshold: float | None = None, step_component_threshold: float | None = None)

Parameters:

• metric (str | None)

• gradient_threshold (float | None)

• delta_energy_threshold (float | None)

• step_component_threshold (float | None)

delta_energy_threshold: float | None = None

gradient_threshold: float | None = None

metric: str | None = None

step_component_threshold: float | None = None

class rush.exess.TrustRegionKeywords(initial_radius: float | None = None, max_radius: float | None = None, min_radius: float | None = None, increase_factor: float | None = None, decrease_factor: float | None = None, constrict_factor: float | None = None, increase_threshold: float | None = None, decrease_threshold: float | None = None, rejection_threshold: float | None = None)

Parameters:

• initial_radius (float | None)

• max_radius (float | None)

• min_radius (float | None)

• increase_factor (float | None)

• decrease_factor (float | None)

• constrict_factor (float | None)

• increase_threshold (float | None)

• decrease_threshold (float | None)

• rejection_threshold (float | None)

constrict_factor: float | None = None

decrease_factor: float | None = None

decrease_threshold: float | None = None

increase_factor: float | None = None

increase_threshold: float | None = None

initial_radius: float | None = None

max_radius: float | None = None

min_radius: float | None = None

rejection_threshold: float | None = None

class rush.exess.LBFGSKeywords(linesearch: LBFGSLinesearchT = 'BacktrackingStrongWolfe', n_corrections: int | None = None, epsilon: float | None = None, max_linesearch: int | None = None, gtol: float | None = None)

Parameters:

• linesearch (LBFGSLinesearchT)

• n_corrections (int | None)

• epsilon (float | None)

• max_linesearch (int | None)

• gtol (float | None)

epsilon: float | None = None

gtol: float | None = None

linesearch: LBFGSLinesearchT = 'BacktrackingStrongWolfe'

max_linesearch: int | None = None

n_corrections: int | None = None

Result Types

class rush.exess.OptimizationResult(trajectory: list[Topology], steps: list[OptimizationStep])

Parameters:

• trajectory (list[Topology])

• steps (list[OptimizationStep])

steps: list[OptimizationStep]

trajectory: list[Topology]

class rush.exess.OptimizationResultPaths(trajectory: pathlib.Path, steps: pathlib.Path)

Parameters:

• trajectory (Path)

• steps (Path)

steps: Path

trajectory: Path

class rush.exess.OptimizationResultRef(trajectory, steps)

Lightweight reference to optimization outputs in the Rush object store.

Parameters:

• trajectory (RushObject)

• steps (RushObject)

classmethod from_raw_output(res)

Parse raw collect_run output into an OptimizationResultRef.

Parameters:

res (Any)

Return type:

OptimizationResultRef

fetch()

Download optimization outputs and parse into Python objects.

Return type:

OptimizationResult

save()

Download optimization outputs and save to the workspace.

Return type:

OptimizationResultPaths

steps: RushObject

trajectory: RushObject

class rush.exess.OptimizationStep(total_energy: float, max_gradient_component: float)

Parameters:

• total_energy (float)

• max_gradient_component (float)

max_gradient_component: float

total_energy: float