Ctrl+K

poli.objective_repository.foldx_stability_and_sasa.register.FoldXStabilityAndSASABlackBox

poli.objective_repository.foldx_stability_and_sasa.register.FoldXStabilityAndSASABlackBox#

class poli.objective_repository.foldx_stability_and_sasa.register.FoldXStabilityAndSASABlackBox(wildtype_pdb_path: Union[Path, List[Path]], experiment_id: Optional[str] = None, tmp_folder: Optional[Path] = None, eager_repair: bool = False, verbose: bool = False, batch_size: int = 1, parallelize: bool = False, num_workers: Optional[int] = None, evaluation_budget: int = inf, force_isolation: bool = False)#

A black box implementation for computing the solvent accessible surface area (SASA) score using FoldX.

Parameters

  • wildtype_pdb_path (Union[Path, List[Path]]) – The path(s) to the wildtype PDB file(s).

  • experiment_id (str, optional) – The ID of the experiment. Default is None.

  • tmp_folder (Path, optional) – The path to the temporary folder. Default is None.

  • eager_repair (bool, optional) – Whether to perform eager repair. Default is False.

  • verbose (bool, optional) – Whether to print the output from FoldX. Default is False.

  • batch_size (int, optional) – The batch size for parallel processing. Default is None.

  • parallelize (bool, optional) – Whether to parallelize the computation. Default is False.

  • num_workers (int, optional) – The number of workers for parallel processing. Default is None.

  • evaluation_budget (int, optional) – The maximum number of function evaluations. Default is infinity.

Notes

We expect the user to have FoldX v5.0 installed and compiled. More specifically, we expect a binary file called foldx to be in the path ~/foldx/foldx.

__init__(wildtype_pdb_path: Union[Path, List[Path]], experiment_id: Optional[str] = None, tmp_folder: Optional[Path] = None, eager_repair: bool = False, verbose: bool = False, batch_size: int = 1, parallelize: bool = False, num_workers: Optional[int] = None, evaluation_budget: int = inf, force_isolation: bool = False)#

Initialize the AbstractBlackBox object.

Parameters

  • batch_size (int, optional) – The batch size for parallel execution, by default None.

  • parallelize (bool, optional) – Flag indicating whether to parallelize the execution, by default False.

  • num_workers (int, optional) – The number of workers for parallel execution, by default we use half the available CPUs.

  • evaluation_budget (int, optional) – The maximum number of evaluations allowed for the black box function, by default float(“inf”).

Methods

__init__(wildtype_pdb_path[, experiment_id, ...])

Initialize the AbstractBlackBox object.

reset_evaluation_budget()

Resets the evaluation budget by setting the number of evaluations made to 0.

set_observer(observer)

Set the observer object for recording observations during evaluation.

terminate()

Terminate the black box optimization problem.