gemseo.algos.opt.scipy_global.settings.shgo module#

Settings for the SciPy SHGO algorithm.

Settings SHGO_Settings(*, enable_progress_bar=None, eq_tolerance=1e-06, ineq_tolerance=0.0001, log_problem=True, max_time=0.0, normalize_design_space=True, reset_iteration_counters=True, round_ints=True, use_database=True, use_one_line_progress_bar=False, store_jacobian=True, ftol_rel=1e-09, ftol_abs=1e-09, max_iter=9223372036854775807, scaling_threshold=None, stop_crit_n_x=3, xtol_rel=1e-09, xtol_abs=1e-09, n=100, iters=1, options=None, sampling_method='simplicial', workers=1)[source]#

Bases: BaseSciPyGlobalSettings

The SciPy differential evolution setting.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

  • enable_progress_bar (bool | None)

  • eq_tolerance (Annotated[float, Ge(ge=0), Ge(ge=0), Ge(ge=0)]) --

    By default it is set to 1e-06.

  • ineq_tolerance (Annotated[float, Ge(ge=0)]) --

    By default it is set to 0.0001.

  • log_problem (bool) --

    By default it is set to True.

  • max_time (Annotated[float, Ge(ge=0)]) --

    By default it is set to 0.0.

  • normalize_design_space (bool) --

    By default it is set to True.

  • reset_iteration_counters (bool) --

    By default it is set to True.

  • round_ints (bool) --

    By default it is set to True.

  • use_database (bool) --

    By default it is set to True.

  • use_one_line_progress_bar (bool) --

    By default it is set to False.

  • store_jacobian (bool) --

    By default it is set to True.

  • ftol_rel (Annotated[float, Ge(ge=0), Ge(ge=0), Ge(ge=0), Ge(ge=0), Ge(ge=0)]) --

    By default it is set to 1e-09.

  • ftol_abs (Annotated[float, Ge(ge=0), Ge(ge=0), Ge(ge=0), Ge(ge=0), Ge(ge=0)]) --

    By default it is set to 1e-09.

  • max_iter (Annotated[int, Gt(gt=0), Gt(gt=0)]) --

    By default it is set to 9223372036854775807.

  • scaling_threshold (Annotated[float, Ge(ge=0)] | None)

  • stop_crit_n_x (Annotated[int, Ge(ge=2)]) --

    By default it is set to 3.

  • xtol_rel (Annotated[float, Ge(ge=0), Ge(ge=0), Ge(ge=0), Ge(ge=0), Ge(ge=0)]) --

    By default it is set to 1e-09.

  • xtol_abs (Annotated[float, Ge(ge=0), Ge(ge=0), Ge(ge=0), Ge(ge=0), Ge(ge=0)]) --

    By default it is set to 1e-09.

  • n (Annotated[int, Ge(ge=0)]) --

    By default it is set to 100.

  • iters (Annotated[int, Ge(ge=0)]) --

    By default it is set to 1.

  • options (Mapping[str, Any])

  • sampling_method (str) --

    By default it is set to "simplicial".

  • workers (Annotated[int, Gt(gt=0)]) --

    By default it is set to 1.

Return type:

None

iters: NonNegativeInt = 1#

The number of iterations used to construct the simplicial complex.

Constraints:

  • ge = 0

n: NonNegativeInt = 100#

The number of samples used to construct the simplicial complex.

Constraints:

  • ge = 0

options: StrKeyMapping [Optional]#

The options for the local optimization algorithm.

sampling_method: str = 'simplicial'#

The sampling method.

workers: PositiveInt = 1#

The number workers to parallelize on.

Constraints:

  • gt = 0

model_post_init(context, /)#

We need to both initialize private attributes and call the user-defined model_post_init method.

Parameters:

  • self (BaseModel)

  • context (Any)

Return type:

None