gemseo.algos.opt.nlopt.settings.base_nlopt_settings module#

Settings for the NLopt algorithms.

Settings BaseNLoptSettings(*, enable_progress_bar=None, eq_tolerance=0.01, 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-08, ftol_abs=1e-14, max_iter=1000, scaling_threshold=None, stop_crit_n_x=None, xtol_rel=1e-08, xtol_abs=1e-14, stopval=-inf)[source]#

Bases: BaseOptimizerSettings

The NLopt optimization library 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 0.01.

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

    By default it is set to 1e-08.

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

    By default it is set to 1e-14.

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

    By default it is set to 1000.

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

  • stop_crit_n_x (Annotated[int | None, Ge(ge=2)])

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

    By default it is set to 1e-08.

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

    By default it is set to 1e-14.

  • stopval (float) --

    By default it is set to -inf.

Return type:

None

ftol_abs: NonNegativeFloat = 1e-14#

The absolute tolerance on the objective function.

Constraints:

  • ge = 0

ftol_rel: NonNegativeFloat = 1e-08#

The relative tolerance on the objective function.

Constraints:

  • ge = 0

stop_crit_n_x: int | None = None#

The minimum number of design vectors to consider in the stopping criteria.

Constraints:

  • ge = 2

stopval: float = -inf#

The objective value at which the optimization will stop.

xtol_abs: NonNegativeFloat = 1e-14#

The absolute tolerance on the design parameters.

Constraints:

  • ge = 0

xtol_rel: NonNegativeFloat = 1e-08#

The relative tolerance on the design parameters.

Constraints:

  • ge = 0