gemseo.algos.doe.pydoe.settings.pydoe_fullfact module#

Settings for the full factorial DOE from the PyDOE library.

Settings PYDOE_FULLFACT_Settings(*, enable_progress_bar=None, eq_tolerance=0.01, ineq_tolerance=0.0001, log_problem=True, max_time=0.0, normalize_design_space=False, reset_iteration_counters=True, round_ints=True, use_database=True, use_one_line_progress_bar=False, store_jacobian=True, eval_jac=False, n_processes=1, wait_time_between_samples=0.0, callbacks=(), n_samples=0, levels=())[source]#

Bases: BasePyDOESettings

The settings for the full factorial DOE from the pyDOE library.

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)]) --

    By default it is set to 0.01.

  • 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 False.

  • 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.

  • eval_jac (bool) --

    By default it is set to False.

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

    By default it is set to 1.

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

    By default it is set to 0.0.

  • callbacks (Sequence[Annotated[Callable[[int, tuple[dict[str, float | ndarray[Any, dtype[floating[Any]]]], dict[str, ndarray[Any, dtype[floating[Any]]]]]], Any], WithJsonSchema(json_schema={}, mode=None)]]) --

    By default it is set to ().

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

    By default it is set to 0.

  • levels (Sequence[Annotated[int, Gt(gt=0)]] | Annotated[int, Gt(gt=0)]) --

    By default it is set to ().

Return type:

None

levels: Sequence[PositiveInt] | PositiveInt = ()#

The levels.

One must either specify n_samples or levels. The levels are inferred from the number of samples if the former is specified.

n_samples: NonNegativeInt = 0#

The number of samples.

If 0, set from the settings.

Constraints:

  • ge = 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