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

Settings for the central composite DOE from the pyDOE library.

class Alpha(*values)[source]#

Bases: StrEnum

A parameter to describe how the variance is distributed.

o = 'o'#
orthogonal = 'orthogonal'#
r = 'r'#
rotatable = 'rotatable'#
class Face(*values)[source]#

Bases: StrEnum

The relation between the start points and the corner (factorial) points.

ccc = 'ccc'#
ccf = 'ccf'#
cci = 'cci'#
circumscribed = 'circumscribed'#
faced = 'faced'#
inscribed = 'inscribed'#
Settings PYDOE_CCDESIGN_Settings(*, enable_progress_bar=None, eq_tolerance=0.01, ineq_tolerance=0.0001, log_problem=True, max_time=0.0, normalize_design_space=False, progress_bar_data_name='ProgressBarData', reset_iteration_counters=True, round_ints=True, store_jacobian=True, use_database=True, use_one_line_progress_bar=False, eval_func=True, eval_jac=False, n_processes=1, wait_time_between_samples=0.0, callbacks=(), preprocessors=(), vectorize=False, alpha=Alpha.orthogonal, center=(4, 4), face=Face.circumscribed)[source]#

Bases: BasePyDOESettings

The settings for the central composite 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)]) --

    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.

  • progress_bar_data_name (ProgressBarDataName) --

    By default it is set to "ProgressBarData".

  • reset_iteration_counters (bool) --

    By default it is set to True.

  • round_ints (bool) --

    By default it is set to True.

  • store_jacobian (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.

  • eval_func (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[tuple[Any, ...], dtype[floating[Any]]]], dict[str, ndarray[tuple[Any, ...], dtype[floating[Any]]]]]], Any], WithJsonSchema(json_schema={}, mode=None)]]) --

    By default it is set to ().

  • preprocessors (Sequence[Annotated[Callable[[int], Any], WithJsonSchema(json_schema={}, mode=None)]]) --

    By default it is set to ().

  • vectorize (bool) --

    By default it is set to False.

  • alpha (Alpha) --

    By default it is set to "orthogonal".

  • center (tuple[int, int]) --

    By default it is set to (4, 4).

  • face (Face) --

    By default it is set to "circumscribed".

Return type:

None

alpha: Alpha = Alpha.orthogonal#

A parameter to describe how the variance is distributed.

Either "orthogonal" or "rotatable".

center: tuple[int, int] = (4, 4)#

The 2-tuple of center points for the central composite design.

face: Face = Face.circumscribed#

The relation between the start and corner (factorial) points.

model_post_init(context, /)#

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that's what pydantic-core passes when calling it.

Parameters:

  • self (BaseModel) -- The BaseModel instance.

  • context (Any) -- The context.

Return type:

None