gemseo.algos.doe.scipy.settings.poisson_disk module#
Settings for the Poisson disk DOE from the SciPy library.
- Settings PoissonDisk_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_func=True, eval_jac=False, n_processes=1, wait_time_between_samples=0.0, callbacks=(), n_samples, seed=None, optimization=None, radius=0.05, hypersphere=Hypersphere.volume, ncandidates=30)[source]#
Bases:
BaseSciPyDOESettings
The settings for the Poisson disk DOE from the SciPy 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), 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 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_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[Any, dtype[floating[Any]]]], dict[str, ndarray[Any, dtype[floating[Any]]]]]], Any], WithJsonSchema(json_schema={}, mode=None)]]) --
By default it is set to ().
seed (int | None)
optimization (Optimizer | None)
radius (Annotated[float, Ge(ge=0)]) --
By default it is set to 0.05.
hypersphere (Hypersphere) --
By default it is set to "volume".
ncandidates (Annotated[int, Gt(gt=0)]) --
By default it is set to 30.
- Return type:
None
- hypersphere: Hypersphere = Hypersphere.volume#
The sampling strategy to generate potential candidates.
The candidates will be added in the final sample.
- ncandidates: PositiveInt = 30#
The number of candidates to sample per iteration.
- Constraints:
gt = 0
- optimization: Optimizer | None = None#
The name of an optimization scheme to improve the DOE's quality.
If
None
, use the DOE as is. New in SciPy 1.10.0.
- radius: NonNegativeFloat = 0.05#
The minimal distance to keep between points when sampling new candidates.
- 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