gemseo.algos.opt.base_optimizer_settings module#
Settings for the optimization algorithms.
- Settings BaseOptimizerSettings(*, 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=0.0, ftol_abs=0.0, max_iter=1000, scaling_threshold=None, stop_crit_n_x=3, xtol_rel=0.0, xtol_abs=0.0)#
Bases:
BaseDriverSettings
The common parameters for all optimization libraries.
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 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)]) --
By default it is set to 0.0.
ftol_abs (Annotated[float, Ge(ge=0)]) --
By default it is set to 0.0.
max_iter (Annotated[int, Gt(gt=0)]) --
By default it is set to 1000.
stop_crit_n_x (Annotated[int, Ge(ge=2)]) --
By default it is set to 3.
xtol_rel (Annotated[float, Ge(ge=0)]) --
By default it is set to 0.0.
xtol_abs (Annotated[float, Ge(ge=0)]) --
By default it is set to 0.0.
- Return type:
None
- ftol_abs: NonNegativeFloat = 0.0#
The absolute tolerance on the objective function.
- Constraints:
ge = 0
- ftol_rel: NonNegativeFloat = 0.0#
The relative tolerance on the objective function.
- Constraints:
ge = 0
- max_iter: PositiveInt = 1000#
The maximum number of iterations.
- Constraints:
gt = 0
- scaling_threshold: NonNegativeFloat | None = None#
The threshold on the reference function value that triggers scaling.
If
None
, do not scale the functions.
- stop_crit_n_x: int = 3#
The minimum number of design vectors to consider in the stopping criteria.
- Constraints:
ge = 2
- xtol_abs: NonNegativeFloat = 0.0#
The absolute tolerance on the design parameters.
- Constraints:
ge = 0
- xtol_rel: NonNegativeFloat = 0.0#
The relative tolerance on the design parameters.
- 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