Scipy Optimizer Parameters
ScipyOptimizerParams ¶
Bases: BaseModel
Wrapper for scipy.optimize.minimize.
See https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html for more information of the available methods and parameters.
Attributes:
Name | Type | Description |
---|---|---|
method |
ScipyOptimizerMethod
|
Type of solver. See https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html for supported methods. |
tol |
float | None
|
Tolerance for termination. |
bounds |
None | list[tuple[float, float]]
|
Bounds on variables for Nelder-Mead, L-BFGS-B, TNC, SLSQP, Powell,
trust-constr, COBYLA, and COBYQA methods. |
jac |
None | Literal['2-point', '3-point', 'cs']
|
Method for computing the gradient vector. Only for CG, BFGS, Newton-CG, L-BFGS-B, TNC, SLSQP, dogleg, trust-ncg, trust-krylov, trust-exact and trust-constr. |
hess |
None | Literal['2-point', '3-point', 'cs']
|
Method for computing the Hessian matrix. Only for Newton-CG, dogleg, trust-ncg, trust-krylov, trust-exact and trust-constr. |
maxiter |
int
|
Maximum number of iterations to perform. Depending on the method each iteration may use several function evaluations. Will be ignored for TNC optimizer. Default: 100 |
options |
dict[str, float]
|
A dictionary of solver options. |
bounds
class-attribute
instance-attribute
¶
bounds: None | list[tuple[float, float]] = Field(
default=None,
description="Bounds on variables for Nelder-Mead, L-BFGS-B, TNC, SLSQP, Powell,trust-constr, COBYLA, and COBYQA methods. None is used to specify no bounds. A sequence of `(min, max)` can be used to specify bounds for each parameter individually.",
)
hess
class-attribute
instance-attribute
¶
hess: None | Literal["2-point", "3-point", "cs"] = Field(
default=None,
description="Method for computing the Hessian matrix. Only for Newton-CG, dogleg, trust-ncg, trust-krylov, trust-exact and trust-constr.",
)
jac
class-attribute
instance-attribute
¶
jac: None | Literal["2-point", "3-point", "cs"] = Field(
default=None,
description="Method for computing the gradient vector. Only for CG, BFGS, Newton-CG, L-BFGS-B, TNC, SLSQP, dogleg, trust-ncg, trust-krylov, trust-exact and trust-constr.",
)
maxiter
class-attribute
instance-attribute
¶
maxiter: int = Field(
default=100,
ge=1,
le=10000,
description="Maximum number of iterations to perform. Depending on the method each iteration may use several function evaluations. Will be ignored for TNC optimizer.",
)
method
class-attribute
instance-attribute
¶
method: ScipyOptimizerMethod = Field(
default="cobyla",
description="Type of solver. See https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.htmlfor supported methods.",
)
options
class-attribute
instance-attribute
¶
options: dict[str, float] = Field(
default_factory=dict, description="A dictionary of solver options."
)
tol
class-attribute
instance-attribute
¶
ScipyOptimizerMethod
module-attribute
¶
ScipyOptimizerMethod = Literal[
"nelder-mead",
"powell",
"cg",
"bfgs",
"newton-cg",
"l-bfgs-b",
"tnc",
"cobyla",
"cobyqa",
"slsqp",
"trust-constr",
"dogleg",
"trust-ncg",
"trust-exact",
"trust-krylov",
"NELDER-MEAD",
"POWELL",
"CG",
"BFGS",
"NEWTON-CG",
"L-BFGS-B",
"TNC",
"COBYLA",
"COBYQA",
"SLSQP",
"TRUST-CONSTR",
"DOGLEG",
"TRUST-NCG",
"TRUST-EXACT",
"TRUST-KRYLOV",
"Nelder-Mead",
"Newton-CG",
]