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Scipy Optimizer Parameters

ScipyOptimizerParams

Bases: BaseModel

Wrapper for scipy.optimize.minimize.

See SciPy minimize documentation for more information of the available methods and parameters.

Attributes:

Name Type Description
method ScipyOptimizerMethod

Type of solver. See SciPy minimize documentation 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. None is used to specify no bounds. A sequence of (min, max) can be used to specify bounds for each parameter individually.
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 

tol: float | None = Field(
    default=None, ge=0, description="Tolerance for termination."
)

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",
]