pandakota.input.derivatives module

Derivatives

Gradients (first derivative) and Hessians (second derivatives)

class pandakota.input.derivatives.Derivatives(derivative_type: str, fd_step_size: Iterable[float], id_numerical: Iterable[int], id_analytic: Iterable[int])

Bases: ABC

Abstract Bace Class for Derivatives

Attributes:

order

Methods

to_string

key = 'derivatives # this class is not meant to be instantiated directly'

order = None

to_string() → str

class pandakota.input.derivatives.Gradients(gradient_type: str, method_source: str | None = None, interval_type: str | None = None, fd_step_size: Iterable[float] | None = None, id_numerical: Iterable[int] | None = None, id_analytic: Iterable[int] | None = None)

Bases: Derivatives

First Derivatives

Attributes:

gradient_type

Methods

to_string

property gradient_type

key = 'gradients'

order = 1

to_string()

class pandakota.input.derivatives.Hessians(hessian_type: str, interval_type: str | None = None, step_scaling: str | None = None, quasi_approximation: str | None = None, fd_step_size: Iterable[float] | None = None, id_numerical: Iterable[int] | None = None, id_analytic: Iterable[int] | None = None, id_quasi: Iterable[int] | None = None, damped: bool = False)

Bases: Derivatives

Second Derivatives

Attributes:

hessian_type

Methods

to_string

property hessian_type

key = 'hessians'

order = 2

to_string() → str