FitResult

class lsst.multiprofit.FitResult(*, chisq_best: float = 0, config: ModelFitConfig = None, inputs: FitInputs | None = None, result: Any | None = None, params: tuple[ParameterD, ...] | None = None, params_best: tuple[float, ...] | None = None, params_free_missing: tuple[ParameterD, ...] | None = None, n_eval_resid: int = 0, n_eval_func: int = 0, n_eval_jac: int = 0, time_eval: float = 0, time_run: float = 0)

Bases: BaseModel

Results from a Modeller fit, including metadata.

Attributes Summary

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

Attributes Documentation

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True, 'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].