parsac.optimize.plot module

class parsac.optimize.plot.PlotType(*values)

Bases: Enum

GENERATIONS = 2

MARGINAL = 1

class parsac.optimize.plot.Result(db_file: str | PathLike[Any], skip_lnl: bool = True, skip_inferred=False)

Bases: object

generations: ndarray | None

get_confidence_interval(lnl_crit=1.920729410347062) → tuple[ndarray, ndarray]

Get the confidence interval for all parameters.

get_errors() → list[str]

iselect: list[int]

parnames: list[str]

plot(lnl_range: float | None = None, bincount: int = 25, keep_updating: bool = False, save: str | PathLike[Any] | None = None, plot_type: PlotType = PlotType.MARGINAL, logger: Logger | None = None) → Figure

plot_best(target_dir: str | PathLike[Any] | None = None, logger: Logger | None = None, rank: int = 1) → list[Figure]

property rowcount: int

Number of rows in the results table.

save_best(file: str | PathLike[Any], *, sep: str = '\t') → None

Save the best parameter set to a file.

update() → int

Update the results from the database.