supaernova.analysis.spectra

source module supaernova.analysis.spectra

Classes

• SpectraPlot — Create a new model by parsing and validating input data from keyword arguments.

• SpectraPlotter

source class SpectraPlot(**data: Any)

Bases : AbstractPlot

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Attributes

• model_extra : dict[str, Any] | None — Get extra fields set during validation.

• model_fields_set : set[str] — Returns the set of fields that have been explicitly set on this model instance.

source class SpectraPlotter()

Bases : Plotter

Methods

• prep

• plot_spectra

• plot_summary

• plot_residual

source staticmethod SpectraPlotter.prep(data: DataStepResult, config: SpectraPlot) → tuple['npt.NDArray[np.float32]', 'npt.NDArray[np.float32]', 'npt.NDArray[np.float32]', 'npt.NDArray[np.int32]', 'npt.NDArray[np.int32]', 'npt.NDArray[np.int32]']

source staticmethod SpectraPlotter.plot_spectra(data: DataStepResult, config: SpectraPlot, *args: Any, fig: Figure | None = None, ax: Axis | None = None, force: bool = False, save: bool = True, **kwargs: Any) → tuple['Figure', 'Axis'] | None

source staticmethod SpectraPlotter.plot_summary(data: DataStepResult, config: SpectraPlot, *args: Any, fig: Figure | None = None, ax: Axis | None = None, force: bool = False, save: bool = True, **kwargs: Any) → tuple['Figure', 'Axis'] | None

source staticmethod SpectraPlotter.plot_residual(data: DataStepResult, amplitude_prime: npt.NDArray[np.float32], config: SpectraPlot, *args: Any, fig: Figure | None = None, ax: Axis | None = None, force: bool = False, save: bool = True, **kwargs: Any) → tuple['Figure', 'Axis'] | None