tardis.plasma.equilibrium.inputs module

class tardis.plasma.equilibrium.inputs.ContinuumRateCoefficients(photoionization: ndarray[tuple[Any, ...], dtype[float64]], collisional_ionization: ndarray[tuple[Any, ...], dtype[float64]], spontaneous_recombination: ndarray[tuple[Any, ...], dtype[float64]], stimulated_recombination: ndarray[tuple[Any, ...], dtype[float64]], collisional_recombination: ndarray[tuple[Any, ...], dtype[float64]])[source]

Bases: object

Level-resolved continuum rate coefficients.

collisional_ionization: ndarray[tuple[Any, ...], dtype[float64]]

collisional_recombination: ndarray[tuple[Any, ...], dtype[float64]]

photoionization: ndarray[tuple[Any, ...], dtype[float64]]

spontaneous_recombination: ndarray[tuple[Any, ...], dtype[float64]]

stimulated_recombination: ndarray[tuple[Any, ...], dtype[float64]]

class tardis.plasma.equilibrium.inputs.LevelEquationRates(ionization: ndarray[tuple[Any, ...], dtype[float64]], recombination: ndarray[tuple[Any, ...], dtype[float64]], ionization_loss_matrix: ndarray[tuple[Any, ...], dtype[float64]])[source]

Bases: object

Density-specific rates used by one reduced level residual.

ionization: ndarray[tuple[Any, ...], dtype[float64]]

ionization_loss_matrix: ndarray[tuple[Any, ...], dtype[float64]]

recombination: ndarray[tuple[Any, ...], dtype[float64]]

class tardis.plasma.equilibrium.inputs.ShellNumberDensity(hydrogen_number_density: float, level_number_density: ndarray[tuple[Any, ...], dtype[float64]], species_level_positions: ndarray[tuple[Any, ...], dtype[int64]])[source]

Bases: object

Absolute population information fixed for one shell.

hydrogen_number_density: float

level_number_density: ndarray[tuple[Any, ...], dtype[float64]]

species_level_positions: ndarray[tuple[Any, ...], dtype[int64]]

class tardis.plasma.equilibrium.inputs.SobolevInputs(lines_lower_level_index: ndarray[tuple[Any, ...], dtype[int64]], lines_upper_level_index: ndarray[tuple[Any, ...], dtype[int64]], g_lower: ndarray[tuple[Any, ...], dtype[float64]], g_upper: ndarray[tuple[Any, ...], dtype[float64]], metastable_upper: ndarray[tuple[Any, ...], dtype[bool]], nlte_lines_mask: ndarray[tuple[Any, ...], dtype[bool]], tau_coefficient: ndarray[tuple[Any, ...], dtype[float64]], line_indices: ndarray[tuple[Any, ...], dtype[int64]], line_index: Index)[source]

Bases: object

Line geometry required to calculate Sobolev tau and beta.

g_lower: ndarray[tuple[Any, ...], dtype[float64]]

g_upper: ndarray[tuple[Any, ...], dtype[float64]]

line_index: Index

line_indices: ndarray[tuple[Any, ...], dtype[int64]]

lines_lower_level_index: ndarray[tuple[Any, ...], dtype[int64]]

lines_upper_level_index: ndarray[tuple[Any, ...], dtype[int64]]

metastable_upper: ndarray[tuple[Any, ...], dtype[bool]]

nlte_lines_mask: ndarray[tuple[Any, ...], dtype[bool]]

tau_coefficient: ndarray[tuple[Any, ...], dtype[float64]]