tardis.opacities.macro_atom.base module

class tardis.opacities.macro_atom.base.NonMarkovChainTransitionProbabilities(plasma_parent)

Bases: TransitionProbabilities

outputs = ('non_markov_transition_probabilities',)

class tardis.opacities.macro_atom.base.TransitionProbabilities(plasma_parent)

Bases: ProcessingPlasmaProperty

Attributes:

transition_probabilitiesPandas DataFrame, dtype float

calculate(atomic_data, beta_sobolev, j_blues, stimulated_emission_factor, tau_sobolevs)

initialize_macro_atom_transition_type_filters(atomic_data, macro_atom_data)

outputs = ('transition_probabilities',)

prepare_transition_probabilities(macro_atom_data, beta_sobolev, j_blues, stimulated_emission_factor)

tardis.opacities.macro_atom.base.get_macro_atom_data(atomic_data)

Get the macro atom data from the atomic data

Parameters:

atomic_datatardis.io.atom_data.AtomData

Atomic Data

Returns:

pd.DataFrame

The macro atom data in the plasma

tardis.opacities.macro_atom.base.get_transition_probability_coefs(macro_atom_data)

Coefficients of the transition probabilities

Parameters:

macro_atom_datapd.DataFrame

Macro Atom Data

Returns:

np.ndarray

Reshaped macro atom transition probabilities

tardis.opacities.macro_atom.base.initialize_macro_atom_transition_type_filters(atomic_data, macro_atom_data)

Get the filters and block references from the macro atom

Parameters:

atomic_datatardis.io.atom_data.AtomData

Atomic Data

macro_atom_datapd.DataFrame

Macro Atom Data

Returns:

np.ndarray

Mask where the transition type is 1

np.ndarray

index of lines at these locations

pd.ndarray

macro atom block references

tardis.opacities.macro_atom.base.initialize_transition_probabilities(atomic_data)

Convienience Function for initializing the transition probabilities

Parameters:

atomic_datatardis.io.atom_data.AtomData

Atomic Data

Returns:

dict

“transition_probability_coef”np.ndarray

Reshaped macro atom transition probabilities

“block_references”: np.ndarray

macro atom block references