tardis.opacities.macro_atom.transition_probabilities module

class tardis.opacities.macro_atom.transition_probabilities.MarkovChainIndex(plasma_parent)[source]

Bases: ProcessingPlasmaProperty

Attributes:
idx2mkv_idxpandas.Series, dtype int
k_packet_idxint

Macro atom level idx corresponding to a k-packet.

idx2deactivation_idxpandas.Series, dtype int
calculate(atomic_data, continuum_interaction_species)[source]
outputs = ('idx2mkv_idx', 'k_packet_idx', 'idx2deactivation_idx')
class tardis.opacities.macro_atom.transition_probabilities.MarkovChainTransProbs(plasma_parent)[source]

Bases: ProcessingPlasmaProperty, SpMatrixSeriesConverterMixin

calculate(p_combined, idx2mkv_idx)[source]
latex_name = ('N', 'R', 'B', 'p_\\textrm{deactivation}')
Attributes:
Npandas.DataFrame, dtype float

Fundamental matrix of the Markov-chain macro atom. Indexed by source_level_idx, destination_level_idx. Expected number of visits to destination_level_idx starting from souce_level_idx (before being absorbed).

Rpandas.DataFrame, dtype float

Deactivation probabilities of the Markov-chain macro atom. Indexed by source_level_idx. Probability of deactivation/absorption in source_level_idx.

Bpandas.DataFrame, dtype float

Absorbing probabilities of the Markov-chain macro atom. Indexed by source_level_idx, destination_level_idx. Probability of being absorbed in destination_level_idx when starting from source_level_idx.

p_deactivationpandas.DataFrame, dtype float

Redistribution probabilities after deactivation of the Markov-chain macro atom. Indexed by source_level_idx, destination_level_idx. Probability of an r-packet being emitted in the transition (source_level_idx –> destination_level_idx) after deactivation in source_level_idx.

outputs = ('N', 'R', 'B', 'p_deactivation')
class tardis.opacities.macro_atom.transition_probabilities.MarkovChainTransProbsCollector(plasma_parent, inputs)[source]

Bases: ProcessingPlasmaProperty

Attributes:
p_combinedpandas.DataFrame, dtype float

Combined and normalized transition probabilities. Indexed by source_level_idx, destination_level_idx.

calculate(*args)[source]
outputs = ('p_combined',)
class tardis.opacities.macro_atom.transition_probabilities.MonteCarloTransProbs(plasma_parent)[source]

Bases: ProcessingPlasmaProperty

calculate(non_markov_transition_probabilities, atomic_data, non_continuum_trans_probs_mask, k_packet_idx, idx2deactivation_idx, level_idxs2transition_idx, p_deactivation, cool_rate_fb, cool_rate_fb_tot, level2continuum_idx, B)[source]
outputs = ('non_continuum_trans_probs', 'level_absorption_probs', 'deactivation_channel_probs', 'transition_probabilities', 'macro_block_references', 'macro_atom_data')
Attributes:
non_continuum_trans_probs
level_absorption_probs
deactivation_channel_probs
transition_probabilities
macro_block_references
macro_atom_data
class tardis.opacities.macro_atom.transition_probabilities.NonContinuumTransProbsMask(plasma_parent)[source]

Bases: ProcessingPlasmaProperty

Attributes:
non_continuum_trans_probs_masknumpy.ndarray, dtype bool
calculate(atomic_data, continuum_interaction_species)[source]
outputs = ('non_continuum_trans_probs_mask',)