PriorWeightsDust¶
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class
beast.physicsmodel.prior_weights_dust.PriorWeightsDust(av_vals, av_model, rv_vals, rv_model, fA_vals, fA_model)[source]¶ Bases:
objectCompute the priors as weights given the input grid
Initialize with basic information
Methods Summary
get_av_weight(av)Get the weight for one A(V)
get_fA_weight(fA)Get the weight for one f_A
get_rv_weight(rv)Get the weight for one R(V)
get_weight(av, rv, fA)Get the weight for one point in A(V), R(V), f_A space
set_av_weights([model])Weights on A(V) based on input model choice
set_fA_weights([model])Weights on f_A based on input model choice
set_rv_weights([model])Weights on R(V) based on input model choice
Methods Documentation
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get_av_weight(av)[source]¶ Get the weight for one A(V)
- Parameters
- av: float
A(V) of point
- Returns
- weight: float
weight fo the point
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get_fA_weight(fA)[source]¶ Get the weight for one f_A
- Parameters
- fA: float
f_A of point
- Returns
- weight: float
weight fo the point
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get_rv_weight(rv)[source]¶ Get the weight for one R(V)
- Parameters
- rv: float
R(V) of point
- Returns
- weight: float
weight fo the point
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get_weight(av, rv, fA)[source]¶ Get the weight for one point in A(V), R(V), f_A space
- Parameters
- av: float
A(V) of point
- rv: float
R(V) of point
- fA: float
f_A of point
- Returns
- weight: float
weight fo the point
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set_av_weights(model={'name': 'flat'})[source]¶ Weights on A(V) based on input model choice
- Parameters
- model: dict
Choice of model type [default=flat] flat = flat prior on linear A(V) lognormal = lognormal prior on linear A(V) two_lognormal = two lognormal prior on linear A(V) exponential = exponential prior on linear A(V)
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