make_extinguished_grid

beast.physicsmodel.creategrid.make_extinguished_grid(spec_grid, filter_names, extLaw, avs, rvs, fAs=None, av_prior_model={'name': 'flat'}, rv_prior_model={'name': 'flat'}, fA_prior_model={'name': 'flat'}, chunksize=0, add_spectral_properties_kwargs=None, absflux_cov=False, filterLib=None)[source]

Extinguish spectra and extract an SEDGrid through given series of filters (all wavelengths in stellar SEDs and filter response functions are assumed to be in Angstroms)

Parameters
spec_grid: string or grid.SpectralGrid

if string: spec_grid is the filename to the grid file with stellar spectra the backend to load this grid will be the minimal invasive: ‘HDF’ if possible, ‘cache’ otherwise.

if not a string, expecting the corresponding SpectralGrid instance (backend already setup)

filter_names: list

list of filter names according to the filter lib

Avs: sequence

Av values to iterate over

av_prior_model: list

list including prior model name and parameters

Rvs: sequence

Rv values to iterate over

rv_prior_model: list

list including prior model name and parameters

fAs: sequence (optional)

f_A values to iterate over f_A can be omitted if the extinction Law does not use it or allow fixed values

fA_prior_model: list

list including prior model name and parameters

chunksize: int, optional (default=0)

number of extinction model variations to generate at each cycle. Note that this means len(spec_grid * chunksize) If default <= 0, all models will be returned at once.

filterLib: str

full filename to the filter library hd5 file

add_spectral_properties_kwargs: dict

keyword arguments to call add_spectral_properties() at each iteration to add model properties from the spectra into the grid property table

asbflux_cov: boolean

set to calculate the absflux covariance matrices for each model (can be very slow!!! But it is the right thing to do)

Returns
g: grid.SpectralGrid

final grid of reddened SEDs and models