beast.fitting.trim_grid.trim_models(sedgrid, sedgrid_noisemodel, obsdata, sed_outname, noisemodel_outname, sigma_fac=3.0, n_detected=4, inFlux=True, trunchen=False)[source]

For a given set of observations, there will be models that are so bright or faint that they will always have ~0 probability of fitting the data. This program trims those models out of the SED grid so that time is not spent calculating model points that are always zero probability.

sedgrid: grid.SEDgrid instance

model grid

sedgrid_noisemodel: beast noisemodel instance

noise model data

obsdata: Observation object instance

observation catalog

sed_outname: str

name for output sed file

noisemodel_outname: str

name for output noisemodel file

sigma_fac: float

factor for trimming the upper and lower range of grid so that the model range cuts off sigma_fac above and below the brightest and faintest models, respectively (default: 3.)

n_detected: int

minimum number of bands where ASTs yielded a detection for a given model, if fewer detections than n_detected this model gets eliminated (default: 4)

inFlux: boolean

if true data are in fluxes (default: True)

trunchen: boolean

if true use the trunchen noise model (default: False)