gen_SimObs_from_sedgrid

beast.observationmodel.observations.gen_SimObs_from_sedgrid(sedgrid, sedgrid_noisemodel, nsim=100, compl_filter='max', complcut=None, magcut=None, ranseed=None, vega_fname=None, weight_to_use='weight', age_prior_model=None, mass_prior_model=None)[source]

Generate simulated observations using the physics and observation grids. The priors are sampled as they give the ensemble model for the stellar and dust distributions (IMF, Av distribution etc.). The physics model gives the SEDs based on the priors. The observation model gives the noise, bias, and completeness all of which are used in simulating the observations.

Currently written to only work for the toothpick noisemodel.

Parameters:

  • sedgrid (grid.SEDgrid instance) – model grid

  • sedgrid_noisemodel (beast noisemodel instance) – noise model data

  • nsim (int) – number of observations to simulate

  • compl_filter (str) – Filter to use for completeness (required for toothpick model). Set to max to use the max value in all filters.

  • complcut (float (defualt=None)) – completeness cut for only including model seds above the cut where the completeness cut ranges between 0 and 1.

  • magcut (float (defualt=None)) – faint-end magnitude cut for only including model seds brighter than the given magnitude in compl_filter.

  • ranseed (int) – used to set the seed to make the results reproducable, useful for testing

  • vega_fname (string) – filename for the vega info, useful for testing

  • weight_to_use (string (default='weight')) – Set to either ‘weight’ (prior+grid), ‘prior_weight’, ‘grid_weight’, or ‘uniform’ (this option is valid only when nsim is supplied) to choose the weighting for SED selection.

  • age_prior_model (dict) – age prior model in the BEAST dictonary format

  • mass_prior_model (dict) – mass prior model in the BEAST dictonary format

Returns:

simtable – table giving the simulated observed fluxes as well as the physics model parmaeters

Return type:

astropy Table