summary_table_memory

beast.fitting.fit.summary_table_memory(obs, noisemodel, sedgrid, keys=None, gridbackend='memory', threshold=-10, save_every_npts=None, lnp_npts=None, resume=False, max_nbins=200, stats_outname=None, pdf1d_outname=None, pdf2d_outname=None, pdf2d_param_list=None, grid_info_dict=None, lnp_outname=None, use_full_cov_matrix=True, surveyname='PHAT', extraInfo=False, do_not_normalize=False)

Do the fitting in memory

Parameters:

obsObservation object instance

observation catalog

noisemodelbeast noisemodel instance

noise model data

sedgridstr or grid.SEDgrid instance

model grid

keysstr or list of str

if str - name of the quantity or expression to evaluate from the grid table if list - list of quantities or expresions

gridbackendstr or grid.GridBackend

backend to use to load the grid if necessary (memory, cache, hdf) (see beast.core.grid)

save_every_nptsinteger

set to save the files below (if set) every n stars a requirement for recovering from partially complete runs

resumebool

set to designate this run is resuming a partially complete run

use_full_cov_matrixbool

set to use the full covariance matrix if it is present in the noise model file

max_nbinsint (default=200)

maxiumum number of bins to use for the 1D likelihood calculations

stats_outnamestr

set to output the stats file into a FITS file with extensions

pdf1d_outnamestr

set to output the 1D PDFs into a FITS file with extensions

pdf2d_outnamestr

set to output the 2D PDFs into a FITS file with extensions

pdf2d_param_listlist of strings or None

set to the parameters for which to make the 2D PDFs

grid_info_dictdict

Set to override the mins/maxes of the 1dpdfs, and the number of unique values.

lnp_outnamestr

set to output the sparse likelihoods into a (usually HDF5) file

thresholdfloat

value above which to use/save for the lnps (defines the sparse likelihood)

lnp_nptsint

set to a number to output a random sampling of the lnp points above the threshold. otherwise, the full sparse likelihood is output

surveynamestr

name of survey [default = ‘PHAT’]

extraInfobool

set to get extra information, such as IAU name, brick, field, etc.

do_not_normalizebool

Do not normalize the prior weights before applying them. This should have no effect on the final outcome when using only a single grid, but is essential when using the subgridding approach.

Returns:

N/A