Artificial Star Input Lists¶
The BEAST requires artificial star tests (ASTs) to produce a noise model. The AST input list software generates lists of magnitudes and (if desired) positions for ASTs that can be injected into the observed imaging and then re-photometered to assess the photometric bias, uncertainty, and completeness as a function of the model grid. The output from this software must be run through the same photometry routine (typically DOLPHOT) as used for the photometry measurements themselves.
Once the input lists have been run through the user’s photometry program and each input magnitude has an associated output magnitude (or non-detection value), those results can be used as input ASTs for the building the BEAST noise model.
Generating BEAST-friendly lists of artificial star tests
- Run
run_beast.py -p
to produce the physics model grid fileproject_name_seds.grid.hd5
. - If you wish to repeat ASTs over multiple bins of stellar density or background brightness, run
tools/create_background_density_map.py
on your observed star catalog. See the help message for this script for the necessary arguments. - Run
run_beast.py -a
. This will use the datamodel to find everything it needs to make ASTs (filters, limits, SED grid, etc.). It will produce a list of fake stars in all bands using the datamodel photometry catalog to trim the inputs at the proper magnitudes. Currently, this script generates fake stars uniformly sampling log(age) space and randomly drawing from the metallicities in the model grid. Alternatively, the user can modify the script to use any combination of one of the SED picking, plus one of the position picking functions described below.
Functions¶
Picking SEDs¶
These functions are found in beast.observationmodel.ast.make_ast_input_list
.
mag_limits
: Determines the magnitude limits for the models in each filter in the photometry file.
pick_models
: Samples the model grid and outputs models that fit within the mag limits.
pick_models_toothpick_style
: Tries to pick models in a way that evenly samples the range of fluxes in each band. Models will be picked until each magnitude bin for each band is covered by a given number of fake stars. (Not yet in example.)
Picking positions¶
These functions are found in beast.observationmodel.ast.make_ast_xy_list
pick_positions
: Uses the observed stellar catalog to distribution the artificial stars in a similar spatial pattern to the observed catalog
pick_positions_from_map
: Uses one of the maps generated by create_background_density_map
to make sure that each of the different source density or background regimes in the image are properly sampled. The source density or background range is divided into bins, and the set of SEDs chosen by one of the pick_models
functions above is then reused for each background intensity bin.
Parameters¶
ast_bands_above_maglimit
: integer
Number of filters that must be above the magnitude limit
for an AST to be included in the list (Default = 3)
ast_realization_per_model
: integer
Number of Realizations of each included AST model
to be put into the list. (Default = 20)
ast_maglimit
: float (single value or array with one value per filter)
- option 1: [number] to change the number of mags fainter than the 90th percentile faintest star in the photometry catalog to be used for the mag cut. (Default = 1)
- option 2: [space-separated list of numbers] to set custom faint end limits (one value for each band).
ast_models_selected_per_age
: integer
Number of models to pick per age (if pick_models
is used) (Default = 70).
ast_with_positions
: (bool, optional)
If True
, the ast list is produced with X,Y positions.
If False
, the ast list is produced with only magnitudes.
ast_density_table
: (string, optional)
Name of the density table created by tools.create_background_density_map
If
supplied, pick_positions_from_map
will be used to repeat the ASTs in the table
for each source density or background density region. The source density and
background maps are in the same format.
ast_N_bins
: (int, optional)
Number of source density or background bins that you want ASTs repeated over
Note that ast_density_table
require ast_reference_image
to be specified (see
below).
ast_pixel_distribution
: float (optional)
(Used if ast_with_positions is True), minimum pixel separation between AST
position and catalog star used to determine the AST spatial distribution.
ast_reference_image
: string (optional, but required if ast_with_positions
is True and no X and Y information is present in the photometry catalog)
Name of the reference image used by DOLPHOT when running the measured
photometry.
Returns¶
Table of fake star magnitudes for all bands in the datamodel photometry file.
The file will be in ascii format in the project directory, and it will have the
name: [project]/[project]_inputAST.txt
The table will have <number of ages> * ast_models_selected_per_age *
ast_realization_per_model
lines. If ast_with_positions
is True
then each
line will start with 0 1 X Y
, which are the first four columns required by
DOLPHOT to define the input star position.
In case the new method is used, which samples by background density, this number will be multiplied by the number of background density bins chosen.
The code will also optionally output a fits file, [project]/[project]_ASTparams.fits
,
which has the physical parameters associated with each of the artificial stars. It
has <number of ages> * ast_models_selected_per_age
lines, and has the same
columns as the main SED grid file.