grism_background_subtraction

niriss_tools.pipeline.grism_background_subtraction(prep_dir='../Prep', field_root='glass-a2744', filters=['f115wn-clear', 'f150wn-clear', 'f200wn-clear'], bkg_box_size=3, smooth_gauss_std=1, min_bkg_thresh=0.0, background2d_kwargs={}, diffuse_catalogue_kwargs={}, grism_prep_kwargs={}, **kwargs)

Model and subtract a dispersed background from WFSS data.

Parameters:

prep_dirPathLike, optional

The default location for all data, by default "../Prep".

field_rootstr, optional

The name of the field, by default "glass-a2744".

filterslist[str], optional

The names of the filters used, by default ["f115wn-clear", "f150wn-clear", "f200wn-clear"].

bkg_box_sizefloat, optional

The size of the boxes within which to calculate the background (in arcseconds), by default 3.

smooth_gauss_stdfloat, optional

The standard deviation of the Gaussian used to smooth the background (in arcseconds), by default 1.

min_bkg_threshfloat, optional

The minimum background value to be used. By default 0, which means that only positive values of the background will be dispersed and subtracted.

background2d_kwargsdict, optional

Any additional arguments to pass to photutils.background.Background2D, by default {}.

diffuse_catalogue_kwargsdict, optional

Any additional arguments to pass to grizli.pipeline.auto_script.multiband_catalog, by default ``{}`. Parameters passed here determine the extraction of the diffuse background, rather than the science objects in the field.

grism_prep_kwargsdict, optional

Any additional arguments to pass to grizli.pipeline.auto_script.grism_prep, by default {}.

**kwargsdict, optional

Any additional keyword arguments.