create_mask
- jwst.clean_flicker_noise.clean_flicker_noise.create_mask(input_model, mask_science_regions=False, n_sigma=2.0, fit_histogram=False, single_mask=False, soss_refmodel=None)[source]
Create a mask identifying background pixels.
- Parameters:
- input_model
JwstDataModel Science data model, containing rate data with all necessary pre-processing already performed.
- mask_science_regionsbool, optional
For NIRSpec, mask regions of the image defined by WCS bounding boxes for slits/slices, as well as any regions known to be affected by failed-open MSA shutters. This requires the
assign_wcsandmsaflagopensteps to have been run on the input_model. For MIRI imaging, mask regions of the detector not used for science. This requires that DO_NOT_USE flags are set in the DQ array for the input_model. For NIRISS SOSS, use thesoss_refmodelto mask the trace locations.- n_sigmafloat, optional
Sigma threshold for masking outliers. Set to 0 to skip outlier rejection.
- fit_histogrambool, optional
If set, the ‘sigma’ used with
n_sigmafor clipping outliers is derived from a Gaussian fit to a histogram of values. Otherwise, a simple iterative sigma clipping is performed.- single_maskbool, optional
If set, a single mask will be created, regardless of the number of input integrations. Otherwise, the mask will be a 3D cube, with one plane for each integration.
- soss_refmodel
PastasossModel, optional If
mask_science_regionsis True and the input exposure is NIS_SOSS, will be used to mask the SOSS traces.
- input_model
- Returns:
- maskndarray of bool
2D or 3D image mask