drizzle_from_visit

grizli.utils.drizzle_from_visit(visit, output=None, pixfrac=1.0, kernel='point', clean=True, include_saturated=True, keep_bits=None, dryrun=False, skip=None, extra_wfc3ir_badpix=True, verbose=True, scale_photom=True, context='jwst_1130.pmap', weight_type='jwst', rnoise_percentile=99, calc_wcsmap=False, niriss_ghost_kwargs={}, snowblind_kwargs=None, get_dbmask=True)[source]

Make drizzle mosaic from exposures in a visit dictionary

Parameters
visitdict

Visit dictionary with ‘product’ and ‘files’ keys

outputWCS, Header, ImageHDU

Output frame definition. Can be a WCS object, header, or FITS HDU. If None, then generates a WCS with grizli.utils.make_maximal_wcs

pixfracfloat

Drizzle pixfrac

kernelstr

Drizzle kernel (e.g., ‘point’, ‘square’)

cleanbool

Remove exposure files after adding to the mosaic

include_saturatedbool

Include pixels with saturated DQ flag

keep_bitsint, None

Extra DQ bits to keep as valid

dryrunbool

If True, don’t actually produce the output

skipint

Slice skip to drizzle a subset of exposures

extra_wfc3ir_badpixbool

Apply extra WFC3/IR bad pix to DQ

verbosebool

Some verbose message printing

scale_photombool

For JWST, apply photometry scale corrections from the grizli/data/photom_correction.yml table

weight_type‘err’, ‘median_err’, ‘time’, ‘jwst’

Exposure weighting strategy.

  • The default ‘err’ strategy uses the full uncertainty array defined in the ERR image extensions. The alternative

  • The ‘median_err’ strategy uses the median of the ERR extension

  • The ‘time’ strategy weights ‘median_err’ by the TIME extension, if available

  • For the ‘jwst’ strategy, if ‘VAR_POISSON’ and ‘VAR_RNOISE’ extensions found, weight by VAR_RNOISE + median(VAR_POISSON). Fall back to ‘median_err’ otherwise.

rnoise_percentilefloat

Percentile defining the upper limit of valid VAR_RNOISE values, if that extension is found in the exposure files(e.g., for JWST)

niriss_ghost_kwargsdict

Keyword arguments for niriss_ghost_mask

snowblind_kwargsdict

Arguments to pass to jwst_snowblind_mask if snowblind hasn’t already been run on JWST exposures

Returns
outsciarray-like

SCI array

outwhtarray-like

Inverse variance WHT array

headerHeader

Image header

flistlist

List of files that were drizzled to the mosaic

wcs_tabTable

Table of WCS parameters of individual exposures