See the
WFPC2 drizzling overview and general tips,
to find a cookbook and/or sample dataset that
best represents your dataset, with regards to
target placement and
pointing strategy.
Cookbook for undithered datasets with the target placed on the PC chip (only)
These instructions are intended for datasets with no dithering
(i.e. CR-SPLIT), and the target on the PC chip. This strategy was common in the mid-1990s,
so many archival datasets from that era may not be dithered.
For CR-SPLIT datasets, the rejection of cosmic rays is usually good.
But detector artifacts such as bad columns and hot pixels won't be rejected,
and so they will either remain on the final output, or be replaced
with a fill value. Such artifacts can also be replaced via cosmetic
interpolation, although that is not described here.
De-archive the science and data quality FITS files to your working
directory. Make a uref directory and download the distortion reference files
(IDCTAB and OFFTAB in your image headers) into it, and define your uref
directory (set uref). Convert the files to GEIS format (with strfits), and make
a list of input images (list_c0h):
> set uref = "/data/mymachine/uref/"
> strfits *c0f.fits "" ""
> strfits *c1f.fits "" ""
> ls u*c0h > list_c0h (no blank lines!)
If your data are not all from the same visit, or otherwise
did not use the same guide stars, you need to refine the
image registration.
MultiDrizzle parameters
The following are sample parameters (with some rationale in the comments)
for applying the geometric distortion correction, combining, and cleaning your dataset.
Some of the default parameters
are not listed here.
> unlearn multidrizzle # reset all parameters to default values first
multidrizzle.input = '@list_c0h' # input image list
multidrizzle.output = 'ngc999_f555w' # convenient target_filter filenaming
multidrizzle.group = '1' # process PC chip only
multidrizzle.build = no # single-extension FITS output
multidrizzle.shiftfile = 'shifts.txt' # apply measured delta-shifts, if relevant
multidrizzle.static = yes
multidrizzle.skysub = no
multidrizzle.driz_separate = yes
multidrizzle.driz_sep_outnx = 800
multidrizzle.driz_sep_outny = 800
multidrizzle.driz_sep_kernel = 'turbo'
multidrizzle.driz_sep_scale = 0.0455 # PC detector pixel scale
multidrizzle.driz_sep_pixfrac = 1.0
multidrizzle.driz_sep_rot = INDEF # don't rotate north up for CR-detection
multidrizzle.driz_sep_fillval = -9.9 # arbitrary low value; easy to exclude
multidrizzle.driz_sep_bits = 0 # exclude all flagged pixels
multidrizzle.median = yes
multidrizzle.combine_type = 'median'
multidrizzle.combine_lthresh = '-8.8' # exclude fill values from median
multidrizzle.blot = yes
multidrizzle.driz_cr = yes
multidrizzle.driz_cr_snr = '4.0 3.5'
multidrizzle.driz_combine = yes
multidrizzle.final_outnx = 1024
multidrizzle.final_outny = 1024
multidrizzle.final_kernel = 'square'
multidrizzle.final_scale = 0.0455 # PC detector pixel scale
multidrizzle.final_pixfrac = 1.0
multidrizzle.final_rot = 0.0 # rotate north up
multidrizzle.final_fillval = 0.0 # zero or INDEF
multidrizzle.final_bits = 0
Inspect your output and iterate as needed
Since flagged detector artifacts cannot be rejected from undithered datasets,
you may want to set the final_bits to include some flagged pixels,
rather than having them replaced by the fill value (final_fillval).
Or you can set final_fillval=INDEF to include all flagged pixels "as is".
Look for under-rejection of cosmic rays, or over-rejection of real features
(e.g. stellar cores) by blink-comparing the output drizzled image and weight map
(drz_sci.fits and drz_weight.fits). You may need to adjust your rejection
thresholds (driz_cr_snr), or grow the rejections and/or reject CTE tails
(driz_cr_grow and driz_cr_ctegrow).
Send any questions or concerns to the STScI Help Desk (help@stsci.edu).
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