For the Kitt Peak data, we need to remove the pupil ghost using
MSCred's task rmpupil, using a ghost pupil that we create from
the flattened data.
The rmpupiltask will guess a scaling, and we adjust it interactively
until we're happy.
PACKAGE = mscred TASK = rmpupil input = @u List of input mosaic exposures output = @u//p List of output mosaic exposures template= Upup.fits Template mosaic exposure (type = difference) Type of removal (extname= im) Extensions for fit (blkavg = 8) Block average factor (fudge = 1.6) Fudge factor (scale = INDEF) Scale (INDEF for automatic estimate) (interac= yes) Interactive? (mscexam= no) Examine corrections with MSCEXAM? (verbose= yes) Verbose output? newscale= 0. Scale (0=done, -1=abort, -2=new blkavg) newblk = 8 New block average factor (fd1 = ) (fd2 = ) (fd3 = ) (mode = ql)
The newer versions of rmpup (V4.8) no longer appear to be interactive, and instead use some new-fangled "mask" philosophy to identify objects/bad columns. I have no idea what this means, and of course there's no documentation. I tried running the code "blind" and at least on simple frames the ghost removal appears to be perfect. That's progress, I guess. Fortunately, the OLD version of rmpupil is still there, as irmpupil .
input = @all List of input images output = @all//p List of output corrected images pupil = pupI.fits Pupil or list of pupil patterns masks = List of object/bad data masks (pupilma= ) Pupil masks (outtype= sdiff) Output type (ncblk = 5) Column smoothing (nlblk = 5) Line smoothing (extfit = im) Extensions to use in scaling fit (logfile= ) Logfile (verbose= yes) Verbose? (mode = ql)