Documentation on tvcln

Task: tvcln
Purpose: Clark/Steer CLEAN with display of intermediates
Categories: deconvolution

        TVCLN is a MIRIAD task, which performs a hybrid Clark/Steer Clean
        algorithm, which takes a dirty map and beam, and produces an output
        map which consists of the Clean components. This output can be
        input to SELFCAL to self-calibrate visibilities, or input to RESTOR
        to produce a "clean" image. Optionally CLEAN can take as one of
        its inputs a model of the deconvolved image. This model could be
        from a previous CLEAN run, or from any of the other deconvolution
        tasks (e.g. MAXEN). 

Key: map
        The input dirty map, which should have units of Jy/beam. No
        default. 

Key: beam
        The input dirty beam. No default

Key: model
        An initial model of the deconvolved image. This could be the
        output from a previous run of CLEAN, or the output of any of the
        deconvolution tasks (e.g. MAXEN). It must have flux units of
        Jy/pixel. The default is no model (i.e. a zero map). 

Key: out
        The name of the output map. The units of the output will be
        Jy/pixel. It can be input to RESTOR, CLEAN (as a model, to do
        more cleaning), or to SELFCAL (for self-calibrating visibility
        data). 

Key: gain
        The minor iteration loop gain. Default is 0.1.

Key: cutoff
        CLEAN finishes when the absolute maximum residual falls below
        CUTOFF. Default is 0. 

Key: niters
        The maximum number of minor iterations. Clean finishes when
        abs(NITERS) minor iterations have been performed. Clean may finish
        before this point, however, if NITERS is negative and the absolute
        maximum residual becomes negative valued, or if the cutoff level
        (as described above) is reached. 

Key: region
        This specifies the region to be Cleaned.

Key: phat
        Cornwells prussian hat parameter. When cleaning extended sources,
        CLEAN may produce a badly corrugated image. This can be suppressed
        to some extent by cleaning with a dirty beam which has had a spike
        added at its center (i.e. a beam that looks like a prussian hat).
        PHAT gives the value of this spike, with 0 to 0.5 being good
        values. Default is 0 (but use a non-zero value for extended
        sources). 

Key: minpatch
        The minimum patch size when performing minor iterations. Default
        is 51, but make this larger if you are having problems with
        corrugations. You can make it smaller when cleaning images which
        consist of a pretty good dirty beam. 

Key: speed
        This is the same as the speed-up factor in the AIPS APCLN.
        Negative values makes the rule used to end a major iteration more
        conservative. This causes less components to be found during a
        major iteration, and so should improve the quality of the Clean
        algorithm Usually this will not be needed unless you are having
        problems with corrugations. A positive value can be useful when
        cleaning simple point-like sources. Default is 0. 

Key: mode
        This can be either "hogbom", "clark", "steer" or "any", and
        determines the Clean algorithm used. If the mode is "any", then
        CLEAN determines which is the best algorithm to use. The default
        is "any". 

Key: clip
        This sets the relative clip level in a Steer clean, values
        typically being 0.75 to 0.9. The default is image dependent. 

Key: server
        If this is set to the name of a TV device, then at the end of
        each major cycle, the restored image is displayed on the TV.