No way to reject outlierss in doing overscan fit

[mwcraig]

As reported by @tapio-not:

I encountered a new issue with the astropy/ccdproc, specifically subtract_overscan.

The "problem" is that the data I have has occasional bad first line with values of 4e9 instead of about 10 000 (ADU). This is a CCD-controller issue, so I just have to live with that.

So, if I fit " models.Polynomial1D(1)" this fails because I have not found "sigma clipping" option in this "task" as with iraf/ccdproc there is "Low and high sigma rejection factors for rejecting deviant points from the overscan fit."

Of course I can replace the 4e9 values with something smaller, but much more elegant solution would be to have "sigma clipping" while fitting the data. I guess that using "NDData uncertainty" could do the job, but I'm not familiar enough with that and anyway this might be an overkill in comparison to reject one/few points from a fit.