John Doty wrote: > The problem: > > I have a bunch of image files in FITS format. For each raster row in > each file, I need to determine the median pixel value and subtract it > from all of the pixels in that row, and then write out the results as > new FITS files. >
This may be personal bias... I have spent a few years with FITS files so every time I see 'FITS' I think 'astronomy' - maybe you are doing something else. (Someone wrote he does not know what FITS is - see fits.gsfc.nasa.gov In a nutshell: FITS file is a list of header-data units. Each header is text containing optional keyword-value pairs and reading instructions for the data unit. Usually astronomical image data but it can be anything.) Sounds like subtracting sky background from the frames, though for some reason (speed?) column-wise. You could have a look at either PyRAF (www.stsci.edu/resources/software_hardware/pyraf) or PyMidas (www.eso.org/sampo/pymidas/). Running some semi-official sky-subtraction algorithm would at least give you a good case to test against. You could also check if ftools already does this. I have not used it much, but sometimes it saves huge amounts of coding time. heasarc.gsfc.nasa.gov/docs/software/ftools/ftools_menu.html > This is a real problem I need to solve, not a made-up toy problem. I was > originally thinking of solving it in C (I know where to get the pieces > in that language) Could you tell a bit more of the data? Are you aiming for accuracy, speed or getting as complete time series as possible? (for me, speed has never been an issue) Photometry/astrometry/something else? Is there some trade-off like "get best possible result in X seconds"? -- Juho Schultz -- http://mail.python.org/mailman/listinfo/python-list
