The gmos.gifringe task would be used to construct the fringe frame, and the gmos.girmfinge task would scale and remove the pattern from science images. This pattern is derived from many low-background science images (with very few extended targets) by masking the targets and combining many dithered (preferably, non-overlapping) images that have been flat-fielded. gireduce Processing Flag Defaults ¶Īppend MDF extension? Not applicable to imaging.Īll of the processing steps below can be performed from the work directory on the lists of files constructed above, using the IRAF notation.Ī fringe pattern may be apparent in the extreme red ( i-band) for some CCDs. The gireduce task has more than 50 parameters the table below lists the defaults for the processing flag keywords-i.e., the keywords with logical values to indicate whether to perform an operation.įor the most part you can use the default parameter values exceptions are noted explicitly in the code blocks below. See Creating Master Reference Files to create the other MasterCals. See Bad Pixel Masks for the location of the appropriate BPM files. If you are concerned about the applicability of flat-field exposures taken weeks apart from the corresponding science exposures, it is simple to alter the date condition above and build more customized Flat-field MasterCals.īasic image reductions are performed by the gireduce task, using the Static BPM, Bias and Flat-field MasterCal files. # Note: IRAF refers to the OBJECT keyword with the special name: "i_title" s1 = "i_title?='Twilight' & obsclass?='da圜al' " # Flat-fields must also match the RoI, CCD binning, grating and aperture: s2 = "& detro1ys>1024 & ccdsum?='2 2' & grating?='MIRROR' & maskname?='None' " # Select flats obtained contemporaneously with the observations string date date = "& > '' & "flt_tmp.txt") gemextn (, omit = omit, outfile = "flat_r.txt" ) #.and so on for each filter. (1981) FITS: A flexible image transport system, Astronomy & Astrophysics Supplement, 363.Cd / path / to / work_directory / raw # Bias exposures with a common observation class, RoI, and CCD binning: s1 = "obstype?='BIAS' & obsclass?='da圜al' & detrO1ys>1024 & ccdsum?='2 2'" # Select bias exposures within a few weeks of the target observations: s2 = "& > '' & "bias_tmp.txt" ) string omit = "exten,index,kernel" gemextn (, omit = omit, outfile = "biasFiles.txt" ) # Flat-fields must match: Object, RoI, CCD binning, grating & aperture. 25, Astronomical Society of the Pacific, San Francisco, p. (1991) The ESO-MIDAS System: Astronomical Data Analysis Software and Systems I, PASP Conf. (1993) DAOPHOT: A computer program for crowded-field stellar photometry, Pub. 2 (1988) Rutherford Appleton Laboratory, Chilton, U. (1982) Maximum likelihood reconstruction for emission tomography, IEEE Trans. (1994) The many hues of astronomical color imaging, CCD Astronomy, 1(2). (1972) Bayesian-based iterative method of image restoration, J. (1995) Pixon-based multiresolution image reconstruction and the quantification of picture information content, Journal of Imaging Systems and Technology, 6, 314–331. (1974) An iterative technique for the verification of observed distributions, Astronomical Journal, 79, 745–754. (1999) Quantified Maximum Entropy MemSys5 User’s Manual V1.2, Maximum Entropy Data Consultants, Bury St. (1994) An overview of the Astrophysics Data System, Experimental Astronomy, 5, 205. (1996) SExtractor: Software for source extraction, Astronomy & Astrophysics Supplement, 117, 393–404.Įichhorn, G.
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