NAME

       mDAGTbls - Construct tables of projected and background corrected images

SYNOPSIS

         mDAGTbls images.tbl region.hdr rimages.tbl pimages.tbl cimages.tbl

DESCRIPTION

         mDAGTbls is primarily a utility for mDAG.  In normal Montage processing,
         one can build support files as you go: retrieve a set of images from an
         archive, then make a list of the images retrieved; reproject the images, then
         make a list of the successfully reprojected images; etc.

         To support a workflow manager which plans processing using an up-front
         Directed Acyclic Graph (DAG) you need to have pre-determined all of this,
         plus which image will overlap (for background matching).  You don't have
         to be completely right (some overlaps may end up empty or some images may
         have no real data in the region of interest) but you need to build a complete
         superset.  mDAGTbls does part of this.  Based on a raw image list, it
         determines as best it can the image lists (raw images in the region of
         interest from larger list of images we have, projected and corrected lists
         from that). mOverlaps can build the difference list from the raw list.

         We document this here since the same analysis may be of use for planning
         other than in mDAG.

ARGUMENTS

       images.tbl

                The   set   of   images   we   have.    For   instance,   a   set   download  via
              mArchiveList/mArchiveGet
                and often a superset of what we are interested in for a specific mosaic.

       region.hdr

                A FITS header template file.  This is used to determine the region of interest
                for this run.

       rimages.tbl

                The "raw" (input) image we will use in this run.

       pimages.tbl

                The corresponding projected image list.

       cimages.tbl

                The corresponding background-corrected image list.

RESULT

         If successful, the three output image lists will be created. NOTE: It is assumed
         that the actual raw, reprojected and background-corrected images will be kept in
         separate directories, so the file names in these tables are identical.

MESSAGES

       ERROR  Cannot open status file: filename

       ERROR  Invalid image metadata file: tblfile

       ERROR  Not enough information to determine coverages (CDELTs or CD matrix)

       ERROR  Need columns: cntr ctype1 ctype2 nl ns crval1 crval2 crpix1  crpix2  cdelt1  cdelt2
              crota2 fname (equinox optional)

       ERROR  Invalid output metadata file: tblfile

       ERROR  Bad WCS for image integer

       ERROR  Output wcsinit() failed.

       ERROR  general error message

EXAMPLES

       mDAGTbls images.tbl region.hdr rimages.tbl pimages.tbl cimages.tbl
              [struct stat="OK", count="48", total="48"]

BUGS

       The drizzle algorithm has been implemented but has not been tested in this release.

       If  a  header  template  contains  carriage  returns  (i.e., created/modified on a Windows
       machine), the cfitsio library will be unable to read it properly, resulting in the  error:
       [struct stat="ERROR", status=207, msg="illegal character in keyword"]

       It  is  best  for the background correction algorithms if the area described in the header
       template completely encloses all of the input images in their entirety. If parts of  input
       images  are  "chopped  off"  by  the  header  template,  the background correction will be
       affected. We recommend you use an expanded header  for  the  reprojection  and  background
       modeling  steps, returning to the originally desired header size for the final coaddition.
       The default background matching assumes that there are no non-linear background variations
       in  the  individual  images  (and  therefore  in the overlap differences). If there is any
       uncertainty in this regard, it is safer to turn on the "level  only"  background  matching
       (the "-l" flag in mBgModel.

COPYRIGHT

       2001-2015 California Institute of Technology, Pasadena, California

       If  your  research  uses  Montage,  please  include  the  following acknowledgement: "This
       research made use of Montage. It is funded by the National Science Foundation under  Grant
       Number  ACI-1440620,  and  was  previously  funded  by  the National Aeronautics and Space
       Administration's Earth Science Technology Office, Computation Technologies Project,  under
       Cooperative  Agreement  Number  NCC5-626  between  NASA  and  the  California Institute of
       Technology."

       The Montage distribution includes an adaptation of the MOPEX algorithm  developed  at  the
       Spitzer Science Center.