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.

Montage 5                                           Dec 2016                                         MDAGTBLS(1)