man mDAGTbls (1): 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.