MDAGTBLS(1)

💖 mDAGTbls — the manual, but make it make sense 💖

okay bestie, so this is mDAGTbls(1) from the Montage suite, and I'm gonna walk you through it like we're texting at 2am. it's giving "niche but iconic". let's go ✨

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🌸 NAME 🌸

mDAGTbls — build tables of projected</> and background corrected</> images. that's the whole vibe, no cap.

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🦋 SYNOPSIS 🦋

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

five arguments, five besties, one command. slay.

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✨ DESCRIPTION ✨

so mDAGTbls is primarily a utility for mDAG. like, that's its whole main character moment.

in normal Montage processing, you can just build your support files as you go, lowkey chill: retrieve a set of images from an archive, then make a list of the images you retrieved; reproject the images, then make a list of the successfully reprojected images; etc. one step at a time, vibes only. 💅

but bestie. if you wanna support a workflow manager that 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). that's the difference. planning ahead = main character energy.

and you don't have to be completely right — some overlaps may end up empty, 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). and mOverlaps can build the difference list from the raw list. team effort fr fr 🫶

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

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🎀 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. it's the "we have options" list 💅
• region.hdr — a FITS header template file. this is used to determine the region of interest for this run. it's basically the vibe check for where we're looking. ✨
• 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.

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🌈 RESULT 🌈

if successful, the three output image lists will be created. iconic. 👑

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. yes bestie, the names match on purpose. don't come for me.

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💀 MESSAGES 💀

the error messages, aka the "we need to talk" texts. here's every single one:

• 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

if you see one of these, that's not a slay. that's a 😭.

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🍓 EXAMPLES 🍓

here's what it actually looks like in the wild:

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

count="48", total="48" — we ate and left no crumbs. 🔥

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🙈 BUGS 🙈

okay bestie, sit down, this part is important:

• the drizzle algorithm has been implemented but has not been tested in this release. it's giving "we wrote it, we don't know". 💀
• 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"]. windows line endings betraying us again, classic. 😭
• 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. so 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. also: 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). periodt. 💅

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👑 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. respect the elders fr fr 🫶

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that's the whole page bestie!! Montage 5, dated Dec 2016 — yeah she's a little vintage but she still serves 💖✨🎀 hope this helped, go build those tables, you got this 🌸🦋💜