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wiki:LargeScaleMaskingAnalysis

Large-Scale Masking Analysis

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How can we convert the masks generated for each image into a resource which helps people to determine the filling factor of their particular science? Here are some thoughts:

  • we generate a mask image with each processed science exposure. These are also warped with the image pixels to skycells. The masks are compressed, and thus small (1% of the image data volume).
  • we ingest exposures into a DVO database, and that is made available to people for their studies.
  • anyone who cares only about a specific object or small area can always request the relevant masks from the postage stamp server
  • The total data volume of per-exposure masks generated to date is in the vicinity of 2TB.
  • Option 1) set up a distribution system for all masks to provide all masks to those who so desire.
    • this scheme, or others below, could use Mario Juric proposed mask compression tool to further reduce the volume.
  • Option 2) set up an analysis stage which generates binned mask images on various scales
    • this system could start with the warped skycell masks
    • these masks could be combined into a lower resolution set of super-skycells
    • a static-sky worth of masks at full resolution should require ~200GB per filter
    • binning by 5x5 (1 arcsec pixels) gets us to the 10GB range.
    • what scales should be generated?
  • Option 3) set up a system to rebin and distribute the masks, to reduce the volume of data I/O
Last modified 15 years ago Last modified on Dec 8, 2010, 3:44:10 PM
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