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Data from HiTS (2015) to verify the performance of alert production in the LSST DM stack.
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ap_verify_hits2015

Data from HiTS (2015) to verify the performance of alert production in the LSST DM stack.

Contains DECam data from the HiTS (2015) fields Blind15A_26, Blind15A_40, and Blind15A_42.

Relevant Files and Directories

path description
raw Raw, compressed DECam fits images from the HiTS (2015) fields Blind15A_26, Blind15A_40, and Blind15A_42.
calib DECam master calibs and wtmaps from the 2015 HiTS campaign. No raw images. See below for filename information.
config Dataset-specific configs to help Stack code work with this dataset.
templates Butler repo containing coadded images intended to be used as templates.
repo A template for a Butler raw data repository. This directory must never be written to; instead, it should be copied to a separate location, and data ingested into the copy (this is handled automatically by ap_verify, see below). Currently contains the appropriate DECam _mapper file.
refcats Tarballs of Gaia and PS1 reference catalogs in HTM format for regions overlapping all three HiTS fields.
dataIds.list List of dataIds for use in running Tasks. Currently set to run all Ids.

Master calibration file names

Below are the different types of master calibration files in the calib directory:

  • fci: dome flat images
  • fcw: dome flat weight maps
  • zci: zero/bias images
  • zcw: zero/bias weight maps
  • ici: illumcor images

Git LFS

To clone and use this repository, you'll need Git Large File Storage (LFS).

Our Developer Guide explains how to setup Git LFS for LSST development.

Usage

ap_verify_hits2015 is designed to be run using ap_verify, which is distributed as part of the lsst_distrib package of the LSST Science Pipelines.

This dataset is not included in lsst_distrib and is not available through newinstall.sh. However, it can be installed explicitly with the LSST Software Build Tool or by cloning directly:

git clone https://github.com/lsst/ap_verify_hits2015/
setup -r ap_verify_hits2015

See the Science Pipelines documentation for more detailed instructions on installing datasets and running ap_verify.

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