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The LSST Stack provides many capabilities for processing images, and creating and analyzing astronomical catalogs. The LSST Stack is currently able to process images as produced by the LSST Image Simulator, as well as data from the Subaru/Hyper Supreme-Cam and from SDSS. Explicit support for other cameras may be added in the future. Most of the following examples can be run with only a binary installation, although the most challenging examples require both a full install from source and the creation of python tasks to use the underlying libraries. In some cases it will be necessary to download or create data for processing.

 

In This Chapter

Preliminaries

Load the LSST Environment

You must have the LSST Stack installed on your system (see LSST Stack Installation) to proceed. The commands listed in the code blocks below primarily assume you are using the bash shell; analogous commands for (t)csh should work as well. If you have not already done so, load the LSST environment:

source $INSTALL_DIR/loadLSST.bash          # bash users

where $INSTALL_DIR is the directory where the LSST Stack was installed. 


Setup Packages

Use the eups setup command to enable the packages you intend to use, which likely includes the LSST pipelines.  You should typically specify a version tag to ensure that all enabled packages are consistent.

setup -T v11_0 pipe_tasks
setup -T v11_0 obs_sdss --keep     # to process SDSS data
setup -T v11_0 obs_lsstSim --keep  # to process LSST Sims

To assure stability in your stack, you may save exactly which versions you are using for subsequent setups to a file. If the stack is later updated you can continue using the older versions. If you fail to do this you may find that your procedures stop working.  But if you are just using a released version tag (or any other tag) with no customized versions, this is probably overkill.

eups list -s >myversions   # save the set of versions to "myversions"
setup -m myversions        # to restore the saved versions 

Note that the available command-line options for resident tasks of packages that have been "setup" can be invoked with the -h or --help switch on the command line. 

Tutorial Scripts

Some of the tutorials provide scripts, configuration files, or other information that you will need to exercise the examples. These have been collected in a tutorials package in the LSST Code Repositories, which you fetch with: 

git clone https://github.com/lsst-dm/tutorials.git

Processing Tutorials

The following tutorials illustrate how to use the LSST Stack for processing images, and (eventually) how to craft your own simple pipelines using software components from the Stack.

Basic LSST Demo

This first, very simple example is used to verify the proper installation of the LSST Stack. See Testing the Installation

Process a Single File on Disk

The next simple tutorial shows how to process a single image and generate a catalog of detected sources. See Processing a Single Image File

Process PhoSim Images

This next, more complicated example shows how to generate LSST image simulations using the PhoSim software, followed by image processing and catalog generation. See the PhoSim processing tutorial for details. 

Process SDSS Stripe 82 Images

The SDSS images from Stripe 82 have been used in Data Release Productions to test scientific performance of the LSST Stack. The standard DRP (lite) processing is quite involved: see the SDSS processing tutorial

Analysis with the Stack

Example Queries on Output Catalogs

Once images are processed, analysis of the resulting output catalog(s) is a logical next step. The catalog query examples can be customized to your science needs. 

Custom Analysis

The LSST Stack includes a base of algorithmic code that is well suited to image and catalog analysis. Some of the Science Data Quality Assurance tasks are based on it. For a quick introduction to the capabilities, see the on-line tutorials by Chris Walter (Duke Univ.) of the DESC. The notebooks are the following: 

Note that these notebooks can be edited (e.g. if you see something out of date), and new additions are welcome.

 

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