In order to be able ingest images via the LSST pipeline you must first install the LSST pipeline.
Note LSST support is currently experimental. The LSST API is currently not finalised so using the latest version of the LSST pipeline may break the code. If in doubt try and use version 19, the last version this code was tested against.
To install the LSST pipeline please refer to https://pipelines.lsst.io/#installation. We recommend using Docker as the installation method for the LSST pipeline. The following instructions assume that Docker has been used to install the LSST pipeline.
To use run pawlikMorph-LSST with the LSST pipeline first mount the directory where the pawlikMorph-LSST code is stored (i.e the directory above pawlikMorphLSST/).
$ docker run -it -v `pwd`:/home/lsst/mnt lsstsqre/centos:7-stack-lsst_distrib-v19_0_0
Setup the LSST environment using which ever shell you are using (if in doubt try .bash)
$ source loadLSST.bash $ setup lsst_distrib
Next you need to change directory into the directory with the code and data
$ cd $ cd mnt/
Finally you need to install the dependacies that do not come with the LSST Docker image
$ pip install numba parsl scikit-image photutils
If everything was correctly installed then running
$ python imganalysis --help
Should output the help for the imganalysis script.
For more help on Docker https://docs.docker.com/get-started/.
Using the LSST databutler¶
Currently this code is only setup for reading in SDSS images using the LSST pipeline. The SDSS images must be available on the machine the script is running on. The folder structure for the SDSS images that the LSST pipeline expects is the same as found in http://das.sdss.org/imaging/, i.e . /path/to/data/756/41/corr/1/fpC-000756-r1-0234.fits etc. Where 756 must be the run number, 41 is the rerun number (must be greater than 40), and 1 is the camcol number.
The script expects a csv file passed via the –file flag with the following columns: ra, dec, run, rerun, camCol, and field. The only other difference for the user along with the different csv file, is to pass the LSST option to the –imgsource flag. Below is an example command for using the LSST pipeline:
$ python imganalysis.py --file sdssimgsinfo.csv --imgsource LSST -Aall -sersic -cas -n 4