astrocompress: A Python repository from profjsb

Getting the data from sources

Setup

You'll need a modern unix-like environment (with git and git-lfs) where Anaconda can be installed:

wget https://repo.anaconda.com/archive/Anaconda3-2024.02-1-Linux-x86_64.sh
sh Anaconda3-2024.02-1-Linux-x86_64.sh

(First time only) Get this repo and clone the conda environment:

git clone https://github.com/profjsb/astrocompress.git
cd astrocompress
mkdir -p data/integer/imaging/sci/
conda env create --file astrocompress.yaml

Activate the environment:

conda activate astrocompress

Download the SDSS Data Cubes

You'll need to get the large CSV containing the list of the SDSS data fields:

cd sources/SDSS
git lfs pull --include "Stripe82Fields.csv"

Now get a sample of cubes. For example:

python ./make_sdss_cubes.py  -m None --size="(800,800)" --random_state=42 -n 2

See the documentation in make_sdss_cubes.py for command-line arguments.

Download the Keck data

cd sources
python download.py

This will do a trial run. To pull all the data:

python download.py --full

Keck Observatory Archive (KOA)

Link: https://koa.ipac.caltech.edu/

Description: this is ground based imaging a spectroscopy data from a variety of telescopes on the world's largest optical/infrared telescope.

Acknowledgements: This research has made use of the Keck Observatory Archive (KOA), which is operated by the W. M. Keck Observatory and the NASA Exoplanet Science Institute (NExScI), under contract with the National Aeronautics and Space Administration.