Skykatana is a pacakge to create and maniputate boolean spatial masks on the celestial sphere, by combining healsparse pixel maps accounting for various effects such as cutting out regions around bright stars, low depth, bad seeing, extended sources, among others. We call these partial maps stages, which are then combined into a final mask.
For each stage you can generate random points, quickly visualize masks, do plots overlaying bright stars, and apply the mask to an arbitrary catalog to select sources located inside.
Although mainly designed to work with the HSC-SSP survey, it is flexible to accomodate other surveys such as the upcoming half-sky dataset of the Vera Rubin Observatory.
SkyMaskPipe()Main class for assembling and handling pixelized masks
build_footprint_mask(), build_patch_mask(), build_holes_mask(), etc--> Generate maps for each stagecombine_mask()--> Merge the maps created above to generate a final maskplot()--> Visualize a mask stage by plotting randoms. Options to zoom, oveplot stars, etc.plot2compare()--> Compare input sources on the left and a mask stage on the rightmakerans()--> Generate randoms over a mask stageapply()--> Cut out sources outside of a given mask stage
There are two ways to get skykatana:
pip install skykatana- Clone the repo, switch to the pacakge directory and do
pip install .. This has the advantage that you will get the latest version and all the files in /example_data (~210 MB)
- A quick introductory notebook is availables here
- An indepth tutorial notebook can be found here
- The full documentation is available here
- Main author: Emilio Donoso
- Contributors: Mariano Dominguez, Claudio Lopez, Konstantin Malanchev
This software was partially developed with the generous support of the LINCC Frameworks Incubator Program using LINCC resources. The healsparse code was written by Eli Rykoff and Javier Sanchez