dc2_stellar_masks

https://github.com/lsstdesc/dc2_stellar_masks

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

✓
CITATION.cff file
Found CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
✓
.zenodo.json file
Found .zenodo.json file
✓
DOI references
Found 2 DOI reference(s) in README
✓
Academic publication links
Links to: zenodo.org
○
Academic email domains
○
Institutional organization owner
○
JOSS paper metadata
○
Scientific vocabulary similarity
Low similarity (7.7%) to scientific vocabulary

Last synced: 6 months ago · JSON representation ·

Repository

Basic Info

Host: GitHub
Owner: LSSTDESC
Language: Jupyter Notebook
Default Branch: main
Size: 3.77 MB

Statistics

Stars: 0
Watchers: 6
Forks: 1
Open Issues: 2
Releases: 2

Created about 2 years ago · Last pushed 7 months ago

Metadata Files

Readme Citation Zenodo

DC2 stellar masks package

This package was developped in the need to construct masks that covers regions where high luminosity of stars affects detected objects and the images in the DC2 context. This work is highly based on Zilong Du's work during his thesis, but also on HSC SSP article.

It is subdivided in 3 modules :

I) call_dc2

It opens the sample you want based on - the name of the catalog you ask for (must be a Catalog avaible in GCR except for the binstar method which only require a catalog). - some selection criterias of your will : general criteria applied to every catalog = conditions, criteria applied to 'galaxies' = conditionsgalaxies, criteria applied to 'stars' = conditions_stars

II) radius_study

As we only want to mask regions affected by the luminosity of the star, we mask a circle around each star within a radius defined as the radius for which the density of clusters in the circle over the mean density of the tract is inferior to a given value called critical_density. This value is customizable in the config file.

III) generate_masks

Here we use the results from 2) and the catalog from 1) to generate a healsparse map which contains the masks. One can chose to save them in a healpix format which is not optimized for high resolution maps.

Note:

Future version of the module might allow one to perform masks on catalogs which are not in GCR

Requirements:

Healsparse v1.9.0 GCRCatalogs v1.4.0

Owner

Name: LSST Dark Energy Science Collaboration (DESC)
Login: LSSTDESC
Kind: organization

Website: http://lsstdesc.org
Repositories: 310
Profile: https://github.com/LSSTDESC

Citation (CITATION.cff)

cff-version: 1.1.0
message: "If you use this software, please cite it as below."
authors:
- family-names: Amouroux 
  given-names: Nathan
  orcid: https://orcid.org/0009-0006-8186-0652
title: "LSSTDESC/DC2_stellar_masks: First DC2 stellar objects release"
version: v1.0.0
doi: 1.5281/zenodo.10986499
date-released: 2024-04-17
url: "https://github.com/LSSTDESC/DC2_stellar_masks/"

ecosyste.ms

Data

Tools

Indexes

Applications

Experiments

Open Source Science