SALSA

SALSA: A Python Package for Constructing Synthetic Quasar Absorption Line Catalogs from Astrophysical Hydrodynamic Simulations - Published in JOSS (2020)

https://github.com/biboyd/salsa

Science Score: 95.0%

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

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 5 DOI reference(s) in README and JOSS metadata
  • Academic publication links
    Links to: joss.theoj.org, zenodo.org
  • Committers with academic emails
    2 of 8 committers (25.0%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
    Published in Journal of Open Source Software

Scientific Fields

Mathematics Computer Science - 84% confidence
Last synced: 6 months ago · JSON representation

Repository

Salsa is a Python package for constructing synthetic absorber catalogs from astrophysical hydrodynamic simulations

Basic Info
  • Host: GitHub
  • Owner: biboyd
  • License: bsd-3-clause
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 12.5 MB
Statistics
  • Stars: 4
  • Watchers: 2
  • Forks: 1
  • Open Issues: 4
  • Releases: 2
Created over 5 years ago · Last pushed over 3 years ago
Metadata Files
Readme License

README.md

SALSA

Build Status Documentation Status Binder DOI DOI

SALSA: Synthetic Absorption Line Surveyor Application is a Python tool that constructs synthetic absorber catalogs from hydrodynamic galaxy simulations. Salsa heavily utilizes yt to access simulation data and Trident to create light rays/sight lines and generate synthetic spectra.

Observational studies generate large absorber catalogs by studying the absorption line spectra of distant quasars, as their light passes through intervening galaxies. Salsa can generate similar catalogs from cosmological and galactic simulations, allowing research to study these simulations from an observers perspective. This can give new insights into the data as well as help facilitate comparisons and collaboration between simulations and observations.

Salsa allows us to dip into galactic simulations and start to chip away at the many unknowns of the universe

A JOSS paper was published for SALSA and we recommend reading it for an overview of the package and its possible uses. If you do use SALSA in a project we ask that you cite this paper.

For detailed information on how to install and run salsa, Read the Docs here

Install

If you have all the dependencies installed, you can use pip and run these commands to install the most stable version: ``` $ pip install astro-salsa $ python

import salsa If you want to install the latest development version and have all the dependencies installed, you can clone the repository and run these commands: $ git clone https://github.com/biboyd/SALSA.git $ cd SALSA $ pip install -e . $ python import salsa ``` Now you should be all set to code!

Installing dependencies

To help with installing dependencies, enivronment.yml is included in the repository. First, install conda Then you should be able to create a conda environment via: $ conda env create --file environment.yml $ conda activate salsa-env Note that you need gcc compiler installed (which it often already is on most machines). For a more detailed description see the installation guide which also includes tips if you want to install dependencies on your own.

Getting Started

For an annotated example go here. Or launch an interactive jupyter hosted on Binder here (note that the notebook may take some time to load as it generally has to build the repository).

If you want to explore on your own, the easiest way to get started is use salsa.generate_catalog(). This takes: * The simulation dataset * Number of light rays/sightlines to make * Directory to save those light rays * A list of ions * Some other optional parameters.
This creates a number light rays and then extracts absorbers for each ion. A pandas.DataFrame is returned with information about all the absorbers which can then be further analyzed.

Contributing Guidelines

All contributions are welcome! This is an open-source project, built on many other open-source projects. Contributing can take many forms including: contributing code, testing and experimenting, or offering ideas for different features.

If you are interested in contributing you can contact us directly at boyd.brendan@stonybrook.edu or add an issue on this Github page.

Owner

  • Name: Brendan Boyd
  • Login: biboyd
  • Kind: user

Physics grad student at Stony Brook University

JOSS Publication

SALSA: A Python Package for Constructing Synthetic Quasar Absorption Line Catalogs from Astrophysical Hydrodynamic Simulations
Published
August 26, 2020
Volume 5, Issue 52, Page 2581
Authors
Brendan I. Boyd
Department of Physics and Astronomy, Michigan State University
Devin W. Silvia
Department of Computational Mathematics, Science and Engineering, Michigan State University
Brian W. O'Shea
Department of Physics and Astronomy, Michigan State University, Department of Computational Mathematics, Science and Engineering, Michigan State University, National Superconducting Cyclotron Laboratory, Michigan State University
Jason Tumlinson
Space Telescope Science Institute, Department of Physics & Astronomy, Johns Hopkins University
Molly S. Peeples
Space Telescope Science Institute, Department of Physics & Astronomy, Johns Hopkins University
Nicholas Earl
Space Telescope Science Institute
Editor
Daniel S. Katz ORCID
Tags
astronomy simulation spectra

GitHub Events

Total
Last Year

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 504
  • Total Committers: 8
  • Avg Commits per committer: 63.0
  • Development Distribution Score (DDS): 0.31
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
boydbre1 b****1@m****u 348
biboyd b****6@g****m 134
boydbre1 4****1 7
Brendan Isaac Seaton Boyd b****1@d****i 5
Brendan Isaac Seaton Boyd b****1@d****i 4
Brendan Boyd b****1@d****i 3
Brendan Isaac Seaton Boyd b****1@d****i 2
Daniel S. Katz d****z@i****g 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 6
  • Total pull requests: 4
  • Average time to close issues: 3 days
  • Average time to close pull requests: 11 minutes
  • Total issue authors: 3
  • Total pull request authors: 3
  • Average comments per issue: 1.33
  • Average comments per pull request: 0.0
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 1
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • clairekope (3)
  • zpace (2)
  • olebole (1)
Pull Request Authors
  • biboyd (2)
  • dependabot[bot] (1)
  • danielskatz (1)
Top Labels
Issue Labels
Pull Request Labels
dependencies (1)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 34 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 1
  • Total maintainers: 1
pypi.org: astro-salsa

Synthetic absorber catalog generator from astrophysical simulations

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 34 Last month
Rankings
Dependent packages count: 7.3%
Forks count: 22.8%
Stargazers count: 25.1%
Average: 34.2%
Downloads: 47.2%
Dependent repos count: 68.5%
Maintainers (1)
Last synced: 6 months ago

Dependencies

environment.yml pypi
  • astropy ==3.2.3
  • gwcs ==0.10.0
  • spectacle *
  • specutils ==0.5.2
  • trident *
tests/requirements.txt pypi
  • matplotlib <=3.2.1 test
  • mpi4py * test
  • numpy ==1.16.6 test
  • pandas * test
  • pip * test
  • pytest * test
  • scipy * test
  • yt * test