Skip to content

GALFITools: a library for GALFIT #220

Open
@canorve

Description

@canorve

Submitting Author: (@canorve)
All current maintainers: (@canorve)
Package Name: GALFITools
One-Line Description of Package: A library for efficient data processing customized for the GALFIT package
Repository Link: https://github.com/canorve/GALFITools
Version submitted: v1.15.0
EiC: @SimonMolinsky, @coatless
Editor: @hamogu
Reviewer 1: @Jammy2211
Reviewer 2: @ tepickering
Archive: TBD
JOSS DOI: TBD
Version accepted: TBD
Date accepted (month/day/year): TBD


Code of Conduct & Commitment to Maintain Package

Description

  • Include a brief paragraph describing what your package does:

GALFIT, a well-established two-dimensional image fitting algorithm (Peng et al. 2002, AJ, 124, 266), is integral to precise modeling of galaxy surface brightness in astronomical images. To optimize GALFIT's utility, GALFITools provides a suite of Python routines that streamline input and output parsing for enhanced efficiency and usability.

Scope

  • Please indicate which category or categories.
    Check out our package scope page to learn more about our
    scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):

    • Data retrieval
    • Data extraction
    • Data processing/munging
    • Data deposition
    • Data validation and testing
    • Data visualization1
    • Workflow automation
    • Citation management and bibliometrics
    • Scientific software wrappers
    • Database interoperability

Domain Specific

  • Geospatial
  • Education

Community Partnerships

If your package is associated with an
existing community please check below:

  • For all submissions, explain how and why the package falls under the categories you indicated above. In your explanation, please address the following points (briefly, 1-2 sentences for each):

GALFITools enhances functionality with a range of features, including mask creation, PSF generation, initial parameter estimation, galaxy image model visualizaton, multigaussian expansion (MGE) fitting, and calculation of sky background along with other key photometric parameters.

  • Who is the target audience and what are scientific applications of this package?
    This a tool for astronomers to streamline image data processing and enhance interpretation of GALFIT outputs

  • Are there other Python packages that accomplish the same thing? If so, how does yours differ?
    No, similar tools act as GALFIT wrappers but focus on different objectives, such as automating GALFIT for large galaxy samples.

  • If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted:

#216

Technical checks

For details about the pyOpenSci packaging requirements, see our packaging guide. Confirm each of the following by checking the box. This package:

  • does not violate the Terms of Service of any service it interacts with.
  • uses an OSI approved license.
  • contains a README with instructions for installing the development version.
  • includes documentation with examples for all functions.
  • contains a tutorial with examples of its essential functions and uses.
  • has a test suite.
  • has continuous integration setup, such as GitHub Actions CircleCI, and/or others.

Publication Options

JOSS Checks
  • The package has an obvious research application according to JOSS's definition in their submission requirements. Be aware that completing the pyOpenSci review process does not guarantee acceptance to JOSS. Be sure to read their submission requirements (linked above) if you are interested in submitting to JOSS.
  • The package is not a "minor utility" as defined by JOSS's submission requirements: "Minor ‘utility’ packages, including ‘thin’ API clients, are not acceptable." pyOpenSci welcomes these packages under "Data Retrieval", but JOSS has slightly different criteria.
  • The package contains a paper.md matching JOSS's requirements with a high-level description in the package root or in inst/.
  • The package is deposited in a long-term repository with the DOI:
    https://zenodo.org/records/13994492

Note: JOSS accepts our review as theirs. You will NOT need to go through another full review. JOSS will only review your paper.md file. Be sure to link to this pyOpenSci issue when a JOSS issue is opened for your package. Also be sure to tell the JOSS editor that this is a pyOpenSci reviewed package once you reach this step.

Are you OK with Reviewers Submitting Issues and/or pull requests to your Repo Directly?

This option will allow reviewers to open smaller issues that can then be linked to PR's rather than submitting a more dense text based review. It will also allow you to demonstrate addressing the issue via PR links.

  • Yes I am OK with reviewers submitting requested changes as issues to my repo. Reviewers will then link to the issues in their submitted review.

Confirm each of the following by checking the box.

  • I have read the author guide.
  • I expect to maintain this package for at least 2 years and can help find a replacement for the maintainer (team) if needed.

Please fill out our survey

P.S. Have feedback/comments about our review process? Leave a comment here

Editor and Review Templates

The editor template can be found here.

The review template can be found here.

Footnotes

  1. Please fill out a pre-submission inquiry before submitting a data visualization package.

Metadata

Metadata

Assignees

No one assigned

    Labels

    Type

    No type

    Projects

    Status

    under-review

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions