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GALFITools: a library for GALFIT #220

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canorve opened this issue Dec 7, 2024 · 2 comments
Open
20 of 32 tasks

GALFITools: a library for GALFIT #220

canorve opened this issue Dec 7, 2024 · 2 comments

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@canorve
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canorve commented Dec 7, 2024

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
Editor: TBD
Reviewer 1: TBD
Reviewer 2: TBD
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.

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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.

@SimonMolinsky
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SimonMolinsky commented Dec 9, 2024

Editor in Chief checks

Hi there! Thank you for submitting your package for pyOpenSci
review. Below are the basic checks that your package needs to pass
to begin our review. If some of these are missing, we will ask you
to work on them before the review process begins.

Please check our Python packaging guide for more information on the elements
below.

  • Installation The package can be installed from a community repository such as PyPI (preferred), and/or a community channel on conda (e.g. conda-forge, bioconda).
    • The package imports properly into a standard Python environment import package.
  • Fit The package meets criteria for fit and overlap.
  • Documentation The package has sufficient online documentation to allow us to evaluate package function and scope without installing the package. This includes:
    • User-facing documentation that overviews how to install and start using the package.
    • Short tutorials that help a user understand how to use the package and what it can do for them.
    • API documentation (documentation for your code's functions, classes, methods and attributes): this includes clearly written docstrings with variables defined using a standard docstring format.
  • Core GitHub repository Files
    • README The package has a README.md file with clear explanation of what the package does, instructions on how to install it, and a link to development instructions.
    • Contributing File The package has a CONTRIBUTING.md file that details how to install and contribute to the package.
    • Code of Conduct The package has a CODE_OF_CONDUCT.md file.
    • License The package has an OSI approved license.
      NOTE: We prefer that you have development instructions in your documentation too.
  • Issue Submission Documentation All of the information is filled out in the YAML header of the issue (located at the top of the issue template).
  • Automated tests Package has a testing suite and is tested via a Continuous Integration service.
  • Repository The repository link resolves correctly.
  • Package overlap The package doesn't entirely overlap with the functionality of other packages that have already been submitted to pyOpenSci.
  • Archive (JOSS only, may be post-review): The repository DOI resolves correctly.
  • Version (JOSS only, may be post-review): Does the release version given match the GitHub release (v1.0.0)?

  • Initial onboarding survey was filled out
    We appreciate each maintainer of the package filling out this survey individually. 🙌
    Thank you authors in advance for setting aside five to ten minutes to do this. It truly helps our organization. 🙌


Editor comments

@canorve I've checked your package and have two issues that should be addressed before we assign the editor and reviewers:

  1. You have provided documentation, but I see only raw rst files. Have you built docs somewhere? Do you have a link to the build docs? Here is the guide that might help you: https://www.pyopensci.org/python-package-guide/documentation/hosting-tools/intro.html
  2. Are your tests automated? Have you considered using GitHub Actions for this? Here's an example of how to set up automated tests: https://www.pyopensci.org/python-package-guide/tests/tests-ci.html

We will go forward with the review when you address those two points!

@SimonMolinsky
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@canorve

Here are my comments:

I've checked your package and have two issues that should be addressed before we assign the editor and reviewers:

  1. You have provided documentation, but I see only raw rst files. Have you built docs somewhere? Do you have a link to the build docs? Here is the guide that might help you: https://www.pyopensci.org/python-package-guide/documentation/hosting-tools/intro.html
  2. Are your tests automated? Have you considered using GitHub Actions for this? Here's an example of how to set up automated tests: https://www.pyopensci.org/python-package-guide/tests/tests-ci.html
    We will go forward with the review when you address those two points!

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