GALAssify submission

[Malclay]

Submitting Author: Manuel Alcázar-Laynez (@Manalclay)
All current maintainers: (@Manalclay, @andonij)
Package Name: GALAssify
One-Line Description of Package: A Python package for visually classifying astronomical objects
Repository Link: https://gitlab.com/astrogal/GALAssify/
Version submitted: v1.0.1
EiC: Szymon Moliński (@SimonMolinsky )
Editor: Avik Basu (@ab93)
Reviewer 1: Akhil Krishna R (@akhilkrishnar0)
Reviewer 2: Erik Whiting (@erik-whiting)
Archive: TBD
JOSS DOI: TBD
Version accepted: TBD
Date accepted (month/day/year): TBD

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Description

• Include a brief paragraph describing what your package does:
  We present GALAssify, a customisable graphical tool that allows the user to visually inspect and characterise properties of astronomical objects in a simple way. GALAssify allows the user to save the results of the visual classification into a file using a list of previously defined tags based on the user's interests. A priori, it has been initially developed to tackle astrophysical problems but, due to its versatility, it could be easily adapted. For instance, this tool can be used to classify microscopy images from biological studies or be used in any other discipline.
  

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  Check out our package scope page to learn more about our
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  • Data retrieval
  • Data extraction
  • Data processing/munging
  • Data deposition
  • Data validation and testing
  • Data visualization¹
  • Workflow automation
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• Geospatial
• Education

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  GALAssify allows the user to visualise and validate a large dataset of astronomical images (or of any other field) using a Graphical User Interface (GUI) to accomplish it using only a keyboard, a mouse or both. User can view the image of the object and a linked FITS image at time, and visually classify it with a previously-defined tags, or even discard the object if required.

  • Who is the target audience and what are scientific applications of this package?
    This package is designed for astronomers who need to manually classify large numbers of astronomical objects given their respective images using customizable labels.

  • Are there other Python packages that accomplish the same thing? If so, how does yours differ?
    Currently, we don't know any customizable GUI-based tool specific for astronomical objects. The most similar tools can be ML generic dataset-creation GUI tools such as image-sorter2 or DataTurks, but their functionality is limited for our use case. For example, our tool can display both RGB and FITS images of the same object at time to perform a better classification. Also, our tool can be used without mouse interaction -- all its functionality can be accessed using keyboard shortcuts, which is a essential speed-up in the workflow when classifying large datasets.

  • 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:
    Presubmission Inquiry for GALAssify: A Python package for visually classifying astronomical objects #189

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

[Manalclay]

Dear pyOpenSci team,

I posted this submission with my other personal (non-scientific) GitHub account (@Malclay). I hope this won't be a problem. If so, please let me repost this submission with my scientific account (@Manalclay).

Thank you!

[hamogu]

Hi! Thanks for your submission @Manalclay! While we are waiting for our Editor-in-Chief to get started with the first look, I already wanted to ask you a question: I noticed that the purpose of your package is listed as "classifying astronomical objects" (though of course other science areas also look at images), so I thought that it might make sense to tick the "astropy" box under "partnerships", but I notice that you didn't do that. So I'm just checking if that's on purpose?

Any pyopensci package will be fully listed on pyopensci - astropy and pang are in addition, not instead of that. So, if your package deal with astronomical data, there really is no downside to also make it "astropy partnership" in this submission.

[hamogu]

Sorry, I just went back to #189 and saw that we already discussed this in #189 (comment) a few months ago. I'm sorry I forgot - please disregard my comment.

[SimonMolinsky]

Hi @Malclay !

I'm currently Editor-in-Chief, so I will start the review process. I need (max) one day for the initial check of your package. Expect the feedback tomorrow!

[Manalclay]

Hello again!

Sorry, I just went back to #189 and saw that we already discussed this in #189 (comment) a few months ago. I'm sorry I forgot - please disregard my comment.

No problem at all :) Thanks for check the presubmission!

Hi @Malclay !

I'm currently Editor-in-Chief, so I will start the review process. I need (max) one day for the initial check of your package. Expect the feedback tomorrow!

Take your time! Thanks for the fast response

[SimonMolinsky]

Editor in Chief checks

Hi there @Malclay ! Thank you for submitting your package for pyOpenSci
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---

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---

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Editor comments

Hi @Malclay !

I've performed initial checks of your package. It's rather uncanny to see the package using QT here, but I know that image classification tasks need to be done manually, and PyQT is one of the best options for GUI programs in Python. I think creating user-facing software is a very hard task, and I'm impressed by your work!

I've encountered a few problems, and here are these with links to the Gitlab issues:

1. Problems with the installation: https://gitlab.com/astrogal/GALAssify/-/issues/13
2. Why does documentation refer to installation directly from the repository when your package is published on PyPI?
3. I couldn't find API docs. Have you written API documentation? In this context, tool customization is your user-facing API. However, you must also provide internal documentation of the project methods and classes for contributors (see point 4).
4. Usually, the package we review should have maintenance workflows documented. This means you should assume that other contributors will eventually join your project. Thus, the package should have a Contributing File as well as some documentation describing low-level API for programmers (see point 3.) The CONTRIBUTING.md file is a bare minimum. I've created an issue here for this point: https://gitlab.com/astrogal/GALAssify/-/issues/14
5. The same as above for Code of Conduct.
6. Do you plan to submit your package to JOSS?

[Manalclay]

Hello @SimonMolinsky !

First of all, thank you very much for your words and for your revision, which we really appreciate.

My colleague @andonij and me are addressing the points you listed. Currently, we added the code of conduct and the CONTRIBUITNG.md file, which points to a new developer guide located inside the doc/ folder.

We are trying to replicate the reported installation issues. All the progress is being reported at the link of the issue you already opened. Also, we are working now on the lack of the API documentation, which is being written using docstrings, as suggested.

Answering to 6th point: A paper of the package was already submitted to JOSS (see the related issue). Unfortunately, it was rejected due it did not pass the substantial scholarly effort criterion. I would have like this package to be published to JOSS, but I understand that it does not match the requisites. The reviewer recommended me to submit it to pyOpenSci, That's why I'm here :) I hope this does not represent an inconvenience to be able to publish with you. In that case, please let us know!

I have already filled the Initial onboarding survey, but I see this box is not checked in your report. There exist any problem locating my filled survey? I can fill it again if needed.

[SimonMolinsky]

Hi @Manalclay

Thanks for your effort. Contribution files and API docs are critical issues right now. Thanks for checking the macOS installation issue; I will test it now and let you know how it went in your repository.

I'm sorry that your package didn't meet the scholarly effort criteria in JOSS. JOSS review and decisions are not a problem for us, but I needed to know about the potential submission because it leads to additional package and documentation checks in pyOpenSci.

Yes, I see that you have completed the onboarding survey. Thanks!

[SimonMolinsky]

Hi @Manalclay

I saw the Code of Conduct and Contributing files, thank you for updating those! Moreover, the installation problem has been resolved. It is platform-specific and has nothing to do with your package, but it may be interesting for you as a maintainer that installation of pyqt5-tools==5.15 on macOS is problematic.

Please let me know when you update your documentation. This is the last step before assigning the editor.

[Manalclay]

Hello @SimonMolinsky,

I'm sorry that your package didn't meet the scholarly effort criteria in JOSS. JOSS review and decisions are not a problem for us, but I needed to know about the potential submission because it leads to additional package and documentation checks in pyOpenSci.

If possible, we would like to know what additional checks are needed in order to publish to JOSS and see if we can assume the workload.

I saw the Code of Conduct and Contributing files, thank you for updating those! Moreover, the installation problem has been resolved. It is platform-specific and has nothing to do with your package, but it may be interesting for you as a maintainer that installation of pyqt5-tools==5.15 on macOS is problematic.

Thank you very much for all your help with the issue. We don't have access to a system similar to yours, so your help was useful. We will update the documentation to include the solution you provided. Thank you again! :)

[SimonMolinsky]

Hi @Manalclay

Reviewers will check those boxes in relation to JOSS submission:

---

#### For packages also submitting to JOSS

- [ ] The package has an **obvious research application** according to JOSS's definition in their [submission requirements](http://joss.theoj.org/about#submission_requirements).

*Note:* Be sure to check this carefully, as JOSS's submission requirements and scope differ from pyOpenSci's in terms of what types of packages are accepted.

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---

If JOSS has dropped your submission because the package didn't meet the scholarly effort criteria, our reviewers will need to know what changes have been made to meet those criteria before they can accept the first point from the list above. Do you plan to make some changes in the package for JOSS? Or have you expanded it from when you submitted it to JOSS? If you haven't made any changes but you plan to, then it's better to develop new functionalities in the package first, then submit the package for review here (and to JOSS after the pyOpenSci review ends). Or just leave the package as it is and focus on the pyOpenSci review right now :)

[Manalclay]

HI @SimonMolinsky,

Finally, we decide to focus on the pyOpenSci review as you said. Therefore, you can proceed without taking into account the JOSS requisites.

Thanks for your patience.

[SimonMolinsky]

Hi @Manalclay

Checking if everything is ok. How is your API documentation? Please let me know if you need any help.

[Manalclay]

Hi @SimonMolinsky,

Currently, all methods are documented. In order to make the documentation easier for anyone who wants to contribute, we're preparing a minimal sphinx web page ('readthedocs' style) to navigate the documentation.

Also, we added support for Python 3.12 and 3.13. This modification broke the test suite for Python 3.11, giving a segmentation fault that took us several weeks to debug. Now, everything is working again an we can focus in finish the sphinx.

Thanks for asking! I hope to have the website up and running as soon as possible.

[Manalclay]

Hello!

We've already commented the code, and also published the docs at https://astrogal.gitlab.io/GALAssify/. Thus, the review can be continued.

If you find any other necessary modifications or improvements, please let us known.

Thanks again for your patience. Regards,
Manuel

[SimonMolinsky]

Hi @Manalclay!

I was thinking about your package yesterday, and you brought such good news!

I've checked your documentation, and we can go ahead with the review. The next step is finding the editor and then the reviewers. I'm starting to search for an editor immediately, so please monitor this thread!

[lwasser]

hey there @Manalclay i'm just checkin in to see you are still around and available if we kick off this review soon. We have been on boarding new editors and may have someone to move this forward. Please reply if you are still in the review queue. Thank you!!

[Manalclay]

Yes! I'm around here, ready for the review. I'll be monitoring this thread frequently. Thanks! :)

[lwasser]

fantastic!! thanks for the speedy reply! 🚀

[ab93]

Hi all, I am happy to serve as an editor for GALAssify. I will update the YAML at the top, and we can get this going.

[ab93]

Hey all! One reviewer is confirmed. Searching for the second reviewer. Will keep you posted!

[ab93]

👋 Hi @akhilkrishnar0 and @erik-whiting! Thank you for volunteering to review
for pyOpenSci! You both have an awesome background in astrophysics and engineering respectively, which is perfect for this package. I look forward to learning new stuff from you both through this review process! 🔭

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TL;DR

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Due date: April 18th 2025 April 30th 2025

[Manalclay]

Hello! Some colleagues asked me for new features in this package. Could I implement them in a branch, without affecting the peer review? Or must I freeze all development until the review is done? Thanks in advance 😄

[ab93]

Hi @Malclay that is not a problem at all. Please go ahead with new features! :)

[akhilkrishnar0]

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Estimated hours spent reviewing: 7

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Review Comments

Thank you for the package — it's a really good one. The scope is clear, the documentation is well done, and the testing setup looks solid. Below, I've provided my comments and suggestions.

1. I’m not checking the box for badges. Please add standard badges (e.g., docs, CI) to the README — these work on GitLab too

2. It's very interesting that you've used PyQt5 to create the GUI — great job! I would suggest adding zoom-in and zoom-out options for the colour image as well, similar to what you've implemented for the FITS view. As a researcher, I would also like to zoom into the colour image to examine the components and features of the galaxy, just like we do with single-band images.

3. It would be beneficial to allow users to control the GUI launch via a command-line argument. Specifically, consider adding a --gui flag to force the GUI to launch, even if other command-line arguments are provided. This would give users more flexibility in choosing whether to use the GUI or command-line functionalities, depending on their needs. For example, running the program with python3 galassify.py --gui could bypass other arguments and directly launch the GUI. This would improve usability, especially for users who prefer a GUI interface.

4. The output table (*_fits.csv) contains an additional column named fits_coords, which is not part of the input columns (['group', 'galaxy', 'ra', 'dec', 'filename']). However, its purpose is not clearly documented, and it appears to contain empty lists ([]) by default. It would be helpful to clarify the intended use of this column—whether it is a placeholder for future coordinate data (e.g., from FITS file analysis), or if it plays a role in subsequent processing steps. Additionally, if this column is not actively used in the current implementation, consider omitting it to reduce potential confusion for users.

5. In the SDSS image download function, I noticed that you are using Data Release version 12. It would be helpful to allow the user to choose the SDSS DR version via an argument.

6. Citation information is missing from the README. Consider adding it to make it easier for others to cite the package properly in their work.

7. It is an impressive and highly customisable tool for astronomical classification, offering flexibility in tagging and workflows. Its integration with DS9 and support for FITS files enhance its utility for researchers. I suggest comparing it with the GalaxyZoo project (https://arxiv.org/abs/1308.3496): GalaxyZoo is a citizen science initiative where volunteers classify galaxies into various morphological types using a web-based interface. Compared to GalaxyZoo, which excels in large-scale morphological classification, GALAssify offers more tailored, research-specific workflows. This tool’s flexibility and potential for future machine learning integration make it a valuable asset for advanced astronomy studies.

8. In addition to these comments, I would like to add a suggestion: besides retrieving SDSS images, incorporating DECaLS images using a similar query would be valuable. Although DECaLS covers a slightly smaller area than SDSS, it provides more recent and higher-resolution imaging, which can significantly enhance galaxy classification.

[Manalclay]

Hi all!

@ab93 Thanks!! I'll push the new changes as soon as possible.

@akhilkrishnar0 Thank you so much for the package review! I will work on all your comments in order to improve the tool. I just have a doubt with the third point: I could implement the --gui option and the GUI will open empty, but once that, there is no option inside GALAssify to load the input files in a graphical way. Do you want me to implement the --gui option with a graphical input file chooser? Or instead, did you want the --gui to open the tool empty for, e.g., debugging purposes? Thanks again for the review!

[akhilkrishnar0]

Hi @Manalclay , Thanks for considering my suggestions!.
I personally think it would be really helpful to implement the --gui option with a graphical input file chooser to make the tool more user-friendly. Maybe adding a "Load File" button or menu item using something like QFileDialog.getOpenFileName() could let users select files interactively. I suggested this because the main advantage of a GUI is to offer a smoother, more accessible experience, especially for users who may not be comfortable with command-line inputs.

[Manalclay]

Hello @akhilkrishnar0,

I totally agree with you. It could be so helpful for inexperienced CLI users. I'll work on that! 🦾

I have one more questions: I noticed that the checkbox of "Descriptive links to all vignettes." is not checked. Is the first time I heard about "vignettes". I discovered that is common in R packages. Is the same think as the autogenerated API documentation in python? Should I do anything about this?

Thanks again for the comments, they are so valuable for fine-tuning the tool!

[akhilkrishnar0]

@Manalclay Thanks for pointing that out — you're absolutely right. In this case, a well-written usage guide in the README.md is sufficient. As long as it explains how to install, run, and interpret the outputs, it can effectively serve as the main vignette.
@ab93 Could you please confirm this as well? Once confirmed, I’ll go ahead and make the edit and check that box.

[ab93]

@Malclay you are right. Vignettes are more common in R packages, as you rightly pointed out. @akhilkrishnar0 feel free to update that.

[ab93]

Hi @erik-whiting, just checking in here, if you have any doubts/questions regarding the review or the process. Would love to help. And please let me know if you need more time to review.

[erik-whiting]

Hi @ab93 sorry for the delay (again), I am at a conference and flying back today. I will have my review done within 24 hours

[erik-whiting]

Package Review

Please check off boxes as applicable, and elaborate in comments below. Your review is not limited to these topics, as described in the reviewer guide

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Documentation

The package includes all the following forms of documentation:

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• Installation instructions: for the development version of the package and any non-standard dependencies in README.
• Vignette(s) demonstrating major functionality that runs successfully locally.
• Function Documentation: for all user-facing functions.
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NOTE: If the README has many more badges, you might want to consider using a table for badges: see this example. Such a table should be more wide than high. (Note that the a badge for pyOpenSci peer-review will be provided upon acceptance.)

• Short description of package goals.
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Estimated hours spent reviewing:

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Review Comments

1. There are no badges, can yo uplease add them?

2. I checked the box for "link to your documentation site, even though you don't specifically have one. I figure GitLab is your documentation website.

3. I don't see any comparisons to existing packages. I believe the other reviewer mentioned Galaxy Zoo, there are also AstroML and DeepGalaxy which, while not exactly the same, may be worth comparing to.

4. I agree with the other reviewer that an option to add a GUI option to the command line would be useful.

5. Overall this is really cool!

[ab93]

Hi @Manalclay just checking in. Let us know if you have any questions regarding the changes requested by the reviewers! 🙂

[Manalclay]

Hello @ab93 !! I think everything is going well by the moment. Currently, the next changes were implemented:

• get_images_sdss: SDSS Data Release selection by argument.
• get_images_sdss: Added DECaLS catalogue and other DESI data releases.
• Added badges in readme
• Added documentation website (GitLab Pages) in README

I'm currently working on:

• Comparison with similar packages (completed but in Test/Review, waiting my colleague to review it)
• Zoom-in and Zoom-out in main display
• GUI-only usage
• Document "fits_coods" column

When these issues were closed, I'll zip the entire repository and upload it to Zenodo in order to get a DOI and add the citation information.

Thank you for you patience and help. Sorry if I'm being slow implementing the changes, hope I have these fixes ASAP!

[ab93]

Thanks for the update @Manalclay! This is really helpful. Once the changes are implemented, let us know here so that the changes can be reviewed again. :)