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arxiv: 1906.11147 · v1 · pith:7NLZA7IOnew · submitted 2019-06-26 · 🌌 astro-ph.IM · astro-ph.GA· cs.SE

Using the Agile software development lifecycle to develop a standalone application for generating colour magnitude diagrams

K. Fitzgerald , L.-M. Browne , R.F. Butler This is my paper

Pith reviewed 2026-05-25 15:14 UTC · model grok-4.3

classification 🌌 astro-ph.IM astro-ph.GAcs.SE
keywords colour magnitude diagramsstandalone applicationAgile SDLCPython GUIphotometric datavirtual observatoriesstar cluster photometryobject oriented programming
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The pith

A standalone Python app for plotting colour-magnitude diagrams was built using the Agile software development lifecycle.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

Astronomers often encounter steep learning curves when trying to visualize data from virtual observatories. The paper presents CMD Plot Tool, a standalone application written in Python that lets users generate and annotate photometric colour magnitude diagrams through a graphical interface. The tool was created with object-oriented programming and the Agile SDLC so that it runs out of the box on multiple platforms without any code interpreters, libraries, or path changes. The authors argue that the astronomical software community should identify and adopt formal development lifecycles to produce more accessible tools for research and teaching. If the approach holds, it supplies a practical example of how such methods can deliver ready-to-use applications from publicly available photometry.

Core claim

CMD Plot Tool is a standalone Python application that plots photometric colour magnitude diagrams from data sources including virtual observatories and reduced observations, using a GUI for quick interaction, annotation, and high-quality output, developed following the Agile SDLC and object-oriented principles to ensure it functions without additional installations or modifications.

What carries the argument

CMD Plot Tool, the standalone Python GUI application for generating annotated CMD plots from photometric data, built via the Agile SDLC.

If this is right

  • Users can produce research- and teaching-quality CMD plots from online data or IRAF-reduced observations without installing any supporting software.
  • The same application runs across multiple operating systems without platform-specific configuration.
  • Adopting formal SDLCs can yield tools that lower barriers for both professional astronomers and educators working with stellar populations.
  • All plots in the paper were generated directly with the tool from publicly accessible virtual observatory data.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Similar standalone tools could be developed for other common astronomical plots such as spectra or light curves using the same development approach.
  • Wider use of formal SDLCs might reduce the time spent by researchers on software troubleshooting rather than science.
  • The tool's design could serve as a template for packaging other Python-based analysis routines into distributable executables.

Load-bearing premise

Astronomical software development benefits from adopting formal lifecycles such as Agile instead of less structured approaches.

What would settle it

Download and execute the CMD Plot Tool on a computer with no Python installation or libraries present, then load public photometry data and confirm that a labelled CMD plot is produced without errors or setup steps.

Figures

Figures reproduced from arXiv: 1906.11147 by K. Fitzgerald, L.-M. Browne, R.F. Butler.

Figure 1
Figure 1. Figure 1: CMD Generation Flowchart. This illustrates the steps and learning [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: The Agile Software Development Lifecycle. [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 4
Figure 4. Figure 4: Test Driven Development Image reproduced from http://agiledata. org/essays/tdd.html. c Scott W Ambler if the user opts to display error bars on the plot. DAOPHOT .mag files. DAOPHOT (ascl:1104.011) (Stetson, 1987) was developed for performing point-source photome￾try, particularly in crowded stellar fields; initially as a stan￾dalone package, and subsequently ported into IRAF. The typ￾ical DAOPHOT .mag fil… view at source ↗
Figure 3
Figure 3. Figure 3: UML diagram for classes outlined in the Python files in Table [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figure 5
Figure 5. Figure 5: CMD Plot Tool: Panel (a) shows its Graphical User Interface (GUI). Panel (b) outlines its operational flowchart. Column Name Description id Identification of the star x,y Position of the star on the master image Vvega, err, VIvega, err, Ivega, err Magnitudes/colour and errors on the VEGAmag photometric system - stars with one measurement have errors based on root(n) noise. Vground, Iground Magnitudes on th… view at source ↗
Figure 6
Figure 6. Figure 6: Comparison of CMDs of globular cluster NGC 6205 (M13), generated as a single output using the Plot Comparison functionality (see [PITH_FULL_IMAGE:figures/full_fig_p009_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: CMDs for GC NGC 3201, generated from ACS Survey of Galactic Globular Clusters data (Sarajedini et al., 2007). Panel (a) shows the full CMD without error bars, while Panel (b) shows error bars, and is zoomed in and annotated to highlight stars at the top of the main sequence and main sequence turn-off. (ii) White Dwarf Cooling and (iii) Main Sequence Turnoff Time Scale: a robust prediction of the theoretica… view at source ↗
Figure 8
Figure 8. Figure 8: CMDs of Globular Cluster NGC 1851. Data from the ACS Survey of Galactic Globular Clusters ( [PITH_FULL_IMAGE:figures/full_fig_p011_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: A single output file in Plot Comparison mode. Left side: CMD for GC NGC 288, where HB-Blue is the blue population of the horizontal branch. Right [PITH_FULL_IMAGE:figures/full_fig_p012_9.png] view at source ↗
read the original abstract

Virtual observatories allow the means by which an astronomer is able to discover, access, and process data seamlessly, regardless of its physical location. However, steep learning curves are often required to become proficient in the software employed to access, analyse and visualise this trove of data. It would be desirable, for both research and educational purposes, to have applications which allow users to visualise data at the click of a button. Therefore, we have developed a standalone application (written in Python) for plotting photometric Colour Magnitude Diagrams (CMDs) - one of the most widely used tools for studying and teaching about astronomical populations. The CMD Plot Tool application functions "out of the box" without the need for the user to install code interpreters, additional libraries and modules, or to modify system paths; and it is available on multiple platforms. Interacting via a graphical user interface (GUI), users can quickly and easily generate high quality plots, annotated and labelled as desired, from various data sources. This paper describes how CMD Plot Tool was developed using Object Orientated Programming and a formal software design lifecycle (SDLC). We highlight the need for the astronomical software development culture to identify appropriate programming paradigms and SDLCs. We outline the functionality and uses of CMD Plot Tool, with examples of star cluster photometry. All results plots were created using CMD Plot Tool on data readily available from various online virtual observatories, or acquired from observations and reduced with IRAF/PyRAF.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 3 minor

Summary. The manuscript describes the development of a standalone Python application, the CMD Plot Tool, for generating photometric colour-magnitude diagrams (CMDs) from astronomical data. The tool was built using object-oriented programming and the Agile software development lifecycle; it is claimed to run out-of-the-box on multiple platforms without requiring code interpreters, library installs, or path modifications. The paper outlines the tool's GUI-based functionality, provides usage examples with star-cluster photometry drawn from virtual observatories or IRAF/PyRAF-reduced observations, and advocates for wider adoption of formal SDLCs in astronomical software development.

Significance. If the implementation matches the claims, the tool would offer a low-barrier entry point for CMD visualization useful in both research and teaching. The explicit use of a structured Agile process supplies a concrete example of disciplined development in astro software. The manuscript does not ship code, executables, or quantitative verification results, so reproducibility and actual cross-platform behaviour cannot be assessed from the text alone.

minor comments (3)
  1. [Abstract and §3 (Development/Functionality)] The abstract states that the application 'functions out of the box' on multiple platforms, yet the manuscript provides neither a list of supported operating systems nor explicit installation or launch instructions; adding these would directly support the central usability claim.
  2. [Throughout (e.g., §4 Examples)] No screenshots of the GUI, example output plots, or usage workflow diagrams appear in the text; inclusion of at least one annotated figure would make the described functionality concrete for readers.
  3. [Discussion/Conclusion] The advocacy for formal SDLCs in the astronomical community is presented without any comparative metrics or case studies; if retained, it should be clearly labelled as an opinion rather than an empirical result.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their positive assessment of the work and for recommending minor revision. We address the principal concern regarding reproducibility below.

read point-by-point responses

  1. Referee: The manuscript does not ship code, executables, or quantitative verification results, so reproducibility and actual cross-platform behaviour cannot be assessed from the text alone.

    Authors: We agree this is a valid limitation of the submitted manuscript. In the revised version we will add an appendix containing (i) a permanent link to the public GitHub repository with the full source code, (ii) direct download links for the pre-built standalone executables for Windows, macOS and Linux, and (iii) a short quantitative verification table documenting successful execution and identical CMD output on the three platforms using the same input catalogue. revision: yes

Circularity Check

0 steps flagged

No significant circularity

full rationale

This is a descriptive software development paper with no derivations, equations, predictions, or fitted parameters. The central claim is the factual completion of a standalone CMD Plot Tool application using Python, OOP, and a formal SDLC, presented as an outcome of the project with usage examples. No load-bearing steps reduce to self-definition, fitted inputs renamed as predictions, or self-citation chains. The forward recommendation to adopt formal SDLCs is an opinion, not an empirical assertion that could be circular. The paper is self-contained against external benchmarks as a tool description.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

This is a software description paper with no mathematical derivations, fitted parameters, axioms, or invented entities.

pith-pipeline@v0.9.0 · 5806 in / 1150 out tokens · 33406 ms · 2026-05-25T15:14:47.603111+00:00 · methodology

discussion (0)

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Reference graph

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