disco-astronomy 1.1.1

Deprojection Image Software for Circumstellar Objects

WORK IN PROGRESS (WIP) This software is currently in early active development. Features and documentation are being updated frequently.

DISCO

Deprojection Image Software for Circumstellar Objects

A hybrid pipeline for the analysis and physical characterization of protoplanetary disks from ALMA FITS data.

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Overview

DISCO is an open-source tool for the interactive and automated analysis of protoplanetary disk observations. It combines a convolutional neural network (DiscoNet) for rapid geometric parameter prediction with a hybrid optimization strategy, enabling robust deprojection and radial profile extraction from FITS images.

It bridges scientific Python libraries with a modern web interface, offering two complementary modes of operation: a CLI pipeline for batch processing and a GUI for interactive exploration.

Citation: If you use DISCO in published work, please cite this repository and acknowledge Jorge Luis Guzmán Lazo, who developed the software within the YEMS Millennium Nucleus under the supervision of Sebastián Pérez.

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Key Features

• DiscoNet (CNN) — Convolutional neural network that predicts disk geometric parameters (inclination, position angle, outer/inner radius) directly from FITS images.
• Hybrid Optimization (CLI) — Combines CNN predictions with fine-grained numerical refinement for physically consistent results.
• Dual Visualization — Real-time rendering of deprojected images in both Cartesian and polar projections.
• Batch Processing (CLI) — Automated pipeline supporting multiple targets and FITS files in a single run.
• Beam Homogenization (CLI) — Convolves images to a target resolution for multi-epoch or multi-band consistency.
• SIMBAD Metadata — A- Gaia Integration (CLI) — Corrects for proper motion of the target system using Gaia DR3 astrometry. utomatically queries object metadata (distance, spectral type) via the CDS SIMBAD service.
• CSV Export — Outputs radial profiles and fitted parameters in tabular format.

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Two Modes of Operation

Feature	CLI Pipeline (disco-start)	GUI (disco-start with no args)
DiscoNet (CNN)	✅	❌
Interactive visualization	❌	✅
Batch processing	✅	❌
Multi-band support	✅	❌
Beam degradation	✅	❌
Ease of use	Moderate	High

The GUI mode is recommended for exploratory analysis and users new to disk deprojection. The CLI mode is designed for reproducible, automated pipelines.

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Installation

Recommended: Use a dedicated virtual environment to avoid dependency conflicts.

# Create and activate a virtual environment
python -m venv disco-env
source disco-env/bin/activate      # Linux / macOS
disco-env\Scripts\activate         # Windows

# Install DISCO
pip install disco-astronomy

# Hint: Remember to update the package using
pip install --upgrade disco-astronomy

📦 Package on PyPI: pypi.org/project/disco-astronomy

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Quick Start

Interactive GUI

Launch the web interface for interactive, user-friendly analysis:

disco-start

This opens a local server with a React-based UI for loading FITS files, adjusting parameters visually, and inspecting radial profiles in real time.

Automated CLI Pipeline

For batch processing of one or more targets:

# Process a single object by identifier
disco-start AS209

# Process a group of object by identifier
disco-start path/to/group/

# Process multiple objects in separate
disco-start AS209 Elias29 DoAr25

# Process a FITS file directly
disco-start path/to/disk.fits

# Force geometric parameters and export CSV
disco-start AS209 --incl 35.0 --pa 120.0 --csv on

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CLI Reference

usage: disco-start [-h] [--rout ROUT] [--rmin RMIN] [--incl INCL] [--pa PA]
                   [--beam BEAM] [--homobeam {on,off}] [--csv {on,off}]
                   [--debug {on,off}] [identifier ...]

Argument	Description
identifier	Object prefix(es) or path(s) to FITS file(s)
--rout ROUT	Force outer radius (arcsec)
--rmin RMIN	Force inner radius (arcsec)
--incl INCL	Force disk inclination (degrees)
--pa PA	Force position angle (degrees)
--beam BEAM	Force target beam resolution (arcsec)
--homobeam {on,off}	Enable/disable beam homogenization
--csv {on,off}	Export radial profile as CSV
--debug {on,off}	Save debug deprojected image

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Tech Stack

Layer	Technology
Backend	Python 3.10+, FastAPI, Astropy, SciPy, NumPy
Deep Learning	PyTorch (DiscoNet CNN)
Frontend	React, Vite, BlueprintJS
Distribution	PyPI (disco-astronomy)

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License

This project is licensed under the MIT License.

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Support & Contact

If you encounter issues or have questions, feel free to reach out:

📬 [e-mail]

Bug reports and contributions via GitHub Issues are also welcome.