astroimg 0.1.0

Astronomical image analysis library

Astroimg

A Python library for astronomical image analysis. Download FITS images from sky surveys, detect sources, measure their brightness, and cross-match with the Gaia DR3 catalog.

Installation

pip install astroimg

Or install from source:

git clone https://github.com/Fr-C-S-08/Astroimg-Library.git
cd Astroimg-Library
pip install -e .

Quick Start

from astroimg import download_best, detect_sources, aperture_photometry, crossmatch_gaia

# Download a FITS image
data, header, wcs = download_best(ra=29.23, dec=37.79, radius=0.12)

# Detect sources
sources = detect_sources(data, wcs, kernel="log", threshold=5.0)

# Measure brightness
phot = aperture_photometry(data, sources)

# Cross-match with Gaia DR3
result = crossmatch_gaia(phot)

Pipeline

download_best() → detect_sources() → aperture_photometry() → crossmatch_gaia()
     ↓                  ↓                     ↓                      ↓
 FITS image       source catalog        flux & magnitudes     Gaia match + temp

Modules

Module	Description
download	Download FITS images from DSS/SkyView
kernels	Gaussian, LoG, and matched filter convolution
detection	Source detection with local maxima and consensus
photometry	Aperture photometry with sky subtraction
crossmatch	Cross-match with Gaia DR3 catalog
visualization	Highlight stars and plot sources

Features

Download astronomical images

from astroimg import download_best
data, header, wcs = download_best(ra=250.42, dec=36.46, radius=0.15)

Detect and count sources

from astroimg import detect_sources, count_sources
sources = detect_sources(data, wcs, kernel="log", threshold=5.0)
print(f"Found {count_sources(sources)} sources")

Aperture photometry

from astroimg import aperture_photometry
phot = aperture_photometry(data, sources)
print(phot[["x_pixel", "y_pixel", "flux", "mag"]].head())

Cross-match with Gaia

from astroimg import crossmatch_gaia, crossmatch_stats
result = crossmatch_gaia(phot)
crossmatch_stats(result)

Highlight specific stars

from astroimg import highlight_star
highlight_star(data, wcs, name="HD 196885", sources=sources)

Docker

docker compose up

Tests

pip install -e ".[dev]"
pytest tests/ -v

Requirements

• Python >= 3.9
• numpy, scipy, matplotlib, astropy, astroquery, pandas

License

MIT