Amanogawa: Reproducible quantification of Milky Way structure from single-exposure smartphone images

Amanogawa is an open-source, MIT-licensed Python package and reproducible workflow for extracting quantitative summaries of Milky Way structure from a single wide-field smartphone long-exposure image. The software bridges widely accessible astrophotography and transparent, inspectable measurements suitable for small research projects, education, and citizen-science studies. From a single image, Amanogawa detects candidate point sources, exports coordinate catalogs, and computes spatial statistics that summarize stellar clustering across scales. In parallel, it estimates the principal axis of the Milky Way band in image coordinates and measures band width from perpendicular profiles, enabling consistent within-image and cross-image comparisons. These analyses are intentionally formulated to remain meaningful even in the absence of full astrometric calibration. The workflow supports both interactive notebook use and a command-line interface, producing archival-friendly artifacts including star catalogs, threshold-sweep summaries, fitted band-width parameters, and diagnostic/publication-quality figures (CSV/JSON/PNG). By combining explicit robustness diagnostics with a standardized, end-to-end pipeline, Amanogawa enables repeatable quantitative analyses of accessible single-exposure imagery while keeping intermediate results transparent and reusable.