GAMMA_FLOW: Guided Analysis of Multi-label spectra by MAtrix Factorization for Lightweight Operational Workflows
gamma_flow is an open-source Python package for real-time analysis of spectral data. It supports classification, denoising, decomposition, and outlier detection of both single- and multi-component spectra. Instead of relying on large, computationally intensive models, it employs a supervised approach to non-negative matrix factorization (NMF) for dimensionality reduction. This ensures a fast, efficient, and adaptable analysis while reducing computational costs. gamma_flow achieves classification accuracies above 90% and enables reliable automated spectral interpretation. Originally developed for gamma-ray spectra, it is applicable to any type of one-dimensional spectral data. As an open and flexible alternative to proprietary software, it supports various applications in research and industry.
Authors
- Tilman Hartwig (ORCID: https://orcid.org/0000-0001-6742-8843)
- Viola Rädle (ORCID: https://orcid.org/0000-0002-5852-0266)
- J. Vogt (ORCID: https://orcid.org/0000-0001-8157-9162)
- Martin Baron
- Benjamin Oesen
- Emily Alice Kröger
- Eike Gericke
Institutions
- German Environment Agency (DE)
- Federal Office for Radiation Protection (DE)
Publication Details
- Journal
- SoftwareX
- Published
- 2025-09-25
- DOI
- https://doi.org/10.1016/j.softx.2025.102342
- Primary Topic
- Advanced Chemical Sensor Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00