PySpecTrace: A Python-based Graphical User Interface for Real-Time Spectroscopy Analysis and Data Analysis [version 1; peer review: 1 approved, 3 approved with reservations]
4 affiliations
- 1Research Center for Photonics, National Research and Innovation Agency Republic of Indonesia, Serpong, Banten, 15314, Indonesia
- 2Department of Chemistry Education, State University of Yogyakarta, Faculty of Mathematics and Natural Sciences, Yogyakarta City, Special Region of Yogyakarta, 55281, Indonesia
- 3Department of Physics and Astronomy, Vrije Universiteit Amsterdam, Amsterdam, North Holland, 1081HZ, The Netherlands
- 4Department of Physics, Universitas Indonesia, Faculty of Mathematics and Natural Sciences, Depok, West Java, 16454, Indonesia
Abstract
Background UV–visible spectroscopy is widely used to monitor real-time transformations in material systems. However, accessible and open-source tools for real-time tracking and analysis of spectral features—including peak position, width, and intensity—remain limited. Existing workflows are often multi-step and/or reliant on proprietary software. Methods We developed PySpecTrace, an open-source, Python-based graphical user interface (GUI) for real-time spectroscopy analysis. The platform integrates spectral data acquisition, preprocessing, visualization, and feature extraction within a unified and modular framework. Core functionalities include real-time tracking of peak/dip wavelength, spectral width, and intensity, as well as configurable data processing workflows. The software is designed for flexibility, enabling adaptation to generic experimental setups and time-resolved measurements. Results PySpecTrace enables continuous monitoring and analysis of spectral evolution with minimal user intervention. Demonstration cases show its capability to track dynamic spectral changes and extract key parameters in real time, improving analysis efficiency and consistency compared to conventional post-processing approaches. In addition to real-time analysis, the platform supports post-processing of pre-recorded spectral data including feature extraction and quantitative analysis. Conclusions PySpecTrace provides an accessible and extensible solution for real-time spectroscopy analysis, bridging experimental measurement and data processing. By offering open-source availability and reproducible workflows, it facilitates more efficient and transparent analysis of time-resolved spectroscopic data.
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BibTeX
@article{anam2026pyspectrace,
title = {{PySpecTrace: A Python-based Graphical User Interface for Real-Time Spectroscopy Analysis and Data Analysis [version 1; peer review: 1 approved, 3 approved with reservations]}},
author = {Sigit Khoirul Anam and Joshu Leonardy and Suwardi Suwardi and Andrea Baldi and Ferry Anggoro Ardy Nugroho and Iwan Darmadi},
journal = {F1000Research},
year = {2026},
month = jul,
doi = {10.12688/f1000research.180635.1},
url = {https://doi.org/10.12688/f1000research.180635.1},
note = {CC BY},
}
RIS
TY - JOUR
TI - PySpecTrace: A Python-based Graphical User Interface for Real-Time Spectroscopy Analysis and Data Analysis [version 1; peer review: 1 approved, 3 approved with reservations]
AU - Sigit Khoirul Anam
AU - Joshu Leonardy
AU - Suwardi Suwardi
AU - Andrea Baldi
AU - Ferry Anggoro Ardy Nugroho
AU - Iwan Darmadi
PY - 2026
DA - 2026/07/01
JO - F1000Research
DO - 10.12688/f1000research.180635.1
UR - https://doi.org/10.12688/f1000research.180635.1
AB - Background UV–visible spectroscopy is widely used to monitor real-time transformations in material systems. However, accessible and open-source tools for real-time tracking and analysis of spectral features—including peak position, width, and intensity—remain limited. Existing workflows are often multi-step and/or reliant on proprietary software. Methods We developed PySpecTrace, an open-source, Python-based graphical user interface (GUI) for real-time spectroscopy analysis. The platform integrates spectral data acquisition, preprocessing, visualization, and feature extraction within a unified and modular framework. Core functionalities include real-time tracking of peak/dip wavelength, spectral width, and intensity, as well as configurable data processing workflows. The software is designed for flexibility, enabling adaptation to generic experimental setups and time-resolved measurements. Results PySpecTrace enables continuous monitoring and analysis of spectral evolution with minimal user intervention. Demonstration cases show its capability to track dynamic spectral changes and extract key parameters in real time, improving analysis efficiency and consistency compared to conventional post-processing approaches. In addition to real-time analysis, the platform supports post-processing of pre-recorded spectral data including feature extraction and quantitative analysis. Conclusions PySpecTrace provides an accessible and extensible solution for real-time spectroscopy analysis, bridging experimental measurement and data processing. By offering open-source availability and reproducible workflows, it facilitates more efficient and transparent analysis of time-resolved spectroscopic data.
SN - 2046-1402
ER -