THORONDOR: a software for fast treatment and analysis of low-energy XAS data
| Autor: | Luca Braglia, Elisa Borfecchia, Alessandro Piovano, David Horst Simonne, Gabriele Ricchiardi, Andrea Martini, Matteo Signorile, Piero Torelli |
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| Rok vydání: | 2020 |
| Předmět: |
Nuclear and High Energy Physics
Computer science 02 engineering and technology in situ measurements computer.software_genre 01 natural sciences Data treatment NEXAFS Software Low energy NEXAFS in situ measurements data treatment peak fitting graphical user interface Python 0103 physical sciences Instrumentation peak fitting computer.programming_language Graphical user interface 010302 applied physics Background subtraction Radiation data treatment business.industry graphical user interface Statistical parameter Python (programming language) 021001 nanoscience & nanotechnology Toolbox Data mining 0210 nano-technology business computer Python |
| Zdroj: | Journal of synchrotron radiation. 27(Pt 6) |
| ISSN: | 1600-5775 |
| Popis: | THORONDOR is a data treatment software with a graphical user interface (GUI) accessible via the browser-based Jupyter notebook framework. It aims to provide an interactive and user-friendly tool for the analysis of NEXAFS spectra collected during in situ experiments. The program allows on-the-fly representation and quick correction of large datasets from single or multiple experiments. In particular, it provides the possibility to align in energy several spectral profiles on the basis of user-defined references. Various techniques to calculate background subtraction and signal normalization have been made available. In this context, an innovation of this GUI involves the usage of a slider-based approach that provides the ability to instantly manipulate and visualize processed data for the user. Finally, the program is characterized by an advanced fitting toolbox based on the lmfit package. It offers a large selection of fitting routines as well as different peak distributions and empirical ionization potential step edges, which can be used for the fit of the NEXAFS rising-edge peaks. Statistical parameters describing the goodness of a fit such as χ2 or the R-factor together with the parameter uncertainty distributions and the related correlations can be extracted for each chosen model. |
| Databáze: | OpenAIRE |
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