| Autor: |
Georgiev D; Department of Computing & UKRI Centre for Doctoral Training in AI for Healthcare, Imperial College London, London SW7 2AZ, United Kingdom.; Department of Materials, Department of Bioengineering & Institute of Biomedical Engineering, Imperial College London, London SW7 2AZ, United Kingdom., Pedersen SV; Department of Materials, Department of Bioengineering & Institute of Biomedical Engineering, Imperial College London, London SW7 2AZ, United Kingdom., Xie R; Department of Materials, Department of Bioengineering & Institute of Biomedical Engineering, Imperial College London, London SW7 2AZ, United Kingdom., Fernández-Galiana Á; Department of Materials, Department of Bioengineering & Institute of Biomedical Engineering, Imperial College London, London SW7 2AZ, United Kingdom., Stevens MM; Department of Materials, Department of Bioengineering & Institute of Biomedical Engineering, Imperial College London, London SW7 2AZ, United Kingdom., Barahona M; Department of Mathematics, Imperial College London, London SW7 2AZ, United Kingdom. |
| Abstrakt: |
Raman spectroscopy is a nondestructive and label-free chemical analysis technique, which plays a key role in the analysis and discovery cycle of various branches of science. Nonetheless, progress in Raman spectroscopic analysis is still impeded by the lack of software, methodological and data standardization, and the ensuing fragmentation and lack of reproducibility of analysis workflows thereof. To address these issues, we introduce RamanSPy , an open-source Python package for Raman spectroscopic research and analysis. RamanSPy provides a comprehensive library of tools for spectroscopic analysis that supports day-to-day tasks, integrative analyses, the development of methods and protocols, and the integration of advanced data analytics. RamanSPy is modular and open source, not tied to a particular technology or data format, and can be readily interfaced with the burgeoning ecosystem for data science, statistical analysis, and machine learning in Python. RamanSPy is hosted at https://github.com/barahona-research-group/RamanSPy, supplemented with extended online documentation, available at https://ramanspy.readthedocs.io, that includes tutorials, example applications, and details about the real-world research applications presented in this paper. |
