RamanSPy: An open-source Python package for integrative Raman spectroscopy data analysis

SpectroChemPy is a framework for processing, analyzing and modeling spectroscopic data for chemistry with Python

Luminescence data analysis with HyperSpy.

Python package for read-only accessing the wdf Raman spectroscopy from Ranishaw WiRE software

Data toolkits for processing NMR, MALDI MSI, MALDI single cell, Raman Spectroscopy, LC-MS and GC-MS raw data, chemoinformatics data analysis and data visualization.

Python code to identify and calculate decomposition of materials using Raman spectroscopy

Python package that provides a full range of functionality to process and analyze vibrational spectra (Raman, SERS, FTIR, etc.).

Perform baseline removal, baseline correction and baseline substraction for raman spectra using Modpoly, ImodPoly and Zhang fit. Returns baseline-subtracted spectrum. Please give proper citation as specified in the documentation if it has helped you.

Integrate your chemometric tools with the scikit-learn API 🧪 🤖

SpectraGuru - A Spectra Analysis Application

A Python framework for the batch processing and deconvolution of Raman spectra of carbonaceous materials.

Master's disseration source code to find peaks of Raman Spectroscopy of CZTS and fit Lorentzians to decompose the structure.

A open-source program for computing the first-order resonance Raman spectroscopy based on Quantum ESPRESSO

Generator useful to handle Raman spectra data augmentation for deep learning models

WORK IN PROGRESS - The Vibration Spectroscopy Ontology defines technical terms with which research data produced in vibrational spectroscopy experiments can be semantically enriched, made machine readable and FAIR.

Baseline correction, smoothing, processing and plotting of Raman spectra

Efficiently compute off-resonance Raman spectra from first principles calculations (e.g. VASP) using polynomial models and machine learning..

We apply deep learning approaches to accurately identify 30 common bacterial pathogens, achieving an average isolate-level accuracy of over 78% and an antibiotic treatment identification accuracy of 95%.

Procedures (for IgorPro) to perform operations needed in day to day analysis of spectroscopic data. For example, Raman or infrared spectra where the data is structured as array of 1-D or 2-D waves.

Code and data for the paper ACS Applied Nano Materials 5, 1356-1366, 2022 doi:10.1021/acsanm.1c03928