SpectroChemPy is a framework for processing, analyzing and modeling spectroscopic data for chemistry with Python
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Updated
Sep 29, 2024 - Python
SpectroChemPy is a framework for processing, analyzing and modeling spectroscopic data for chemistry with Python
Luminescence data analysis with HyperSpy.
RamanSPy: An open-source Python package for integrative Raman spectroscopy data analysis
Python package that provides a full range of functionality to process and analyze vibrational spectra (Raman, SERS, FTIR, etc.).
Python code to identify and calculate decomposition of materials using Raman spectroscopy
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 package for read-only accessing the wdf Raman spectroscopy from Ranishaw WiRE software
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.
Generator useful to handle Raman spectra data augmentation for deep learning models
Master's disseration source code to find peaks of Raman Spectroscopy of CZTS and fit Lorentzians to decompose the structure.
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.
Integrate your chemometric tools with the scikit-learn API 🧪 🤖
A Python framework for the batch processing and deconvolution of Raman spectra of carbonaceous materials.
A open-source program for computing the first-order resonance Raman spectroscopy based on Quantum ESPRESSO
Baseline correction, smoothing, processing and plotting of Raman spectra
Here we apply deep learning approaches to accurately identify 30 common bacterial pathogens, reaching an average isolate-level accuracy exceeding 78%, and an antibiotic treatment identification accuracy of 95%.
Code and data for the paper ACS Applied Nano Materials 5, 1356-1366, 2022 doi:10.1021/acsanm.1c03928
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.
Visualitzation and processing toolbox for Confocal Raman Spectroscopy Imaging
Official implementation for paper "Raman spectra matching with contrastive representation learning"
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