Chemometrics library for data fusion, model training and prediction of data from multiple sensor sources.
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Updated
Jul 2, 2024 - Jupyter Notebook
Chemometrics library for data fusion, model training and prediction of data from multiple sensor sources.
Tools for chemometrics and machine learning on high-dimensional data (e.g. Partial least squares regression/discrimination)
Implementation of PLS-DA and OPLS-DA for high dimensional data, like MS in metabolomics.
The specProc package is a collection of preprocessing tools for spectroscopy data analysis.
Integrate your chemometric tools with the scikit-learn API 🧪 🤖
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Examples of scripts with package Jchemo (Training material)
pyChemometrics - Objects for multivariate analysis of chemometric and metabonomic datasets
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.).
ANOVA-Simultaneous Component Analysis
Opus2csv is a command-line tool that allows users to convert Opus Binary Files to either CSV or Array format. When the spectra exhibit dissimilar wavenumber or wavelength datapoints, the process results in the creation of multiple CSV files. Each of these files encompasses spectra with comparable wavenumber or wavelength datapoints.
volcalc: Calculate Volatility of Chemical Compounds
CRAN Task View: Chemometrics and Computational Physics
Analyzing thin-layer chromatography (TLC) chromatograms
Non-linear fitting tool for supramolecular titration experiments and kinetics.
📈 Ordered Homogeneity Pursuit Lasso for Group Variable Selection
Spectroscopic data processing approaches for petroleum wax blends quantification
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