Package: chemotools
chemotoolsWelcome to Chemotools, a Python package that integrates chemometrics with Scikit-learn.NoteSince I released Chemotools, I have received a fantastic response from the community. I am really happy for the interest in the project 🤗. This also means that I have received a lot of good feedback and suggestions for improvements. I have been intensively working on releasing new versions of Chemotools to address the feedback and suggestions. If you use Chemotools,make sure you are using the latest version(see installation), which will be aligned with the documentation.👉👉 Check thelatest versionand make sure you don't miss out on cool new features.👉👉 Check thedocumentationfor a full description on how to use chemotools.DescriptionChemotools is a Python package that provides a collection of preprocessing tools and utilities for working with spectral data. It is built on top of popular scientific libraries and is designed to be highly modular, easy to use, and compatible with Scikit-learn transformers.If you are interested in learning more about chemotools, please visit thedocumentationpage.Benefits:Provides a collection of preprocessing tools and utilities for working with spectral dataHighly modular and compatible with Scikit-learn transformersCan perform popular preprocessing tasks such as baseline correction, smoothing, scaling, derivatization, and scattering correctionOpen source and available on PyPIApplications:Analyzing and processing spectral data in chemistry, biology, and other fieldsDeveloping machine learning models for predicting properties or classifying samples based on spectral dataTeaching and learning about chemometrics and data preprocessing in PythonInstallationChemotools is distributed via PyPI and can be easily installed using pip:pipinstallchemotoolsUpgrading to the latest version is as simple as:pipinstallchemotools--upgradeUsageChemotools is designed to be used in conjunction with Scikit-learn. It follows the same API as other Scikit-learn transformers, so you can easily integrate it into your existing workflow. For example, you can use chemotools to build pipelines that include transformers from chemotools and Scikit-learn:fromsklearn.preprocessingimportStandardScalerfromsklearn.pipelineimportmake_pipelinefromchemotools.baselineimportAirPlsfromchemotools.scatterimportMultiplicativeScatterCorrectionpreprocessing=make_pipeline(AirPls(),MultiplicativeScatterCorrection(),StandardScaler(with_std=False))spectra_transformed=preprocessing.fit_transform(spectra)Check thedocumentationfor more information on how to use chemotools.ContributingWe welcome contributions to Chemotools from anyone interested in improving the package. Whether you have ideas for new features, bug reports, or just want to help improve the code, we appreciate your contributions! You are also welcome to see theProject Boardto see what we are currently working on.To contribute to Chemotools, please follow thecontributing guidelines.LicenseThis package is distributed under the MIT license. See theLICENSEfile for more information.CreditsAirPLS baseline correction is based on the implementation byZhang et al.. The current implementation is based on the Python implementation byzmzhang.