ramanspy

https://github.com/qibebt-scc/ramanspy

Science Score: 67.0%

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Repository

Basic Info

Host: GitHub
Owner: QIBEBT-SCC
License: bsd-3-clause
Language: Jupyter Notebook
Default Branch: main
Size: 34.2 MB

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Created 11 months ago · Last pushed 11 months ago

Metadata Files

Readme Contributing License Citation

RamanSPy: An open-source package for Raman Spectroscopy analytics in Python.

Key features

Overview of RamanSPy

Common data format
Data loaders
Preprocessing methods
Preprocessing pipelining
Preprocessing protocols
Analysis methods
AI & ML integration
Visualisation tools
Datasets
Synthetic data generator
Metrics

Installation

RamanSPy has been published on PyPI and can be installed via pip:

console pip install ramanspy

Code example

Below is a simple example of how RamanSPy can be used to load, preprocess and analyse Raman spectroscopic data. Here, we load a data file from a commercial Raman instrument; apply a preprocessing pipeline consisting of spectral cropping, cosmic ray removal, denoising, baseline correction and normalisation; perform spectral unmixing; and visualise the results.

``` import ramanspy as rp

load data

image_data = rp.load.witec("")

apply a preprocessing pipeline

pipeline = rp.preprocessing.Pipeline([ rp.preprocessing.misc.Cropper(region=(700, 1800)), rp.preprocessing.despike.WhitakerHayes(), rp.preprocessing.denoise.SavGol(windowlength=9, polyorder=3), rp.preprocessing.baseline.ASPLS(), rp.preprocessing.normalise.MinMax() ]) data = pipeline.apply(imagedata)

perform spectral unmixing

nfindr = rp.analysis.unmix.NFINDR(n_endmembers=5) amaps, endmembers = nfindr.apply(data)

plot results

rp.plot.spectra(endmembers) rp.plot.image(amaps) rp.plot.show() ```

Documentation

For more information about the functionalities of the package, refer to the online documentation.

Credits

If you use RamanSPy for your research, please cite our paper:

Georgiev, D.; Pedersen, S. V.; Xie, R.; Fernández-Galiana, Á.; Stevens, M. M.; Barahona, M. RamanSPy: An open-source Python package for integrative Raman spectroscopy data analysis. ACS Analytical Chemistry 2024, 96(21), 8492-8500, DOI: 10.1021/acs.analchem.4c00383

bibtex @article{georgiev2024ramanspy, title={RamanSPy: An open-source Python package for integrative Raman spectroscopy data analysis}, author={Georgiev, Dimitar and Pedersen, Simon Vilms and Xie, Ruoxiao and Fern{\'a}ndez-Galiana, Alvaro and Stevens, Molly M and Barahona, Mauricio}, journal={Analytical Chemistry}, volume={96}, number={21}, pages={8492-8500}, year={2024}, doi={10.1021/acs.analchem.4c00383} }

Also, if you find RamanSPy useful, please consider leaving a star on GitHub.

Owner

Name: QIBEBT-SCC
Login: QIBEBT-SCC
Kind: organization

Repositories: 1
Profile: https://github.com/QIBEBT-SCC

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as follows."
authors:
  - family-names: Georgiev
    given-names: Dimitar
title: "RamanSPy"
repository-code: "https://github.com/barahona-research-group/RamanSPy"
preferred-citation:
  type: article
  authors:
  - family-names: Georgiev
    given-names: Dimitar
  - family-names: Pedersen
    given-names: Simon Vilms
  - family-names: Xie
    given-names: Ruoxiao
  - family-names: Fernández-Galiana
    given-names: Álvaro
  - family-names: Stevens
    given-names: Molly M.
  - family-names: Barahona
    given-names: Mauricio
  doi: "10.26434/chemrxiv-2023-m3xlm"
  journal: "ChemRxiv"
  title: "RamanSPy: An open-source Python package for integrative Raman spectroscopy data analysis"
  url: "https://chemrxiv.org/engage/chemrxiv/article-details/64a53861ba3e99daef8c9c51"
  year: 2023

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actions/checkout v3 composite
actions/setup-python v3 composite

pyproject.toml pypi

cvxopt *
matplotlib *
numpy *
pandas *
pybaselines *
pysptools *
renishawWiRE *
scikit-learn *
scipy *
wget *

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