RamanSPy

<p align="center"> <a href="https://ramanspy.readthedocs.io/"> <img src="https://github.com/barahona-research-group/RamanSPy/blob/1121738ca4b8b64d938b81eefe32059ac33ace8e/docs/source/images/raman_logo_transparent.png" alt="RamanSPy logo" width="300"> </a> </p>

RamanSPy: An open-source package for <ins>Raman</ins> <ins>S</ins>pectroscopy analytics in <ins>Py</ins>thon.

Key features

• 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:

consoleCopy
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("<PATH>")

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

# 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

bibtexCopy
@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.