spectrapepper

spectrapepper: A Python toolbox for advanced analysis of spectroscopic data for materials and devices. - Published in JOSS (2021)

https://github.com/spectrapepper/spectrapepper

Science Score: 95.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
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codemeta.json file
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DOI references
Found 6 DOI reference(s) in README and JOSS metadata
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Links to: joss.theoj.org
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1 of 10 committers (10.0%) from academic institutions
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JOSS paper metadata
Published in Journal of Open Source Software

Scientific Fields

Mathematics Computer Science - 84% confidence

Last synced: 6 months ago · JSON representation

Repository

A Python package for advanced processing and combinatorial analysis of spectroscopy data.

Basic Info

Host: GitHub
Owner: spectrapepper
License: mit
Language: Python
Default Branch: main
Size: 9.04 MB

Statistics

Stars: 16
Watchers: 3
Forks: 5
Open Issues: 1
Releases: 21

Created almost 5 years ago · Last pushed over 1 year ago

Metadata Files

Readme Contributing License Zenodo

README.md

A Python package to simplify and accelerate analysis of spectroscopy data.

GitHub repo: https://github.com/spectrapepper/spectrapepper
Documentation: https://spectrapepper.github.io/spectrapepper
PyPI: https://pypi.python.org/pypi/spectrapepper
Conda-forge: https://anaconda.org/conda-forge/spectrapepper
Free software: MIT license

Introduction

spectrapepper is a Python package that makes advanced analysis of spectroscopic data easy and accessible through straightforward, simple, and intuitive code. This library contains functions for every stage of spectroscopic methodologies, including data acquisition, pre-processing, processing, and analysis. In particular, advanced and high statistic methods are intended to facilitate, namely combinatorial analysis and machine learning, allowing also fast and automated traditional methods.

Features

The following is a short list of some main procedures that spectrapepper package enables.

Baseline removal functions.
Normalization methods.
Noise filters, trimming tools, and despiking methods.
Chemometric algorithms to find peaks, fit curves, and deconvolution of spectra.
Combinatorial analysis tools, such as Spearman, Pearson, and n-dimensional correlation coefficients.
Tools for Machine Learning applications, such as data merging, randomization, and decision boundaries.
Sample data and examples.

Quickstart

Install this library using pip:
```
pip install spectrapepper
```

Install this library using conda-forge:

conda install -c conda-forge spectrapepper

Test it by plotting some data:

import spectrapepper as spep
import matplotlib.pyplot as plt

x, y = spep.load_spectras()
for i in y:
    plt.plot(x, i)
plt.xlabel('Raman shift ($cm^{-1}$)')
plt.ylabel('Intensity (a.u.)')
plt.show()

If you find this library useful, please consider a reference or citation as:

Grau-Luque et al., (2021). spectrapepper: A Python toolbox for advanced analysis
of spectroscopic data for materials and devices. Journal of Open Source Software,
6(67), 3781, https://doi.org/10.21105/joss.03781

Stay up-to-date by updating the library using:

conda update spectrapepper pip install --update spectrapepper
If you encounter problems when updating, try uninstalling and then re-installing::
```
pip uninstall spectrapepper
conda remove spectrapepper
```

Credits

This package was created with Cookiecutter and the giswqs/pypackage project template.

JOSS Publication

spectrapepper: A Python toolbox for advanced analysis of spectroscopic data for materials and devices.

Published

November 19, 2021

DOI

10.21105/joss.03781

Volume 6, Issue 67, Page 3781