CHARISMA - Raman spectrum harmonization

This is the GIT development platform for algorithms that generate CHADA (characteristic data) from a given Raman spectrum. It refers to CHARISMA Work Package 4.

Quick Start for users

Pip

NOTE: It is usually a good idea to use a virtual environment.

pip install -r requirements.txt
jupyter notebook

Conda

Install Conda, then run the following:

conda env update -f environment.yml
conda activate ramanchada
jupyter notebook

Docker (on Linux)

WARNING: This will produce files in the test directory that will be owned by root. To fix it, do sudo rm -r test, followed by git checkout -- test. An enhanced procedure without this problem may be introduced in the future.

Install Docker, then run the following:

docker pull python
docker run -it --rm -p 8888:8888 -v "${PWD}":/work python /bin/bash

In the container, run:

cd work
pip install -r requirements.txt
jupyter notebook --ip 0.0.0.0 --allow-root --no-browser

Quick Start for contributors

Please see the Contributor Guide.

What is the CHARISMA Project ?

• Visit the CHARISMA Home Page !

What is CHADA ?

• CHAracterization DAta

ramanchada package

You have to install ramanchada package before using the notebooks - see Quick Start above.

Relevant use cases: what will CHADA be used for ?

[List of CHADA use cases](documents/Use cases CHADA.xlsx): This is a living document - please add to it! Download, then replace by the changed doc.

• Use cases implemented in the current version of the CHADA library
  • General demonstration of Chada class and data structure
  • Demonstration of Chada generation from various text and CSV-based manufacturer formats
  • Demonstration of CHADA Groups and their functions
  • Demonstration of CHADA wavenumber (x axis) calibration using a refernece spectrum

Relevant Raman manufacturers, OEM software, and file formats

[List of relevant manufacturers and file formats](documents/Raman data formats.xlsx)

CHADA data structure

Description of CHADA data structure

Chemometric methods for Raman data implemented in CHADA

Chamometrics Review from CHARISMA WP3

WWW resources (Please add by entering README.md in EDIT mode!)

Readers

• specio Python library for Spectroscopy I/O: https://specio.readthedocs.io/en/stable/sec_user.html
• spc file format: https://docuri.com/download/spc-file-format_59c1d322f581710b28653306_pdf
• gwyddion file formats: http://gwyddion.net/documentation/user-guide-en/file-formats.html
• wit_io repository (Matlab implementation of WITec SUITE): https://gitlab.com/jtholmi/wit_io
• Formats on Spectroscopy Ninja: https://www.effemm2.de/info/info_free_sw.html

Baseline separation

• Python code for SNIP: https://stackoverflow.com/questions/57350711/baseline-correction-for-spectroscopic-data, https://stackoverflow.com/questions/57350711/baseline-correction-for-spectroscopic-data
• Python code for ALS: https://stackoverflow.com/questions/29156532/python-baseline-correction-library

Spectrum calibration

• Affine transforms: https://scipy-lectures.org/packages/scikit-image/auto_examples/plot_features.html
• Rascal Python library for automated spectrometer wavelength calibration: https://pypi.org/project/rascal/, https://arxiv.org/abs/1912.05883
• xcal_raman Python functions for wavenumber calibration of Raman spectrometers: https://pypi.org/project/xcal_raman/
• Scikit-spectra: Explorative Spectroscopy in Python: https://openresearchsoftware.metajnl.com/articles/10.5334/jors.bs/

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🇪🇺 This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 952921.