Skip to main content

Open Raman Processing Library

Project description

ORPL

ORPL (read orpel) is the Open Raman Processing Library. It provides tools for the processing of Raman spectrum, including;

  1. System calibration (x-axis and system response)
  2. Cosmic Ray removal
  3. Baseline removal (autofluorescence)
  4. Spectrum analysis (peak finding, ...)
  5. Synthetic spectrum generation (for testing and benchmarking)

As of v1.0.0, ORPL also provides a Graphical User Interface. See demo below ;)

Table of content

ORPL GUI in action

https://user-images.githubusercontent.com/27356351/225768644-56ebf40a-51d1-44a1-bba3-edb86f8b1fad.mp4

Installation

At its core, ORPL is designed to be a processing library to use in your own processing workflow. Nevertheless, I also wrote a GUI to go with it if programming is not your jam. In either case, installation is made through pip.

Windows Installation Guide

I wrote a detailed installation guide for windows complete with screenshots of all the steps, so do not worry if you are a python beginer and have no idea what I'm talking about here. You can access the guide on github here or download a PDF version.

Already familiar with python and pip?

I recommend you create a virtual environment with venv. Otherwise, just install orplib with pip.

pip install orplib

Using Anaconda?... dont... Jokes aside, if people ask me about this, I might write a guide for this. Otherwise, use pip.

I'm new to python and this 'pip' thing?

I am working on a python tutorial repository, you can learn more about it here.

Updating ORPL to the latest version

If you want to update to the latest version of ORPL, run the following pip command,

If you have admin rights

pip install --upgrade orplib

If you do not have admin rights

pip install --upgrade --user orplib

Building from source

This is the command you need to run if you want to build the .whl from the source code yourself (make sure you run it from orpl's project root directory):

python -m build

and to update the build on pypi (this is a reminder for me, it won't do anything if you do this),

python -m twine upload --repository pypi --skip-existing dist/*

Baseline removal

BubbleFill

Bubblefill is a morphological processing algorithm designed for the removal of baselines in spectroscopic signal. It was created and optimized specifically to remove autofluorescence baselines in Raman spectra measured on biological samples.

Bubblefill in action

The tuning parameter of Bubblefill is the size of the smallest bubble allowed to grow. In general, the smallest bubble width should be chosen to be larger than the widest Raman peak present in the signal. Otherwise, the baseline fit will grow inside the peaks and the output Raman signal will have under expressed peaks.

Note : Bubbles can become arbitrarily small if they are growing along the leftmost or rightmost edge of the signal.

Bubblefill with bubbles that are too small

Different smallest bubble widths can be specified for different regions of the spectrum. This enables nearly infinite tuning of the algorithm and can be used to remove peaks that are known artifacts (for instance). In this example, the smallest bubble width for detector pixels 400 to 650 was set to 1 and to 100 for the rest of the x-axis.

Bubblefill with multiple smallest bubble widths

How to cite this work

Guillaume Sheehy, Fabien Picot, Frédérick Dallaire, Katherine Ember, Tien Nguyen, Kevin Petrecca, Dominique Trudel, and Frédéric Leblond "Open-sourced Raman spectroscopy data processing package implementing a baseline removal algorithm validated from multiple datasets acquired in human tissue and biofluids," Journal of Biomedical Optics 28(2), 025002 (21 February 2023). https://doi.org/10.1117/1.JBO.28.2.025002

BibTex (.bib)

@article{10.1117/1.JBO.28.2.025002,
author = {Guillaume Sheehy and Fabien Picot and Fr{\'e}d{\'e}rick Dallaire and Katherine Ember and Tien Nguyen and Kevin Petrecca and Dominique Trudel and Fr{\'e}d{\'e}ric Leblond},
title = {{Open-sourced Raman spectroscopy data processing package implementing a baseline removal algorithm validated from multiple datasets acquired in human tissue and biofluids}},
volume = {28},
journal = {Journal of Biomedical Optics},
number = {2},
publisher = {SPIE},
pages = {025002},
keywords = {Raman spectroscopy, fluorescence, tissue optics, open-sourced software, machine learning, optics, Raman spectroscopy, Data processing, Bubbles, Equipment, Tissues, Biological samples, Raman scattering, Fluorescence, Aluminum, Spectroscopy},
year = {2023},
doi = {10.1117/1.JBO.28.2.025002},
URL = {https://doi.org/10.1117/1.JBO.28.2.025002}
}

EndNote (.enw)

%0 Journal Article
%A Sheehy, Guillaume
%A Picot, Fabien
%A Dallaire, Frédérick
%A Ember, Katherine
%A Nguyen, Tien
%A Petrecca, Kevin
%A Trudel, Dominique
%A Leblond, Frédéric
%T Open-sourced Raman spectroscopy data processing package implementing a baseline removal algorithm validated from multiple datasets acquired in human tissue and biofluids
%V 28
%J Journal of Biomedical Optics
%N 2
%P 025002
%D 2023
%U https://doi.org/10.1117/1.JBO.28.2.025002
%DOI 10.1117/1.JBO.28.2.025002
%I SPIE

Contributors

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

orplib-1.0.4.tar.gz (52.7 kB view details)

Uploaded Source

Built Distribution

orplib-1.0.4-py3-none-any.whl (54.1 kB view details)

Uploaded Python 3

File details

Details for the file orplib-1.0.4.tar.gz.

File metadata

  • Download URL: orplib-1.0.4.tar.gz
  • Upload date:
  • Size: 52.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.16

File hashes

Hashes for orplib-1.0.4.tar.gz
Algorithm Hash digest
SHA256 1f5819ac7e4daa6e800247e1fdd44e03d1c98882784e59683845948986214e2e
MD5 75be6ce14bc840152f2d88113ff8342b
BLAKE2b-256 4eade67c09f5acb9e5f60ac1e8015aa464e3171333451622070b776b5beb8ab7

See more details on using hashes here.

File details

Details for the file orplib-1.0.4-py3-none-any.whl.

File metadata

  • Download URL: orplib-1.0.4-py3-none-any.whl
  • Upload date:
  • Size: 54.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.16

File hashes

Hashes for orplib-1.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 0c0c39c0c08decbd96421d9024d5e6d3525e2e555a78b8c085c666bd9c3c382a
MD5 a9669bd2f1f5b021b6e1e000c88cbf67
BLAKE2b-256 dd1c6071c989ea3a5167f3850e686d23fb9f80665ae805f7769316be79879651

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page