omer-bio 0.1.1

Ce package contient un module d'Analyse Promethee et des fonctions necessaires pour cette analyse

Python package: omerbio

Metadata

• authors: [e-mail]
• creation date: 2025-08-19
• main usage: This repo contains the code for the omerbio python package. A Promethee multi-criteria analysis weighted by PCA.

Description

This package implements a multi-criteria analysis of data using Promethee method, with a weighing procedure based of principal components analysis (PCA).

Features

The main functions are:

• run_promethee_analysis: Execute the multi-criteria analysis
• generate_radar_plots: Generates a pdf with radar plots of individuals on a set of criteria.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

Before you begin, ensure you have met the following requirements:

• Operating System: Windows 10+, macOS 10.14+, or Linux
• Programming Language: [Python] version 3.6 or higher
• Package Manager: [pip] version 24.1 or higher
• Other dependencies: Python packages: matplotlib, pandas, numpy, Promethee, sklearn

Installing

Clone the repo and install the package localy (soon available via pip gitlab or pypi) :

git clone https://forge.inrae.fr/pfem/dev/libs/omerbio
cd src
pip install -e .

Running the tests

In the root folder of this repository run:

python -m unittest

This runs the unit test of the package functions.

Changelog

COMING SOON !

Authors

• Elfried Salanon - Initial idea and implentation - MTH, INRAE, UNH, PFEM
• Salomon Gouiri Loembe - First packaging work - INRAE, UNH, PFEM
• Marie Lefebvre - Project management - MTH, INRAE, UNH, PFEM
• Etienne Jules - Project management, final packaging, maintainer - MTH, INRAE, UNH, PFEM

License

Omerbio is distributed under the MIT License.

Please refer to LICENSE file for further details.

Support & External resources

• :book: Documentation - Coming soon !
• :bug: Bug Reports - GitLab Issues
• :email: Email - [e-mail]

Acknowledgments

• Thanks to Elfried Salanon, Salomon Gouiri Loembe, Marie Lefebvre and Etienne Jules for their valuable contributions
• Inspired by and built with Promethee python package
• Special thanks to the open-source community

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