A package for STEM-EDX data processing and analysis
Project description
STEM-EDX ML
Full documentation available here : https://edx-ai-84a865.gitlab.io/
Description
STEM-EDX ML is a graphical application designed for managing and analyzing STEM-EDX (Scanning Transmission Electron Microscopy - Energy Dispersive X-ray Spectroscopy) data using machine learning algorithms.
The graphical user interface, built with PySide6, allows users to:
- Load STEM-EDX data files (.pts)
- Visualize images and spectra
- Apply decomposition algorithms such as PCA (Principal Component Analysis) and NMF (Non-negative Matrix Factorization)
- Interact with results through dynamic graphs
Features
- Load and manage STEM-EDX data files
- Select and display analyzed objects
- Apply and visualize PCA and NMF results
- Interactive and responsive user interface
Scientific Context
This project is based on STEM-EDX measurement results. The full study framework and experimental details can be found in the "Report" (in French) located in the Presentations folder.
Installation
Installation of Hyperspy and Exspy
Run the following commands:
conda install hyperspy -c conda-forge
conda install exspy
Prerequisites
- Python 3.x
- Hyperspy for spectral analysis
- Exspy (exspy) for TEM-EELS data type managment
- PySide6 for the graphical interface
Installation with pip
Run the following commands:
pip install EDX-AI
Usage
Run the application with the following command:
EDX-AI
Project structure
STEM-EDX-ML/
│── mainwindow.py # Main graphical interface
│── stem.py # STEM-EDX data management and ML algorithms
│── utils.py # Utility functions and widget management
|── colorscales.py # Colorscales available
|── main.py # The main program to execute
License
This project is licensed under the MIT License. See the LICENSE file for more details.
Author
Anthony Pecquenard, 2025.
Project details
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