A Graphical User Interface (GUI) for the Probability Learning on Manifolds (PLoM) framework.
PLoM-GUI is a user-friendly interface for the PLoM framework, designed to simplify the process of probability learning on manifolds. It provides an interactive environment for data analysis, visualization, and model building without the need for extensive coding.
- Intuitive graphical interface for PLoM functionalities
- Data import and preprocessing tools
- Visualization of datasets and manifold structures
- Data sampling on manifold
- Interactive parameter tuning and real-time feedback
- Feature importance ranking
- Automation of forward model(s) consturction
- Python 3.6 or higher
- Required Python packages (listed in
requirements.txt)
git clone https://github.com/philippehawi/PLoM-GUI.git
cd PLoM-GUIThis GUI package requires, among others, the PLoM Python package. To install this dependency, run the following command from the root of PLoM-GUI.
pip3 install -r requirements.txtAfter downloading the repository, run the following command from the root of PLoM-GUI.
pip3 install .If the above command hangs on Windows WSL2, you may need to clear the DISPLAY environment variable first:
export DISPLAY=To launch the PLoM-GUI application, run the following command from the terminal:
plom-guiNOTE: You might need to add the directory where Python places the installed scripts to your system’s PATH environment variable. During the installation of this package, a warning is usually displayed if this scripts directory is not in PATH, and the full path is printed. An example of the scripts path on Windows:
C:\Users\<YourUser>\AppData\Roaming\Python\PythonXX\Scripts\Follow the on-screen instructions to load your dataset, configure parameters, and start the analysis.
Explore the examples directory for sample datasets and projects to help you get started with PLoM-GUI.
Contributions are welcome! Please read our contribution guidelines before submitting a pull request.
This project is licensed under the MIT License. See the LICENSE file for details.
For questions or feedback, please contact:
- Philippe Hawi - philippehawi@gmail.com