Please refer to the main Gitlab repository for source code and more details

VS2N (Visualization tool for Spiking Neural Networks) is an interactive web-based tool. It is designed to analyze and visualize the activity we collect from SNN simulators.

We can use VS2N to:

• Follow the evolution of our network during training.
• Validate hypotheses.
• Debug any newly implemented component.

VS2N is a module-based tool written in Python, those modules concern defined questions or elements to visualize, and it is possible to add new modules. Each module contains different visualizations.

Initial requirements for contributions :

• Python (Flask)
• Dash Plotly (to implement different visualizations)
• Apache Spark (for any heavy pre-calculations if needed)
• MongoDB (to store and read data)

https://gitlab.univ-lille.fr/bioinsp/VS2N/-/wikis/home

Use the following link to install MongoDB.

Execute this command to install the needed libraries

pip install -r requirements.txt

1. If you want to add authentication to VS2N (optional):

• Generate users credentials (Email/Password) using python manageUsers.py

2. Rename default.config.py to config.py

3. If a password protects MongoDB:

• Add MongoDB credentials in config.py

4. Using Python >= 3.0 (make sure MongoDB is running) run python VS2N.py to start VS2N. If everything is fine, the web interface should appear automatically.

You can also use a docker image to run VS2N : https://hub.docker.com/r/helbez/vs2n

VS2N.py             # Main script to start VS2N.
addUser.py          # Generate user credentials.
defaut.config.py    # Default configuration file.
img/                # Folder contains images.
Docker/             # Contains docker files.
assets/             # Folder contains CSS file.
src/                # Source directory.
|- Modules/         # Folder of the existing modules.
|- static/          # Contains static files (.js, .css, etc).
|- templates/       # Static html files + template for new modules.
|- Global_Var.py    # Contains global variables of VS2N.

• Multilayer support added
• Spark & MongoDB version updated

• Graphs improved & fixed typos.
• UI updated.

• Added authentication.
• Added support for Nengo simulator.

View the full changes log here

In case you decide to mention or use VS2N:

H. Elbez, M. K. Benhaoua, P. Devienne and P. Boulet, "VS2N : Interactive Dynamic Visualization and Analysis Tool for Spiking Neural Networks," 2021 International Conference on Content-Based Multimedia Indexing (CBMI), pp. 1-6, 2021.

The project is licensed under the CeCILL-B license.