simsnn 1.0.2

Radboud Spiking Neural Network Simulator

SimSNN

A spiking neural network simulator developed and maintained by Radboud University staff and students.

Requirements

To run the program, make sure you have installed the dependencies listed in environment.yml. We recommend creating a conda environment for every project. You can do this with the following command: conda env create --file environment.yml

Usage

On Google Colab

Click on the badge to open the notebook in google colab. Then run every cell to see the example output.

Locally using jupyter notebooks

Clone this repository or download the zipped version. Unzip and open a terminal in the project directory. From there you can install the conda requirements, as mentioned before. You can also run the notebook by running

jupyter lab ./example.ipynb

Locally from the command line

To run the example network, located in the examples directory, open up a terminal in the project directory and run the following command:

python -m simsnn

You should be presented with a read out from the connected measuring tools like this:

(see homepage if the image doesn't render correctly.)