CNM is a powerful Python package tailored for computational neuroscience modeling. With its user-friendly design and flexibility, it serves as an invaluable tool for constructing and running simulations of neural networks and other computational models in the realm of neuroscience. It is designed to be a GUI simulator later, letting researchers use and infer various models available.
There are a plethora of models available. We will be using some of the most common models out there.

How to use it?

The project will soon be available in Pypi. Since it’s in the early progress, few models will be available and constantly get updated/added. You can install it using git for now.
git clone https://github.com/Da4kek/CNM.git

Usage:

cd CNM
The repository’s README.md will give the theoretical aspects of the project, including the classification of models and hierarchy of the project.
Check out the Example_usage.ipynb for reference.

Classes available:

src.algorithms
src.models
         |_ src.Descriptive
         |_ src.Interpretive
         |_ src.Mechanistic
src.utils

src.algorithms:

Contains algorithms necessary to preprocess the data/input (optional).
usage: from src.algorithms import *

src.models:

Contains model classified into 3 categories according to D.Marr (Descriptive, Interpretive, and Mechanistic).
usage: from src.models import *
Descriptive.NRM, Descriptive.PRM and Descriptive.NFM (Stands for Neural firing rate models, Population rate models, and Neural field models).
Interpretive.IFM and Interpretive.GLM (Stands for Integrate-and-Fire models, and Generalized linear models).
Mechanistic.HH, Mechanistic.SYN, Mechanistic.BIO (Stands for Hodgkin-Huxley model, Synaptic models, and Biophysical models).
Each model is different in their mathematical and theoretical ways.

src.utils:

Contains utility functions such as plotting and other constant functions (optional).
usage: from src.utils import *

Note:

The project is open source, anyone can contribute in any way possible. Feel free to open an issue or pull request to contribute.
Project link: CNM