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NeuronetExperimenter Installation Guide

Updated: 03/18/2025

Since NeuronetExperimenter generates optimized C++ code from your models, you need to be able to generate an executable binary on your system. This requires several free development tools. Most of these tools should be accessible on any Unix-compatible system (i.e., Linux, OS X, *BSD, Solaris, etc.).

Required Tools:

GCC 11.X+ - The Gnu Compiler Collection
Python 3.9.X+ - The Python Programming Language Interpreter
GSL - The Gnu Scientific Library for random number generation
OpenMPI - A library for parallel processing communication
Conda - A tool for managing a customized Python environment specific to NeuronetExperimenter
NeuronetExperimenter

!!!! - IMPORTANT - !!!!

To simplify the installation we assume that you do not have root or administrator access to your computer. In that case, we will put all the tools in the user's home directory tree.

cd $HOME
mkdir bin include lib

Installing GCC

Linux, Solaris, and *BSD:

GCC is typically installed by default on most Linux distributions or can be selected as an additional package to include during installation.

macOS:

GCC is usually NOT installed by default on macOS. Instead, macOS uses Clang which masquerades as GCC. This is included in Xcode with the Apple Developer Command Line Tools and can be installed from the Terminal.app by typing "

xcode-select




            --install"

or you can try the following link: https://developer.apple.com/download/more/.

Installing Python

A Python interpreter should already be installed on most Unix-compatible systems. You can confirm this by typing,

python -V

at a command terminal. This will return the Python version that is installed. If the command is not recognized, you can download and install the package from http://www.python.org.

Installing GSL

Download the latest stable version of GSL from the developer's website: http://www.gnu.org/software/gsl/. For example, https://mirror.ibcp.fr/pub/gnu/gsl/gsl-latest.tar.gz.

Unpack the source code and build the code as follows (note the comment in blue):

mkdir ~/src
cd ~/src
mv ~/Downloads/gsl-latest.tar.gz ~/src
tar zxvf gsl-latest.tar.gz
cd gsl-2.8
./configure --prefix=$HOME
make
make install

Installing Open MPI

Download the latest stable version of Open MPI from the developer's website: http://www.open-mpi.org/. For example, https://download.open-mpi.org/release/open-mpi/v5.0/openmpi-5.0.6.tar.gz.

Unpack the source code and build the code as follows (note the comment in blue):

cd ~/src
mv ~/Downloads/openmpi-5.0.6.tar.gz ~/src
tar zxvf openmpi-5.0.6.tar.gz
cd openmpi-5.0.6
./configure --prefix=$HOME
make
make install

Installing Conda

Download and install the latest stable version of Miniconda from the website.

Installing the nne_env Conda Environment

Download the latest stable version of nne from the Sourceforge website.

Unpack the nne source code as follows:

tar zxvf NeuronetExperimenter-4.0.1.tar.gz
cd NeuronetExperimenter-4.0.1

Before building the source code of nne, you must create and activate the Conda nne_env environment as follows:

conda env create -f nne_env.yml
conda activate nne_env

Note: You must only 'create' the Conda environment once; however, to compile and run the nne tools you must have 'activate'd the nne_env environment.

Compiling NeuronetExperimenter

In the nne_env Conda environment, compile the core nne simulator:

./configure --prefix=$HOME
make # this builds an executable binary of the core simulator w/o the models included
make install # this makes the binary accessible from anywhere on your file system

After that, you should be able to type the following to enter the NeuronetExperimenter's interactive mode (program output in GREEN):

NeuronetExperimenter interactive mode

nne_run

Welcome to NeuronetExperimenter (nne) v4.0
Copyright (C) 2006-2024, J. A. Hayes and J. L. Mendenhall

Neurons this binary supports:

Select one from the following menu:
-1. Enter manually
0. Use the same setup and network file as last time
1. ../
2. docs/
3. include/
4. models/
5. scripts/
6. src/

Ctrl-C to exit

Now if everything is installed, you should be able to go through the tutorials without any problems.

>>Tutorial #1. Building and Running a Simple Single-Neuron Simulation