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Installation instructions for Windows via WSL

WSL Configuration

Clock on Windows host

If Windows host time is not correct, it should be corrected in Settings/'Time and language' (choose 'Set time automatically', 'Set time zone automatically' and 'Synchronize clock' with 'Synchronize now')

Restart the machine

Installing WSL and Ubuntu

WSL (Windows Subsystem for Linux) lets developers run a GNU/Linux environment directly on Windows, without traditional virtual machine.

Run Windows Powershell as an administrator (right click)

Type the following in the command prompt of Windows Powershell

  • If Windows 11

wsl --install Ubuntu-22.04

  • If Windows 10

wsl --install -d Ubuntu-22.04

Ubuntu credentials

If WSL and Ubuntu installations have been successful, an Ubuntu window opens. Then the user is proposed to create an identifier with an associated password (to be memorized).

Updating WSL and using Ubuntu in WSL2 version

Close Ubuntu window and return to Windows Powershell window.

Type the following in the command prompt (it may take a few minutes)

wsl --update

wsl --set-version Ubuntu-22.04 2

Ubuntu Setup

Open Ubuntu window again by clicking on the corresponding icon in Windows menu and type the following

sudo apt update

then answer 'Y'

sudo apt upgrade

then answer 'Y'

sudo apt install x11-apps libarchive13

then answer 'Y'

Requirements

Conda is a package management system and environment management system.

The easiest and fastest way to get the package up and running is to install miniconda and to use mamba, which is much faster than conda.

Type the following two lines in Ubuntu to install conda from miniconda

wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh

bash Miniconda3-latest-Linux-x86_64.sh

then 'Enter'

space (several times),

'yes'

'ENTER' (default)

Answer 'yes' to (conda init)

Close and reopen Ubuntu window.

To install mamba, run what follows

conda install -c conda-forge mamba

(answer 'yes')

Setting up the conda environment

We recommend installing nm-bridge into a separate environment called neuromod, see conda's documentation for more details. To do so, use:

mamba create -n neuromod

conda activate neuromod

In the neuromod environment, we will need several dependencies, used in the demo script, which we install as follows

mamba install -c conda-forge r-igraph jupyter

(answer 'yes')

Installing nm-bridge

We install nm-bridge in the neuromod environment as follows:

mamba install -c neuromod -c conda-forge nm-bridge python=3.10

(answer 'yes')

Updating nm-bridge

In case of update of nm-bridge, run inside the neuromod environment, in Ubuntu window

mamba update -c neuromod -c conda-forge nm-bridge