NeuroAnalyzer tutorials: Download and install

Note: this toolbox is under active development and is subject to change.

First, download latest stable Julia version.

Multi-threading

Please note that Julia uses the JULIA_NUM_THREADS environmental variable to determine the number of threads available for the program.

For optimal performance this number should be > 1 and, depending upon your CPU number of cores, usually is equal or more than the number of cores.

For Unix-based systems (Linux, FreeBSD, MacOS) this may be set in the ~/.profile file or ~/.zshrc or ~/.bashrc (depending on your shell).

export JULIA_NUM_THREADS=12

The easiest way (which also works in Windows) it to set this variable in the Julia startup.jl file, located in ~/.julia/config directory:

ENV["JULIA_NUM_THREADS"] = 12
ENV["JULIA_NUM_PRECOMPILE_TASKS"] = 12

(!) Setting the JULIA_NUM_PRECOMPILE_TASKS variable speeds up packages precompilation process.

(!) Note that the 32-bit x86 architecture does not support threading due to lack of compiler runtime library support, so you may need to set JULIA_NUM_THREADS=0 and JULIA_NUM_PRECOMPILE_TASKS=0 if you’re on a 32-bit system.

(!) If you encounter the following error: dyld: Library not loaded: @rpath/libLLVM.dylib at pre-compilation, start Julia using:

julia --pkgimages=no

Installation using package manager

Since version 0.24.1, NeuroAnalyzer is registered in the Julia general registry. Therefore, the easiest way of installing the package is to press ] to enter the package mode, and then add this package:

(@v1.10) pkg> add NeuroAnalyzer

using Pkg
Pkg.add("NeuroAnalyzer.jl")

You may also manually add NeuroAnalyzer using Julia package manager:

using Pkg
Pkg.update()
Pkg.add(url="https://codeberg.org/AdamWysokinski/NeuroAnalyzer.jl")
Pkg.resolve() # if necessary
Pkg.update()

Installation using environment

Another option is to initialize a new Julia environment for the package:

git clone https://codeberg.org/AdamWysokinski/NeuroAnalyzer.jl
cd NeuroAnalyzer.jl
julia --project
# or (in which case you may ignore the line `Pkg.activate(@__DIR__)` below)
julia

Activate the package in the Julia REPL:

using Pkg
Pkg.activate(@__DIR__)
Pkg.instantiate()
Pkg.resolve() # if necessary
Pkg.update()

Downloading zipped release

Alternatively, you may download NeuroAnalyzer latest release:

unzip NeuroAnalyzer-*.zip
cd NeuroAnalyzer-*
julia --project
# or (in which case you may ignore the line `Pkg.activate(@__DIR__)` below)
julia

Activate the package in the Julia REPL:

using Pkg
Pkg.activate(@__DIR__)
Pkg.instantiate()
Pkg.resolve() # if necessary
Pkg.update()

Installation using LOAD_PATH variable

The third option is to extend the Julia LOAD_PATH variable in the ~/.julia/config/startup.jl with the NeuroAnalyzer folder (downloaded as cloned or zipped repository):

push!(LOAD_PATH, "path/to/NeuroAnalyzer/folder")

Running NeuroAnalyzer

Start Julia and in the Julia REPL do the following:

using NeuroAnalyzer

Due to the nature of Julia compiler, initial startup of NeuroAnalyzer takes several seconds. To speedup the process, creating a custom sysimage for reduced latency using PackageCompiler.jl is recommended. See this tutorial how to do it.

Show version and info (for reproducibility):

na_version()
na_info()

Get help:

?NeuroAnalyzer.plot

For interactive GUI, use Pluto and PlutoUI:

using Pkg
Pkg.add("Pluto")
Pkg.add("PlutoUI")
Pkg.add("Gtk")
using Pluto
Pluto.run()

Example Pluto notebook is located here.

For non-interactive GUI, use Jupyter:

using Pkg
Pkg.add("IJulia")
using IJulia
notebook()

Example Jupyter notebook is located here.

Docker image

NeuroAnalyzer is also available as the Docker image:

docker pull neuroanalyzer/neuroanalyzer:latest
xhost local:docker
docker run -e DISPLAY=:0 -v /tmp/.X11-unix:/tmp/.X11-unix -it neuroanalyzer