Installation
installations.Rmd
This page walks through the installation of ModelArray
package and necessary dependent packages/libraries. If you have
difficulty installing necessary packages (e.g., on HPC clusters), you
also have an option to use the container image of
ModelArray + ConFixel
. Please refer to
vignette("container")
for more.
We’ll directly install ModelArray
from GitHub. Please notice
that, this is only fully tested and supported on Linux Ubuntu system and
macOS system. If you are a Windows user, you will face errors when
running with more than one CPU cores
(n_cores = 2 or above
). You may install a Linux subsystem
or virtual machine on your Windows computer; or using the container
image of ModelArray
and running on High Performance
Computing (HPC) clusters (see vignette("container")
for
more).
We will first set up the conda environment, then install some
dependent packages and libraries, and finally install
ModelArray
.
Set up a conda environment
We first create a conda environment modelarray
for
installing the companion software ConFixel
etc. We’ll
install python version 3.9:
foo@bar:~$ conda create --name modelarray python=3.9
foo@bar:~$ conda activate modelarray
Install MRtrix (Only required for fixel-wise data)
When converting fixel-wise data’s format (.mif
),
ConFixel
uses function mrconvert
from MRtrix,
so please make sure MRtrix has been installed. It can either be
installed via conda
in this conda environment we just
created, or be compiled from source. See MRtrix’s webpage for more.
Type mrview
in the terminal to check whether MRtrix
installation is successful.
If your input data is voxel-wise data, you can skip this step.
Install HDF5 libraries in the system
Because ModelArray works with the Hierarchical Data Format 5 (HDF5) file format, we need to make sure necessary libraries of HDF5 are installed in the system.
On a Linux Ubuntu system
If you’re on Linux Ubuntu system: First, please check if
libhdf5-dev
has been installed in the system:
foo@bar:~$ ldconfig -p | grep libhdf5*
If you got more than one line of outputs, congrats, you have
libhdf5-dev
installed. Otherwise, please install it
via:
foo@bar:~$ sudo apt-get update -y
foo@bar:~$ sudo apt-get install -y libhdf5-dev
On a macOS system
Use Homebrew
to install:
foo@bar:~$ brew install hdf5
For details you may refer to the webpage here
Install ConFixel python package from GitHub
ConFixel provides
file format conversion for both fixel-wise data (.mif
) and
voxel-wise data (NIfTI). Follow the commands below to install it from
GitHub:
# We first activate the conda environment we just created:
foo@bar:~$ conda activate modelarray
# Then install ConFixel:
foo@bar:~$ cd ~/myProject
foo@bar:myProject$ git clone https://github.com/PennLINC/ConFixel.git
foo@bar:myProject$ cd ConFixel
foo@bar:myProject$ pip install .
# You may remove the original source code if you are an end user instead of a developer:
foo@bar:myProject$ cd ..
foo@bar:myProject$ rm -r ConFixel
Install R
ModelArray
requires R >=4.1.2, and we currently only
tests ModelArray on R 4.1.2. If you have already installed it, you can
skip this step. If you don’t, you may download it from CRAN.
(Optional) Install RStudio
RStudio provides a good IDE for using R. However it’s optional to install RStudio. If you haven’t got one but want to install it, you may download it from here.
Install ModelArray R package from GitHub
ModelArray R package’s source code is available on GitHub. To install it in R:
# First, load library "devtools":
library(devtools)
# if you got error, it means you don't have devtools installed, please install it by: install.packages("devtools")
# Then, install ModelArray:
devtools::install_github("PennLINC/ModelArray")
Now, ModelArray is ready to use:
(Optional) Other potential packages only needed for downloading demo
data in vignette("walkthrough")
page
There are several potential packages only needed for downloading demo
data in vignette("walkthrough")
page. You may skip this
step if you will not use the demo data.
- wget
- tar
If you don’t have them, please install them first. For macOS system,
you may try out brew
to install them. For Linux Ubuntu
system, you may try out sudo apt-get
to install them.