Scilpy is the main library supporting research and development at the Sherbrooke Connectivity Imaging Lab (SCIL).
Scilpy mainly comprises tools and utilities to quickly work with diffusion MRI. Most of the tools are based on or are wrappers of the DIPY library, and most of them will eventually be migrated to DIPY. Those tools implement the recommended workflows and parameters used in the lab.
The library is now built for Python 3.10 so be sure to create a virtual environnement for Python 3.10. If this version is not installed on your computer:
sudo add-apt-repository ppa:deadsnakes/ppa
sudo apt-get install python3.10 python3.10-dev python3.10-venv python3.10-minimal python3.10-tk
Make sure your pip is up-to-date before trying to install:
pip install --upgrade pip
The library's structure is mostly aligned on that of DIPY.
scilpy 1.6.0 is based on hot_dipy a fork of dipy locked before release v1.8.0. In order to install the library and scripts flawlessly (we hope), please follow these instructions:
pip install packaging>=19.0
pip install numpy==1.23.*
pip install Cython==0.29.*
pip install -e .
The library and scripts can be installed locally by using:
pip install -e .
On Linux, most likely you will have to install libraries for COMMIT/AMICO
sudo apt install libblas-dev liblapack-dev
While on MacOS you will have to use (most likely)
brew install openblas lapack
On Ubuntu >=20.04, you will have to install libraries for matplotlib
sudo apt install libfreetype6-dev
Note that using this technique will make it harder to remove the scripts when changing versions. We highly recommend working in a Python Virtual Environment.
Scilpy documentation is available: https://scilpy.readthedocs.io/en/latest/