Installation

pNet is installable via pip:

pip install fmripnet

pNet is accessbile via docker:

docker pull mldataanalytics/fmripnet:latest

or:

docker pull ghcr.io/mldataanalytics/fmripnet:latest

run:

docker run mldataanalytics/fmripnet -h

Alternatively, you can install the most up-to-date version of from GitHub:

git clone https://github.com/MLDataAnalytics/pNet.git
cd pNet
conda env create --name fmripnet -f environment_pnet.yml
pip install .

Note that pnet requires Python 3.8+ and some key dependencies:

• h5py

• mesalib

• nibabel

• numpy

• pandas

• pip

• python==3.8.13

• pytorch==2.1.0

• scikit-image

• scikit-learn

• scipy

• vtk>=9.2=*osmesa*

• ggplot

• matplotlib

• plotnine

• statsmodels

• surfplot

• tomli

Support:

If you encounter problems or bugs with pNet, or have questions or improvement suggestions, please feel free to get in touch via the Github issues: https://github.com/MLDataAnalytics/pNet/issues.

Previous versions:

• Matlab and Python: https://github.com/MLDataAnalytics/pNet_Matlab

• Matlab: https://github.com/MLDataAnalytics/Collaborative_Brain_Decomposition

• GIG-ICA: https://www.nitrc.org/projects/gig-ica/

Other useful packages:

• brainspace: https://brainspace.readthedocs.io/en/latest/index.html

• matplotlib: https://matplotlib.org/

• numpy: https://numpy.org/

• nibabel: https://nipy.org/nibabel/

• vtk: https://vtk.org/

• nilearn: https://nilearn.github.io/index.html

• neuromaps: https://netneurolab.github.io/neuromaps/