A Python package for performing multivariate General Linear Model (GLM) analysis with GPU acceleration. This package is designed to handle complex and real data, providing efficient computations for large datasets using PyTorch.
- Multivariate GLM analysis with permutation tests
- GPU and CPU support
- Handles complex-valued data
- Missing data handling (beta)
- Interaction modeling for experimental designs
Set up PyTorch within your virtual environment.
Clone the repository and install the package using setup.py:
git clone https://github.com/mdarmstr/parglm_torch.git
cd parglm_torch
pip install .Translated from parglm from the MEDA toolbox: https://github.com/CoDaSLab/MEDA-Toolbox/
Michael Sorochan Armstrong, José Camacho
contact: mdarmstr(at)ugr.es
Copyright (C) 2025 Universidad de Granada
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.