To use this fork of fmralign with conda package manager: Clone this package into your local directory, then:
conda create -n myenvname python=3.9
cd fmralign
pip install -e .
pip install -e .[jax]
Changes in this fork compared to parent fmralign package:
- surf_pairwise_alignment.py takes input images as numpy arrays instead of NIFTI
- template_alignment.py modified to take input images as numpy arrays instead of NIFTI
- Added template generation methods: hyperalignment, PCA method
- Added spatial regularization (Jeganathan et al., 2024, draft)
- Added ProMises model
- Added SCCA regularization (Xu et al., 2012)
Functional alignment for fMRI (functional Magnetic Resonance Imaging) data.
This light-weight Python library provides access to a range of functional alignment methods, including Procrustes and Optimal Transport. It is compatible with and inspired by Nilearn. Alternative implementations of these ideas can be found in the pymvpa or brainiak packages. The netrep library also offers many of the same metrics,though with a more general focus beyond fMRI data.
You can access the latest stable version of fmralign directly with the PyPi package installer:
pip install fmralign
For development or bleeding-edge features, fmralign can also be installed directly from source:
git clone https://github.com/Parietal-INRIA/fmralign.git
cd fmralign
pip install -e .
Note that if you want to use the JAX-accelerated optimal transport methods, you should also run:
pip install fmralign .[jax]
You can found an introduction to functional alignment, a user guide and some examples on how to use the package at https://parietal-inria.github.io/fmralign-docs.
This project is licensed under the Simplified BSD License.
This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 785907 (HBP SGA2). This project was supported by Digiteo.