pyTA

py Total Activation (pyTA) implements the Total Activation approach (ie deconvolution via a spatial and temporal total variation constraint for fMRI data).

[1] F. I. Karahanoglu, C. Caballero Gaudes, F. Lazeyras, D. Van De Ville, "Total Activation: FMRI Deconvolution through Spatio-Temporal Regularization", NeuroImage, vol. 73, pp. 121-134, 2013

Important links

• Official source code repo: https://github.com/hcherkaoui/pyta
• Original Matlab implementation: https://miplab.epfl.ch/index.php/software/total-activation

Dependencies

• numpy >= 1.14.0
• numba >= 0.48.0
• scipy >= 1.0.0
• joblib >= 0.11
• prox_tv
• carpet
• matplotlib >= 2.1.2 (for examples)

Install

In order to perform the installation, run the following command from the pyTA directory:

pip install -r 'joblib>=0.11' 'numpy>=1.14.0' 'scipy>=1.0.0' 'scikit-learn>=0.19.2' 'matplotlib>=2.1.2' 'prox_tv' 'carpet'
python setup.py install --user

Testing

In order to perform the unit tests, run the following command from the pyTA directory:

pip install pytest --user
pytest

Development

You can check the latest sources with the command:

git clone https://github.com/hcherkaoui/pyta