pypreprocess is a collection of python scripts for preprocessing (motion correction, spatial normalization, smoothing, etc.) fMRI data using nipype's SPM and FSL interfaces. It also contains utilities for automatic QA like registration checks (using nipy.labs), and template-based html report generation using (tempita, jquery, and home-grown css).
These days, it also contains pure-Python (no C extensions, no compiled code, just Python) modules and scripts for slice-timing correction, motion correction, coregistration, and smoothing, without need for nipype or matlab.
Check out the wiki at https://github.com/neurospin/pypreprocess/wiki.
This work is made available by the INRIA Parietal Project Team.
- Official source code repo: https://github.com/neurospin/pypreprocess
- Python >= 2.6
- Numpy >= 1.3
- SciPy >= 0.7
- matplotlib >= 0.99.1
- nibabel >= 1.3.0
- networkx >= 1.7
- traits >= 4.3.0
- sympy >= 0.7.4.1
- nipype >= 0.8.0
- nipy >= 0.3.0
Ensure that you have the above dependencies installed. Then run:
python setup.py install --user
To install for all users on Unix/Linux:
python setup.py build
sudo python setup.py installWe have written some examplary scripts for preprocessing some popular datasets.
cd to the pypreprocess/examples directory, and run the following command:
python nipype_preproc_spm_auditory.py
Now open the file spm_auditory_runs/sub001/report.html in your browser (firefox), to see the generate report (QA).
The scripts/ sub-folder contains scripts for preprocessing popular datasets like ABIDE, HCP, HAXBY2001, NYU rest, etc. They should work 'out-of-the-box'.
cd to the pypreprocess/examples directory, and run the following command:
python purepython_preproc_demo.py
You can check the latest sources with the command:
git clone git://github.com/neurospin/pypreprocess.gitor if you have write privileges:
git clone git@github.com:neurospin/pypreprocess.git