nistats

Nistats is a Python module for fast and easy modeling and statistical analysis of functional Magnetic Resonance Imaging data.

It leverages the nilearn Python toolbox for neuroimaging data manipulation (data downloading, visualization, masking).

This work is made available by a community of people, amongst which the INRIA Parietal Project Team and D'esposito lab at Berkeley, in particular G. Varoquaux, B. Thirion, J.B. Poline and M. Brett.

It is based on developments initiated in the nipy nipy project.

Important links

• Official source code repo: https://github.com/nistats/nistats/
• HTML documentation (stable release): http://nistats.github.io/

Dependencies

The required dependencies to use the software are:

• Python >= 2.6
• setuptools
• Numpy >= 1.6.1
• SciPy >= 0.9
• Nibabel >= 1.1.0
• Nilearn >= 0.1.3
• Pandas >= 0.12

If you are using nilearn plotting functionalities or running the examples, matplotlib >= 1.1.1 is required.

If you want to run the tests, you need nose >= 1.2.1 and coverage >= 3.6.

Install

Not available at the moment

Development

Code

GIT

You can check the latest sources with the command:

git clone git://github.com/nistats/nistats

or if you have write privileges:

git clone [email protected]:nistats/nistats