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Python toolbox for analyzing imaging data
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Python toolbox for analyzing neuroimaging data. It is particularly useful for conducting multivariate analyses. It is originally based on Tor Wager's object oriented matlab canlab core tools and relies heavily on nilearn and scikit learn. Nltools is compatible with Python 3.6+. Python 2.7 was only supported through 0.3.11. We will no longer be supporting Python2 starting with version 0.3.12.


  1. Method 1

    pip install nltools
  2. Method 2 (Recommended)

    pip install git+
  3. Method 3

    git clone
    python install


    pip install -e 'path_to_github_directory'


nltools requires several dependencies. All are available in pypi. Can use pip install 'package'

  • nibabel>=2.0.1
  • scikit-learn>=0.19.1
  • nilearn>=0.4
  • pandas>=0.20
  • numpy>=1.9
  • seaborn>=0.7.0
  • matplotlib>=2.1
  • scipy
  • six
  • pynv
  • joblib

Optional Dependencies

  • mne
  • requests
  • networkx
  • ipywidgets >=5.2.2


Current Documentation can be found at readthedocs.

Please see our tutorials, which provide numerous examples for how to use the toolbox.


Please see our cosanlab_preproc library for nipype pipelines to perform preprocessing on neuroimaging data.

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