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Python toolbox for analyzing imaging data
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README.md

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NLTools

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.

Installation

  1. Method 1

    pip install nltools
    
  2. Method 2 (Recommended)

    pip install git+https://github.com/ljchang/neurolearn
    
  3. Method 3

    git clone https://github.com/ljchang/neurolearn
    python setup.py install
    

    or

    pip install -e 'path_to_github_directory'
    

Dependencies

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

Documentation

Current Documentation can be found at readthedocs.

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

Preprocessing

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

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