Python toolbox for analyzing neuroimaging data. Compatible with both Python 2.7 and Python 3.6. 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

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'
   

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

• 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.