Welcome to NIPY. We are a community of practice devoted to the use of the Python programming language in the analysis of neuroimaging data. You can find us on github, as well as social media [blog] [twitter]. We welcome contributions and ask that you read about our standards of conduct. You are also invited to ask for help.

Our community includes the following projects:

  • nipype - Provides a uniform interface to existing neuroimaging software.
  • dipy - Focuses on diffusion magnetic resonance imaging (dMRI) analysis.
  • mindboggle - Improves the accuracy, precision, and consistency of labeling & morphometry of brain imaging data.
  • nibabel - Read / write common neuroimaging file formats.
  • Scitran SDM - Delivers efficient and robust archiving, organization, and sharing of scientific data.
  • Nipy - Analysis of structural and functional neuroimaging data.
  • Nitime - Time-series analysis of neuroscience data.
  • popeye - Population receptive field estimation
  • Nilearn - Fast and easy statistical learning on neuroimaging data.
  • PyMVPA - Eases statistical learning analyses of large neuroimaging datasets.
  • MNE - Processes magnetoencephalography (MEG) and electroencephalography (EEG) data.
  • napari-nibabel - A plugin for the napari image viewer to view and annotate neuroimaging data
  • niwidgets - Provides interactive plots for volumetric images.