Connectome File Format Library for Multi-Modal Neuroimaging Data and Metadata
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Connectome File Format Library

The Connectome File Format Library (cfflib) is a pure Python library for multi-modal connectome data and metadata management and integration,
based on the specification of the Connectome File Format (CFF). The cfflib provides a high-level interface to many common data formats
by using `Nibabel <>`_ for basic neuroimaging data format IO, and NumPy and the Python standard-library for other formats. The Connectome
File Format provides means to store arbitrary metadata as tags and in structured form for any so-called connectome object. Connectome objects
encapsulate the various data types as they occur in connectome research.

* CMetadata: Connectome Markup Language (XML)
* CNetwork: Networks, Connectomes (GraphML, GEXF, NXGPickle)
* CSurface: Surface data (Gifti)
* CVolume: Volumetric data (Nifti1)
* CTrack: Fiber track data (TrackVis)
* CTimeserie: Timeseries data (HDF5, NumPy)
* CData: Other data, like tables (HDF5, NumPy, XML, JSON, CSV, Pickle)
* CScript: Processing and analysis scripts (ASCII, UTF-8, UTF-16)
* CImagestack: Imagestacks (PNG, JPG, TIFF, SVG)

The Connectome File Format Library is part of the Connectome Mapping Toolkit.

Copyright (C) 2009-2011, Ecole Polytechnique Fédérale de Lausanne (EPFL) and
Hospital Center and University of Lausanne (UNIL-CHUV), Switzerland

Main Author: Stephan Gerhard

See THANKS for contributions