treem 1.0.2

Tree-like morphology data processing

treem - neuron morphology processing tool

Module provides data structure and command-line tools for accessing and manipulating the digital reconstructions of the neuron morphology in Stockley-Wheal-Cannon format (SWC).

Main classes

Access to morphological data from the source code is supported by the classes Tree, Node, Morph and SWC.

• Tree - Recursive tree data structure
• Node - Morphology data storage
• Morph - Neuron morphology representation
• SWC - Definitions of the data format

Commands

Common operations with SWC files are possible via the swc command-line tool:

swc <command> [options] file

List of swc commands:

• check - Test morphology reconstruction for structural consistency
• convert - Convert morphology to compliant SWC format
• find - Locate single nodes in the reconstruction
• measure - Calculate morphometric features
• modify - Manipulate morphology reconstruction
• render - Display 3D model of the reconstruction
• repair - Correct reconstruction errors
• view - Show morphology structure

Installation

Install the latest stable release:

pip3 install treem

Install a development version:

pip3 install git+git://github.com/a1eko/treem

See also pip3 documentation for installation alternatives.

Dependencies

Module treem has minimal runtime dependencies:

• python >= 3.7
• matplotlib
• numpy
• PyOpenGL (optional) enables swc render command

For testing and documentation, treem needs development packages with third-party extensions:

• sphinx with napoleon and programoutput
• pytest with pytest-cov
• coverage

Documentation

Documentation is available online at Read the Docs.

Funding

Horizon 2020 Framework Programme (785907, HBP SGA2); Horizon 2020 Framework Programme (945539, HBP SGA3); Vetenskapsrådet (VR-M-2017-02806, VR-M-2020-01652); Swedish e-science Research Center (SeRC); KTH Digital Futures.