Tree-like morphology data processing
Project description
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 structureNode
- Morphology data storageMorph
- Neuron morphology representationSWC
- 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 consistencyconvert
- Convert morphology to compliant SWC formatfind
- Locate single nodes in the reconstructionmeasure
- Calculate morphometric featuresmodify
- Manipulate morphology reconstructionrender
- Display 3D model of the reconstructionrepair
- Correct reconstruction errorsview
- 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
>= 3.7matplotlib
numpy
PyOpenGL
(optional) enablesswc render
command
For testing and documentation, treem
needs development packages with
third-party extensions:
sphinx
withnapoleon
andprogramoutput
pytest
withpytest-cov
coverage
Documentation
Documentation is available online at Read the Docs.
Project details
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