Skip to content
Snippets Groups Projects
user avatar
Sam Yates authored
New PR post master rollback; squashed and rebased, but reprises #1111.

* Add (forward) ordered forest implementation, tests.
* Add `segment` region expression; to ease implementation, `msegment` now also knows its own id.
* Add `stitch_builder` and `stitched_morphology`. A stitch corresponds to a labelled, linearly-interpolated segment which can be attached at any point along a parent stitch. A `stitched_morphology` takes a `stitch_builder` object and constructs a segment tree and morphology, and provides a dictionary of stitch labels to segment indices and region expressions.
* Add `import` method for `label_dict`, so that the label dictionary returned by `stitched_morphology` can be merged with an existing dictionary.
* Add section on stitch builder etc. to cable cell docs.
* Update cable cell docs to remove out of date info and to provide some context.
* Describe ordered forest datastructure and interface in a long comment at the beginning of the header file.
135e91ac

CI status Build Status codecov Gitpod Ready-to-Code

Arbor Library

Arbor is a library for implementing performance portable network simulations of multi-compartment neuron models.

An installation guide and library documentation are available online at Read the Docs.

Submit a ticket or start a discussion if you have any questions or want help.

Citing Arbor

The Arbor software can be cited via Zenodo: DOI.

Previous versions of Arbor can be cited specifically:

  • Version 0.2: DOI
  • Version 0.1: DOI

The following BibTeX entry can be used to cite Arbor:

@INPROCEEDINGS{
    paper:arbor2019,
    author={N. A. {Akar} and B. {Cumming} and V. {Karakasis} and A. {Küsters} and W. {Klijn} and A. {Peyser} and S. {Yates}},
    booktitle={2019 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)},
    title={{Arbor --- A Morphologically-Detailed Neural Network Simulation Library for Contemporary High-Performance Computing Architectures}},
    year={2019}, month={feb}, volume={}, number={},
    pages={274--282},
    doi={10.1109/EMPDP.2019.8671560},
    ISSN={2377-5750}}

Alternative citation formats for the paper can be downloaded here, and a preprint is available at arXiv.