NeuroM: a light-weight neuron morphology analysis package
Project description
NeuroM
NeuroM is a Python toolkit for the analysis and processing of neuron morphologies.
Documentation
NeuroM documentation is built and hosted on readthedocs.
Migration to v2 or v3 versions
Refer to the doc page on this topic.
Reporting issues
Issues should be reported to the NeuroM github repository issue tracker. The ability and speed with which issues can be resolved depends on how complete and succinct the report is. For this reason, it is recommended that reports be accompanied with
- A minimal but self-contained code sample that reproduces the issue. Minimal means no code that is irrelevant to the issue should be included. Self-contained means it should be possible to run the code without modifications and reproduce the problem.
- The observed and expected output and/or behaviour. If the issue is an error, the python error stack trace is extremely useful.
- The commit ID of the version used. This is particularly important if reporting an error from an older version of NeuroM.
- If reporting a regression, the commit ID of the change that introduced the problem
- If the issue depends on data, a data sample which reproduces the problem should be
up-loaded. But check first whether the error can be reproduced with any of the data
samples available in the
tests/datadirectory.
Citation
When you use the NeuroM software, we ask you to cite the following (this includes poster presentations):
Funding & Acknowledgements
This work has been partially funded by the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 720270, 785907 (Human Brain Project SGA1/SGA2) and by the EBRAINS research infrastructure, funded from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 945539 (Human Brain Project SGA3).
The development of this software was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology.
For license and authors, see LICENSE.txt and AUTHORS.md respectively.
Copyright (c) 2015-2022 Blue Brain Project/EPFL
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file neurom-3.2.11.tar.gz.
File metadata
- Download URL: neurom-3.2.11.tar.gz
- Upload date:
- Size: 490.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 8beaafd5dbfcd363da0cb33f867426591cbde48d2bb44397f91cb36db2f2ce3e |
|
| MD5 | f98016367cd92ea7602a815ecbe77c76 |
|
| BLAKE2b-256 | b7c858e354bad207081b0266bb36e0f08c823852dbbbcd1d18a2463caaf5be4c |
File details
Details for the file neurom-3.2.11-py3-none-any.whl.
File metadata
- Download URL: neurom-3.2.11-py3-none-any.whl
- Upload date:
- Size: 109.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 3ea7d1a125ec616853d64a8be979451ebecfbe493c1d5a5e1edc07488edb471e |
|
| MD5 | 6360f218f448135cfd0ac4f31f716283 |
|
| BLAKE2b-256 | ef8b35e955caaafea563cdf6bbd0439ceebb70dee845b7b479ff724a80cb33f1 |
