SimBA (Simple Behavioral Analysis)
SimBA (Simple Behavioral Analysis) is a platform for analyzing behaviors of experimental animals within video recordings.
More Information
See below for raison d'être, detailed API, tutorials, data, documentation, support, and walkthroughs:
- GitHub: https://github.com/sgoldenlab/simba
- Documentation readthedocs: https://simba-uw-tf-dev.readthedocs.io/en/latest/
- API: https://simba-uw-tf-dev.readthedocs.io/en/latest/api.html
- Gitter chat support: https://app.gitter.im/#/room/#SimBA-Resource_community:gitter.im
- bioRxiv preprint: https://www.biorxiv.org/content/10.1101/2020.04.19.049452v2
- Nature Neuroscience paper: https://www.nature.com/articles/s41593-024-01649-9
- Open Science Framework (OSF) data buckets: https://osf.io/tmu6y/
- Video examples: http://youtube.com/playlist?list=PLi5Vwf0hhy1R6NDQJ3U28MOUJPfl2YWYl
- Slide examples: https://simba-uw-tf-dev.readthedocs.io/en/latest/docs/workflow.html
Installation
To install SimBA, use the following command:
pip install simba-uw-tf-dev
Citation
If you use the code, please cite:
@article{Nilsson2020.04.19.049452,
author = {Nilsson, Simon RO and Goodwin, Nastacia L. and Choong, Jia Jie and Hwang, Sophia and Wright, Hayden R and Norville, Zane C and Tong, Xiaoyu and Lin, Dayu and Bentzley, Brandon S. and Eshel, Neir and McLaughlin, Ryan J and Golden, Sam A.},
title = {Simple Behavioral Analysis (SimBA) – an open source toolkit for computer classification of complex social behaviors in experimental animals},
elocation-id = {2020.04.19.049452},
year = {2020},
doi = {10.1101/2020.04.19.049452},
publisher = {Cold Spring Harbor Laboratory},
URL = {https://www.biorxiv.org/content/early/2020/04/21/2020.04.19.049452},
eprint = {https://www.biorxiv.org/content/early/2020/04/21/2020.04.19.049452.full.pdf},
journal = {bioRxiv}
}
Licence
SimBA is licensed under a modified BSD 3-Clause License, permitting use for academic and research purposes only. For commercial licensing inquiries, contact sronilsson@gmail.com.
Contributors
Contributers on Github https://github.com/sgoldenlab/simba#contributors
Contact
1 maintainer
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
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file simba_uw_tf_dev-5.4.7.tar.gz.
File metadata
- Download URL: simba_uw_tf_dev-5.4.7.tar.gz
- Upload date:
- Size: 9.9 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/3.8.0 pkginfo/1.10.0 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/1.0.0 urllib3/1.26.20 tqdm/4.30.0 importlib-metadata/4.8.3 keyring/23.4.1 rfc3986/1.5.0 colorama/0.4.4 CPython/3.6.13
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
81667411c8eeaed974c8ad518e2053571b03b29a2882c34f8d698a63008f8ac1
|
|
| MD5 |
850748501172d935a5d6ce2041f3b4f1
|
|
| BLAKE2b-256 |
4c61b0a8db2bdadff45cc90f99eb576b2ca9040435fdf34d8f233f3b730f9127
|
File details
Details for the file simba_uw_tf_dev-5.4.7-py3-none-any.whl.
File metadata
- Download URL: simba_uw_tf_dev-5.4.7-py3-none-any.whl
- Upload date:
- Size: 12.0 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/3.8.0 pkginfo/1.10.0 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/1.0.0 urllib3/1.26.20 tqdm/4.30.0 importlib-metadata/4.8.3 keyring/23.4.1 rfc3986/1.5.0 colorama/0.4.4 CPython/3.6.13
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
659746921d77a191a4647558b524d5b42c3115df0aff7a943ef69f1ad94dd2a3
|
|
| MD5 |
229733e5b985ddf6612a276896ddbda4
|
|
| BLAKE2b-256 |
b4101f0aae310d96e67dbf7c2c327253a02bb84c8f4e4f3ec18417acc28669ad
|
