PyRat - Python in Rodent Analysis and Tracking
PyRat is a user friendly library in python to analyze data from the DeepLabCut. Developed to help researchers unfamiliar with programming can perform animal behavior analysis more simpler.
Installation
The latest stable release is available on PyPi, and you can install it by saying
pip install pyratlib
Anaconda users can install using conda-forge
:
conda install -c conda-forge pyratlib
To build PyRat from source, say python setup.py build
.
Then, to install PyRat, say python setup.py install
.
If all went well, you should be able to execute the demo scripts under examples/
(OS X users should follow the installation guide given below).
Alternatively, you can download or clone the repository and use pip
to handle dependencies:
unzip pyratlib.zip
pip install -e pyratlib
or
git clone https://github.com/pyratlib/pyrat.git
pip install -e pyratlib
By calling pip list
you should see pyrat
now as an installed package:
pyrat (0.x.x, /path/to/pyratlib)
Data
The data is available on Zenodo
Examples
- Basic Usage
- Behavior Classification
- Behavior Classification of multiple videos
- Metrics in mice
- Neural Data example
References:
If you use our code we kindly as that you please cite De Almeida et al, 2022 and, if you use the dataset please also cite De Almeida et al, 2021.
Please check out the following references for more details:
@article{deAlmeida2022,
title = {PyRAT: An open source-python library for fast and robust animal behavior analysis and neural data synchronization},
author = {De Almeida, Tulio Fernandes and
Spinelli, Bruno Guedes and
Hypolito Lima, Ram{\'o}n and
Gonzalez, Maria Carolina and
Rodrigues, Abner Cardoso},
journal = {Frontiers in Neuroscience},
pages = {505},
publisher = {Frontiers}
}
@dataset{deAlmeida2021,
title = {PyRAT-data-example},
author = {Almeida, Túlio and
Spinelli, Bruno and
Gonzalez, Maria Carolina and
Lima, Ramón and
Rodrigues, Abner},
month = sep,
year = 2021,
publisher = {Zenodo},
version = {1.0.0},
doi = {10.5281/zenodo.5883277},
url = {https://doi.org/10.5281/zenodo.5883277}
}
Development Team: