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.
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)
The data is available on Zenodo
- Basic Usage
- Behavior Classification
- Metrics in mice
- Neural Data example
- Tulio Almeida - GitHub - Google Scholar
- Bruno Spinelli - GitHub - Google Scholar
- Ramon Hypolito - GitHub - Google Scholar
- Maria Carolina Gonzalez - GitHub - Google Scholar
- Abner Rodrigues - GitHub - Google Scholar