A python package for processing eye movement data
Project description
pymovements is an open-source python package for processing eye movement data. It provides a simple interface to download publicly available datasets, preprocess gaze data, detect oculomotoric events and render plots to visually analyze your results.
- Website: https://github.com/aeye-lab/pymovements
- Documentation: https://pymovements.readthedocs.io
- Source code: https://github.com/aeye-lab/pymovements
- Mailing list: pymovements-list@uni-potsdam.de
- Contributing: https://github.com/aeye-lab/pymovements/blob/main/CONTRIBUTING.md
- Bug reports: https://github.com/aeye-lab/pymovements/issues
- PyPI package: https://pypi.org/project/pymovements
- Conda package: https://anaconda.org/conda-forge/pymovements
Getting Started
With pymovements loading your eye movement datasets is just a few lines of code away
import pymovements as pm
dataset = pm.Dataset(
'JuDo1000', # choose a public dataset from our dataset library
path='data/judo100', # setup your local dataset path
)
dataset.download() # download a public dataset from our dataset library
dataset.load() # download the dataset
calculate velocities on the fly
dataset.pix2deg() # transform pixel coordinates to degrees of visual angle
dataset.pos2vel() # transform positional data to velocity data
and extract events with different eye movements event extraction algorithms
dataset.detect('ivt') # detect fixation using the I-VT algorithm
dataset.detect('microsaccades') # detect saccades using the microsaccades algorithm
Check out our guide on how to install pymovements and get started here: Installation
We provide a range of tutorial aimed at beginners: Tutorials
The complete reference of the package can be found here: API Reference
Contributing
We welcome any sort of contribution to pymovements!
For a detailed guide, please refer to our CONTRIBUTING.md first.
If you have any questions, please open an issue or write us at pymovements-list@uni-potsdam.de
Citing
If you are using pymovements in your research, we would be happy if you cite our work by using the following BibTex entry:
@inproceedings{pymovements,
author = {Krakowczyk, Daniel G. and Reich, David R. and Chwastek, Jakob and Jakobi, Deborah N.
and Prasse, Paul and Süss, Assunta and Turuta, Oleksii and Kasprowski, Paweł
and Jäger, Lena A.},
title = {pymovements: A Python Package for Processing Eye Movement Data},
year = {2023},
isbn = {979-8-4007-0150-4/23/05},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3588015.3590134},
doi = {10.1145/3588015.3590134},
booktitle = {2023 Symposium on Eye Tracking Research and Applications},
location = {Tubingen, Germany},
series = {ETRA '23},
}
There is also a preprint available on arxiv.
Project details
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
Hashes for pymovements-0.18.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | db97134a6b83122824b9e16bb501ab1879298eab52bf43c4d3650f6d33e3cafc |
|
MD5 | 3c46c231e94153efbbb673795d3b16e4 |
|
BLAKE2b-256 | ee96315012e305173c35803213338fa18df4a71b1a8bdf784a9534ddc7414908 |