Pymovements

<p style="text-align:center;"> <img width="110%" height="110%" alt="pymovements" src="https://raw.githubusercontent.com/pymovements/pymovements/main/docs/source/_static/logo.svg" onerror="this.onerror=null;this.src='./docs/source/_static/logo.svg';"/> </p>

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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/pymovements/pymovements
• Documentation: https://pymovements.readthedocs.io
• Source code: https://github.com/pymovements/pymovements
• PyPI package: https://pypi.org/project/pymovements
• Conda package: https://anaconda.org/conda-forge/pymovements
• Bug reports: https://github.com/pymovements/pymovements/issues
• Contributing: https://github.com/pymovements/pymovements/blob/main/CONTRIBUTING.md
• Mailing list: pymovements@python.org (subscribe)
• Discord: https://discord.gg/K2uS2R6PNj

Getting Started

If you are new to pymovements or to eye-tracking data analysis, we recommend starting with the User Guide, which introduces the concepts, data structures, and workflows used throughout the library: 👉 :doc:user-guide/index

Quick example

For a minimal example of loading and processing eye-tracking data with pymovements:

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()  # load the dataset

Transform coordinates and calculate velocities:

dataset.pix2deg()  # transform pixel coordinates to degrees of visual angle
dataset.pos2vel()  # transform positional data to velocity data

Detect oculomotoric events:

dataset.detect('ivt')  # detect fixation using the I-VT algorithm
dataset.detect('microsaccades')  # detect saccades using the microsaccades algorithm

<!-- With pymovements loading your eye movement [datasets](https://pymovements.readthedocs.io/en/stable/datasets/index.html) is just a few lines of code away -->

Quick Links

• :doc:Installation Options <user-guide/getting-started/installation>
• Tutorials
• 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 to us at pymovements@python.org

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.