EyeFeatures is an open-source Python package for analyzing eye movement data in any visual task. Its capabilities encompass preprocessing, visualization, statistical analysis, feature engineering and machine learning. Its unique feature is its architecture and versatility. Accepting data in .csv format containing gaze position coordinates, the package allows filtration of raw data to remove noise and detecting fixations and saccades with different algorithms. Having fixations any standard descriptive statistical eye movement features (such as totalFD, meanFD etc.) can be computed, including AOI-wise features. AOIs can be predefined or assigned automatically. More complex features, such as chaos measures, topological features, density maps, scanpath similarities for various distance metrics can be computed as well. The package allows to account for the panel structure of the data, calculating shift features relative to group averages. The visualization module allows output a variety of visualization options, including static and dynamic scanpath plots. The architecture of the package allows seamless embedding of its preprocessing and feature extraction classes in Sklearn pipelines. Moreover, it provides datasets and models for deep learning with Pytorch.
Documentation for the latest version can be found here.
Here are package tutorials devoted to different parts of the library:
| Tutorial | Notebook |
|---|---|
| Simple Features Tutorial |  |
| Complex Features Tutorial | |
| Gazes Preprocessing Tutorial | |
| AOI Definition Tutorial | |
| Visualization Tutorial | |
| Deep Learning Tutorial | |
Extensive table with references to all methods is coming soon.