gazekit 0.0.3

This is a Python library designed for processing eye-tracking data.

GazeKit (Under Development) 🚧👁️

GazeKit is a Python library currently under development for processing and analyzing eye-tracking data. It aims to provide a comprehensive set of functions for noise reduction, area of interest (AOI) localization, data analysis, and plotting. This library is being developed to simplify the preprocessing and analysis of eye-tracking data, enabling researchers in psychology, neuroscience, and human-computer interaction to gain valuable insights into human visual cognitive processes.

Features

• Noise Reduction: GazeKit offers advanced techniques for reducing noise in eye-tracking data, allowing for more accurate and reliable analysis.
• AOI Localization: Easily define and locate areas of interest (AOIs) within eye-tracking data, facilitating the analysis of gaze patterns and attentional focus.
• Data Analysis: GazeKit provides a range of analysis tools, including fixation duration, saccade detection, heatmaps, and scanpath visualization, empowering researchers to extract meaningful information from eye-tracking data.
• Plotting: Visualize eye-tracking data with customizable plots and graphs, enabling researchers to effectively communicate their findings.

Installation

Once GazeKit is released, you will be able to install it using pip:

pip install gazekit

Usage

Once installed, you can use GazeKit in your Python code. Here's a sneak peek at how GazeKit might be used for preprocessing and analyzing eye-tracking data:

import numpy as np
from gazekit.aoi import read_aoi_ini_file
from gazekit.sequence import Sequence

# Load eye-tracking data
data = np.genfromtxt('../tests/data.csv', delimiter=',', dtype=None, encoding=None)

# Load AOIs
aois = read_aoi_ini_file('../tests/aoi.ini', (2560, 1600))

# Load data into GazeKit Sequence class
seq = Sequence(*data.T)

# Apply noise reduction techniques (under development)
seq = seq.denoise(myfunc)

# Detect fixations (under development)
seq = seq.detect_fixations()

# Locate AOIs within the data
seq = seq.loc_aoi(aois)

# Generate a plot (under development)
heatmap = seq.plot(myfunc)

# ... Perform further analysis and visualization

For more detailed instructions and examples, please refer to the documentation (coming soon).

Contributing

Contributions to GazeKit are welcome! Since this project is currently under development, we are not accepting contributions at this stage. However, once the project reaches a more stable state, we would love to collaborate with the open-source community. Stay tuned for updates!

License

This project is licensed under the MIT License.

Acknowledgements

We would like to express our gratitude to the open-source community for their valuable contributions and support in developing GazeKit. 🎉😊