Metadata-Version: 2.4
Name: PyOKR
Version: 1.1.3
Summary: A semi-automated method to analyze optokinetic reflex responses
Author-email: James Kiraly <james@kiraly.com>
Project-URL: Homepage, https://github.com/KolodkinLab/PyOKR
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: matplotlib~=3.6.3
Requires-Dist: keyboard~=0.13.5
Requires-Dist: numpy~=1.24.4
Requires-Dist: pandas~=2.0.3
Requires-Dist: PyQt5~=5.14.0
Requires-Dist: scikit-learn~=1.3.2
Requires-Dist: scipy~=1.10.1
Requires-Dist: pandasgui~=0.2.14
Requires-Dist: sympy~=1.12
Dynamic: license-file

# PyOKR
A Python-based optokinetic reflex analysis tool to measure and quantify eye tracking motion in three dimensions. Video-oculography data can be modeled computationally to quantify specific tracking speeds and ability in horizontal and vertical space. 

**Requirements**: 

- Python >= 3.8

- Spyder IDE via Anaconda (suggested for interactive graphs)

**Imports**:

- PyQT5

- Pandas

- Matplotlib

- Numpy

- Sklearn.neighbors (from scikit)

- Scipy

- SymPy

- Pandasgui

