A semi-automated method to analyze optokinetic reflex responses
Project description
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
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
PyOKR-1.0.7.tar.gz
(16.6 kB
view details)
Built Distribution
PyOKR-1.0.7-py3-none-any.whl
(15.9 kB
view details)
File details
Details for the file PyOKR-1.0.7.tar.gz.
File metadata
- Download URL: PyOKR-1.0.7.tar.gz
- Upload date:
- Size: 16.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.18
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | b1277a00170754085514b56a2ec304bea70e449440239f49e57735efdf4a3a16 |
|
| MD5 | 3771cf6552a9045aa9bea16863368c6e |
|
| BLAKE2b-256 | 47cf7ee2b5b043a2201be5eb7ba6295bd77f415e290304361191efd4efa4f50b |
File details
Details for the file PyOKR-1.0.7-py3-none-any.whl.
File metadata
- Download URL: PyOKR-1.0.7-py3-none-any.whl
- Upload date:
- Size: 15.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.18
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | b65058ee8aad6b69f2d14da42ef546f37e5e5134d86b4b168cb0e5bac714ec5b |
|
| MD5 | 789f2a02df3ba77f8e906775121c6c7b |
|
| BLAKE2b-256 | c79ab4a7048cc22cf1896ce80e425095a64ba951ec694cc50d06df1b1c3dbce6 |
