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
Project details
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-1.1.2.tar.gz
(29.4 kB
view details)
Built Distribution
PyOKR-1.1.2-py3-none-any.whl
(29.2 kB
view details)
File details
Details for the file PyOKR-1.1.2.tar.gz
.
File metadata
- Download URL: PyOKR-1.1.2.tar.gz
- Upload date:
- Size: 29.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.18
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 1f418f34fa35822262ea3f037dfc8141c3a85ff591b7697cb2f36d9147082f29 |
|
MD5 | 57c426b128c1e220175070df367615d7 |
|
BLAKE2b-256 | 1198b1544218fc4ef38881771d1a0048e8c4c7516d9603f0d22a77a64c6c5f12 |
File details
Details for the file PyOKR-1.1.2-py3-none-any.whl
.
File metadata
- Download URL: PyOKR-1.1.2-py3-none-any.whl
- Upload date:
- Size: 29.2 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 | 39e4e7e06e55ad3b1313d92d47eed2c15e361b5286d235385c20d54deb44e0a5 |
|
MD5 | bbcce9b27e3cc5f3a466dc01da642c2d |
|
BLAKE2b-256 | fab351001feb279a44c8db00452cf3161b3ebc1eba49b05c62ea106cf3386530 |