Ocupy - Oculography Analysis Tools
----------------------------------
Ocupy provides functionality for analysis of blocked data:
* DataMat objects for reading of and filtering by block meta-data and data
* Corresponding objects for stimulus data, aligned to DataMat objects
* Measures for prediction quality for eye-tracking data: AUC, NSS, KL, EMD.
* Lower and upper bound calculation for prediction quality of attention models.
* RPC Client/Server for parallel task execution on a grid
* Evaluation (with cross-validation) of attention models
Install
-------
To install ocupy into your Python environment, type:
python setup.py build
python setup.py test
python setup.py install
The core requirements for ocupy, numpy and scipy, are automatically
installed if not found on your Python path.
If you want to use the parallel module you'll need to install Twisted manually.
Documentation
-------------
The documentation is generated by sphinx (http://sphinx.pocoo.org):
cd doc
make html
This will create a set of html files in doc/_build/html. You have to
have sphinx and matplotlib installed. Also, ocupy has to be on your
path, if you didn't install it add this directory to the python path:
export PYTHONPATH=$PYTHONPATH:`pwd`
Copyright & License
-------------------
Copyright (C) 2010, 2011 WhiteMatter Labs GmbH -- http://whitematter.de
Licensed under GPLv2 or later, see file LICENSE in this source tree
Ocupy was developed jointly by WhiteMatter Labs GmbH and the Neurobiopsychology
Group at the Unversity of Osnabrueck's Institute of Cognitive Science.
Project Lead: Niklas Wilming <nwilming@uos.de>
Contributors: Robert Muil, Torsten Betz, Hannah Knepper, Johannes Steger, Kilian Klimek