.. image:: https://github.com/SlugocM/bayesfit/blob/master/logos/logo.png :alt: BayesFit Logo :scale: 50 %
|pypi| |coverage|
:Authors: Michael Slugocki
Special Note from Author:
[ updated on: 2024/02/17 ]
BayesFit now has a brand new website (http://www.bayesfit.org).
Some outstanding issues have been addressed, and a new PYPI version of BayesFit (version 2.4) has been released. Please update to the latest version to get all the benefits.
Kind Regards,
š³ M š³
Citation:
Slugocki, M., Sekuler, A.B. and Bennett, P., 2019. BayesFit: A tool for modeling psychophysical data using Bayesian inference. Journal of Open Research Software, 7(1), p.2. DOI: http://doi.org/10.5334/jors.202
API documentation: http://www.bayesfit.org
Issues? Submit a question here: https://github.com/SlugocM/bayesfit/issues
Release 2.4:
BayesFit provides a simple and easy to use interface to fit and plot psychometric functions using Bayesian inference via numerical integration.
Packages required (versions specified in requirements.txt):
Numpy <http://www.numpy.org/>
Matplotlib <https://matplotlib.org/>
Scipy <https://docs.scipy.org/doc/>
_
To install required packages if the versions are out of date, or not installed in your working environment, first download the requirements.txt file in this repository. Then navigate to the directory that contains the downloaded text file using the command-prompt. Then type:
::
pip install -r requirements.txt
RECOMMENDED: BayesFit and required packages may be installed from the Python Package Index <https://pypi.python.org/pypi>
_ using pip
.
::
pip install bayesfit
Alternatively, if required packages are already installed on your system, BayesFit can be installed via:
::
git clone --recursive https://github.com/slugocm/bayesfit.git cd bayesfit python setup.py install
Simply type:
::
pip install bayesfit -U
.. |pypi| image:: https://badge.fury.io/py/bayesfit.png :target: https://badge.fury.io/py/bayesfit :alt: pypi version
.. |coverage| image:: https://coveralls.io/repos/github/SlugocM/bayesfit/badge.svg?branch=master :target: https://coveralls.io/github/SlugocM/bayesfit?branch=master