Metadata-Version: 2.1
Name: psytrack
Version: 2.0.0
Summary: Tool for tracking dynamic psychometric curves
Home-page: http://github.com/nicholas-roy/psytrack
Author: Nicholas A. Roy, Ji Hyun Bak, and Jonathan W. Pillow
Author-email: nicholas.roy.42@gmail.com
License: MIT
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Description-Content-Type: text/markdown
Requires-Dist: matplotlib
Requires-Dist: markdown
Requires-Dist: numpy
Requires-Dist: scipy

# PsyTrack

PsyTrack is a package for fitting a dynamic psychophysical model to behavioral data as proposed in our 2018 NeurIPS paper, '[Efficient inference for time-varying behavior during learning](http://pillowlab.princeton.edu/pubs/Roy18_NeurIPS_dynamicPsychophys.pdf).'

<img src='./psytrack/examples/weights.png' alt='Figure 1b from paper' height='300'/>

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## Documentation

Documentation and examples can be found in [`ExampleNotebook.ipynb`](./psytrack/examples/ExampleNotebook.ipynb)

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## How to install

Just run `pip install psytrack`


## Authors

Nick Roy, [Ji Hyun Bak](http://newton.kias.re.kr/~jhbak/), and [Jonathan Pillow](http://pillowlab.princeton.edu/)


Please cite as:

Roy NA, Bak JH, Akrami A, Brody CD, & Pillow JW (2018). [Efficient inference for time-varying behavior during learning.](http://pillowlab.princeton.edu/pubs/abs_Roy_NeurIPS18.html) _Advances in Neural Information Processing Systems_ 31, 5696-5706.  (2018).


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