A module for fitting 2AFC psychometric data.
The psychofit module contains tools to fit two-alternative psychometric data. The fitting is done using maximal likelihood estimation: one assumes that the responses of the subject are given by a binomial distribution whose mean is given by the psychometric function.
The data can be expressed in fraction correct (from 50 to 100%) or in fraction of one specific choice (from 0 to 100%). To fit them you can use these functions:
weibull50- Weibull function from 0.5 to 1, with lapse rate.weibull- Weibull function from 0 to 1, with lapse rate.erf_psycho- erf function from 0 to 1, with lapse rate.erf_psycho_2gammas- erf function from 0 to 1, with two lapse rates.
Functions in the toolbox are:
mle_fit_psycho- Maximumum likelihood fit of psychometric function.neg_likelihood- Negative likelihood of a psychometric function.
For more info, see:
Examples.ipynb- Examples of use of psychofit toolbox.
Matteo Carandini (2000-2017) initial Matlab code
Miles Wells (2017-2018) ported to Python