MAP

% ------------------------------------------------------- psychometricFunction

function [psy, levelsBinVector, binFrequencies, nNo, nYes]=...

    psychometricFunction(levels, responses, psyBinWidth)

% computes a psychometric function from rwo vectors (levels and responses)

% responses is a binary vectory (1=yes)

% psyBinWidth is the bin width (dB) of the output psychometric function

% this function is called by both fitPsychometricFunction and subjGUI

% for this reason it should notbe bundled with fitPsychometricFunction

binFrequencies=[]; nNo=[]; nYes=[];

if min(levels)+abs(psyBinWidth) < max(levels)

    % create a set of bins for the psychometric function

    levelsBinVector= min(levels): abs(psyBinWidth): max(levels);

else

    psy=[]; levelsBinVector=[];

    return

end

idx0=find(responses==0);	% isolate 'no'

z=levels(idx0);

nNo=hist(z, levelsBinVector);

idx1=find(responses>0);	% isolate 'yes'

y=levels(idx1);

nYes=hist(y, levelsBinVector);

if sum(nNo)==0 | sum(nYes)==0

        psy=[]; levelsBinVector=[];

    return             % yesses and nos required for a function

end

binFrequencies=nNo+nYes;

warning off MATLAB:divideByZero

psy=nYes./binFrequencies;        % psy is the proportion of 'yes' responses

warning on MATLAB:divideByZero

lastwarn('');

idx=~isnan(psy);	%remove empty bins

idx=(nYes>0) |(nNo>0);	%remove empty bins

psy=psy(idx);

levelsBinVector=levelsBinVector(idx);

binFrequencies=binFrequencies(idx);

nNo=nNo(idx);

nYes=nYes(idx);

% [nNo' nYes']

% [levelsBinVector' psy']

% plot(levelsBinVector,psy,['o'])