comparison Copy_of_multithreshold 1.46/psychometricFunction.m @ 28:02aa9826efe0

mainly multiThreshold

+% ------------------------------------------------------- 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'])