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#This analysis script takes one or more staircase datafiles as input
#from a GUI. It then plots the staircases on top of each other on
#the left and a combined psychometric function from the same data
#on the right
from psychopy import data, gui, misc, core
import pylab
#Open a dialog box to select files from
files = gui.fileOpenDlg('.')
if not files:
core.quit()
#get the data from all the files
allIntensities, allResponses = [],[]
for thisFileName in files:
thisDat = misc.fromFile(thisFileName)
allIntensities.append( thisDat.intensities )
allResponses.append( thisDat.data )
#plot each staircase
pylab.subplot(121)
colors = 'brgkcmbrgkcm'
lines, names = [],[]
for fileN, thisStair in enumerate(allIntensities):
#lines.extend(pylab.plot(thisStair))
#names = files[fileN]
pylab.plot(thisStair, label=files[fileN])
#pylab.legend()
#get combined data
combinedInten, combinedResp, combinedN = \
data.functionFromStaircase(allIntensities, allResponses, 5)
#fit curve - in this case using a Weibull function
fit = data.FitFunction('weibullTAFC',combinedInten, combinedResp, \
guess=[0.2, 0.5])
smoothInt = pylab.arange(min(combinedInten), max(combinedInten), 0.001)
smoothResp = fit.eval(smoothInt)
thresh = fit.inverse(0.8)
print thresh
#plot curve
pylab.subplot(122)
pylab.plot(smoothInt, smoothResp, '-')
pylab.plot([thresh, thresh],[0,0.8],'--'); pylab.plot([0, thresh],\
[0.8,0.8],'--')
pylab.title('threshold = %0.3f' %(thresh))
#plot points
pylab.plot(combinedInten, combinedResp, 'o')
pylab.ylim([0,1])
pylab.show()
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