from psychopy import calib import matplotlib.matlab as mat myMonitor = calib.Monitor('iiyama514') #run a calibration series lumsPRE = calib.getLumSeriesPR650(1,8) gamCalc = calib.GammaCalculator(lums=lumsPRE) print "monitor gamma=%.2f" %(gamCalc.gammaVal) myMonitor['gamma'] = gamCalc.gammaVal myMonitor.save() #set the gamma value and test again lumsPOST = calib.getLumSeriesPR650(1,8,myMonitor['gamma']) mat.plot(calib.DACrange(len(lumsPRE)),lumsPRE,'bo-') mat.plot(calib.DACrange(len(lumsPOST)),lumsPOST,'ro-') mat.ylabel('cd/m^2') mat.show()
#!/usr/bin/env python from matplotlib import matlab data = ((3,1000), (10,3), (100,30), (500, 800), (50,1)) matlab.xlabel("FOO") matlab.ylabel("FOO") matlab.title("Testing") matlab.gca().set_yscale('log') dim = len(data[0]) w = 0.75 dimw = w / dim x = matlab.arange(len(data)) for i in range(len(data[0])) : y = [d[i] for d in data] b = matlab.bar(x + i * dimw, y, dimw, bottom=0.001) matlab.gca().set_xticks(x + w / 2) matlab.gca().set_ylim( (0.001,1000)) matlab.show()
#!/usr/bin/env python from matplotlib import matlab data = ((3, 1000), (10, 3), (100, 30), (500, 800), (50, 1)) matlab.xlabel("FOO") matlab.ylabel("FOO") matlab.title("Testing") matlab.gca().set_yscale('log') dim = len(data[0]) w = 0.75 dimw = w / dim x = matlab.arange(len(data)) for i in range(len(data[0])): y = [d[i] for d in data] b = matlab.bar(x + i * dimw, y, dimw, bottom=0.001) matlab.gca().set_xticks(x + w / 2) matlab.gca().set_ylim((0.001, 1000)) matlab.show()
from psychopy import calib import matplotlib.matlab as mat myMonitor = calib.Monitor('iiyama514') #run a calibration series lumsPRE = calib.getLumSeriesPR650(1, 8) gamCalc = calib.GammaCalculator(lums=lumsPRE) print "monitor gamma=%.2f" % (gamCalc.gammaVal) myMonitor['gamma'] = gamCalc.gammaVal myMonitor.save() #set the gamma value and test again lumsPOST = calib.getLumSeriesPR650(1, 8, myMonitor['gamma']) mat.plot(calib.DACrange(len(lumsPRE)), lumsPRE, 'bo-') mat.plot(calib.DACrange(len(lumsPOST)), lumsPOST, 'ro-') mat.ylabel('cd/m^2') mat.show()