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()
