class TestTrialResponse(unittest.TestCase):
@data(('0.pkl',
[50,11,3.3,1.83,0.92,0.31],
12,
36,
4.0,
0.0,
0.7,
0.0,
8,
Visualization.Visualize(circleSize=10, screenColor=[255,255,255], screen = pg.display.set_mode([800,800]),
saveImage=False, saveImageFile='image'),
0.95,
{50:5,11:30,3.3:60,1.83:90,0.92:120,0.31:150}))
@unpack
def testResponseForSimpleChasing(self,filename,subtletyHypothesis,updateFrequency,attentionSwitchFrequency,precisionPerSlot,precisionForUntracked,memoryratePerSlot,memoryrateForUntracked,attentionLimitation,visualize,responseRule,precisionToSubtletyDict):
loadTrajectory=LoadTrajectory.loadTrajectory
initialPrior=targetCode.initialPrior(attentionLimitation)
computePosterior=calPosterior.calPosteriorLog
attention=Attention.AttentionToPrecisionAndDecay(precisionPerSlot, precisionForUntracked, memoryratePerSlot, memoryrateForUntracked)
attentionSwitch=Attention.AttentionSwitch(attentionLimitation)
perception=Perception.Perception(attention, computePosterior, attentionSwitch, attentionSwitchFrequency)
response=Response.RuleBasedResponse(responseRule, precisionToSubtletyDict)
trial=targetCode.Trial(subtletyHypothesis, updateFrequency, loadTrajectory, visualize, initialPrior, response, perception)
trialResponse=trial(filename)
# self.assertTrue(trialResponse['action'])
self.assertLessEqual(trialResponse['RT'],8000)
self.assertEqual(trialResponse['wolfIdentity'],0)
self.assertEqual(trialResponse['sheepIdentity'],1)
screenHeight=800
filename='0.pkl'
subtletyHypothesis=[50,11,3.3,1.83,0.92,0.31]
precisionToSubtletyDict={50:5,11:30,3.3:60,1.83:90,0.92:120,0.31:150}
updateFrequency=12
attentionSwitchFrequency = 24
responseRule=1.01
precisionPerSlot=8.0
precisionForUntracked=2.5
memoryratePerSlot=0.7
memoryrateForUntracked=0.45
attentionLimitation=2
outputpath=os.path.abspath(os.path.join(os.getcwd(), os.pardir))+'/data/'
saveImage=False
saveImageFile='image'
initialPrior=initialPrior(attentionLimitation)
screen = pg.display.set_mode([screenWide,screenHeight])
loadTrajectory=LoadTrajectory.loadTrajectory
visualize=Visualization.Visualize(circleSize, screenColor, screen, saveImage, outputpath+saveImageFile)
computePosterior=calPosterior.calPosteriorLog
attentionSwitch=Attention.AttentionSwitch(attentionLimitation)
attention = Attention.AttentionToPrecisionAndDecay(precisionPerSlot, precisionForUntracked, memoryratePerSlot, memoryrateForUntracked)
perception=Perception.Perception(attention, computePosterior, attentionSwitch, attentionSwitchFrequency)
response=Response.RuleBasedResponse(responseRule, precisionToSubtletyDict)
runOneTrial=Trial(subtletyHypothesis, updateFrequency, loadTrajectory, visualize, initialPrior, response, perception)
response=runOneTrial(filename)
pg.quit()
print(response)
updateFrequency=12
attentionSwitchFrequency = 24
responseRule=1
precisionPerSlot=8.0
precisionForUntracked=2.5
memoryratePerSlot=0.7
memoryrateForUntracked=0.45
attentionLimitation=2
outputpath=os.path.abspath(os.path.join(os.getcwd(), os.pardir))+'/data/'
saveImage=True
saveImageFile='image'
saveResultFile='Hybird.csv'
screen = pg.display.set_mode([screenWide,screenHeight])
loadTrajectory = LoadTrajectory.loadTrajectory
initialPrior=Trial.initialPrior(attentionLimitation)
response=Response.RuleBasedResponse(responseRule, precisionToSubtletyDict)
# response=Response.Response(precisionToSubtletyDict)
writer=Writer.writeToCSV(outputpath+'results/'+saveResultFile)
plotResult=ResultPlot.plotResult
computePosterior = calPosterior.calPosteriorLog
attentionSwitch=Attention.AttentionSwitch(attentionLimitation)
attention = Attention.AttentionToPrecisionAndDecay(precisionPerSlot, precisionForUntracked, memoryratePerSlot, memoryrateForUntracked)
perception=Perception.Perception(attention,computePosterior,attentionSwitch,attentionSwitchFrequency)
visualize = Visualization.Visualize(baseLineWidth, circleSize, screenColor, screen, saveImage, saveImageFile)
Trial=Trial.Trial(subtletyHypothesis, updateFrequency, loadTrajectory, visualize, initialPrior, response, perception)
runExperiment = Experiment(trialListFilename, Trial, writer)
runExperiment()
plotResult(saveResultFile)
