def InstructionPlay(Df, win, params):
Dict = {
"ExperimentName":
params['expName'],
"Subject":
params['subjectID'],
"Session":
params["Session"],
"Version":
params["Version"],
"Section":
"Instructions",
"SessionStartDateTime":
datetime.datetime.now().strftime("%m/%d/%y %H:%M:%S"),
}
width = params["screenSize"][1] * 1.294
height = params["screenSize"][1]
# Display Instruction
message = visual.TextStim(
win,
text="Do you want to see the instruction?\n\n(y: Yes, n: No)",
units='norm',
wrapWidth=3)
message.draw()
win.flip()
c = ['']
# Wait for user types "y" or "n".
while (c[0].upper() != "Y" and c[0].upper() != "N"):
core.wait(1 / 120)
c = event.waitKeys() # read a character
get_keypress(Df, params)
# If user types "y", run instruction.
if c[0].upper() == "Y":
c = ['R']
while (c[0].upper() == "R"):
# core.wait(1 / 120)
for i in range(1, 17):
imgFile = "./instruction/Slide" + str(i) + ".JPG"
img1 = visual.ImageStim(win=win,
image=imgFile,
units="pix",
opacity=1,
size=(width, height))
img1.draw()
win.flip()
if i == 16:
c = event.waitKeys()
else:
waitUserSpace(Df, params)
# Log the dict result on pandas dataFrame.
tableWrite(Df, params, Dict)
def VASplay(Df, win, params, SectionName):
# VAS Initialization.
Dict = {
'ExperimentName':
params['expName'],
"Subject":
params['subjectID'],
"Session":
params['Session'],
"Version":
params['Version'],
"Section":
SectionName,
"VAS_type":
"Anxiety",
"SessionStartDateTime":
datetime.datetime.now().strftime("%m/%d/%y %H:%M:%S")
}
# VAS Start Screen
message = visual.TextStim(
win,
text=
"Before we continue, please answer a few questions. \n\n Press the spacebar to continue.",
units='norm',
wrapWidth=3)
message.draw()
win.flip()
# waitUserInput(Df,message, win, params)
waitUserSpace(Df, params)
# event.waitKeys(maxWait=3)
# VAS (Anxiety)
startTime = time.time()
Dict["VAS_score"], Dict["VAS_RT"] = displayVAS(
Df, params, win, "How anxious do you feel right now?",
['Not anxious', 'Very anxious'])
Dict["VAS_RT"] = (time.time() - startTime) * 1000
tableWrite(Df, params, Dict) # Log the dict result on pandas dataFrame.
# VAS (Avoidance)
Dict["VAS_type"] = "Avoidance"
Dict["SessionStartDateTime"] = datetime.datetime.now().strftime(
"%m/%d/%y %H:%M:%S")
startTime = time.time()
Dict["VAS_score"], Dict["VAS_RT"] = displayVAS(
Df, params, win, "How much do you feel like taking part in the task?",
['Not at all', 'Very much'])
Dict["VAS_RT"] = (time.time() - startTime) * 1000
tableWrite(Df, params, Dict) # Log the dict result on pandas dataFrame.
# VAS (Tired)
Dict["VAS_type"] = "Tired"
Dict["SessionStartDateTime"] = datetime.datetime.now().strftime(
"%m/%d/%y %H:%M:%S")
startTime = time.time()
Dict["VAS_score"], Dict["VAS_RT"] = displayVAS(
Df, params, win, "How tired are you right now?",
['Not at all tired', 'Very tired'])
Dict["VAS_RT"] = (time.time() - startTime) * 1000
tableWrite(Df, params, Dict) # Log the dict result on pandas dataFrame.
# VAS (Mood)
Dict["VAS_type"] = "Mood"
Dict["SessionStartDateTime"] = datetime.datetime.now().strftime(
"%m/%d/%y %H:%M:%S")
startTime = time.time()
Dict["VAS_score"], Dict["VAS_RT"] = displayVAS(
Df, params, win,
"Think about your mood right now. \nHow would you describe it?",
['Worst mood ever', 'Best mood ever'])
Dict["VAS_RT"] = (time.time() - startTime) * 1000
tableWrite(Df, params, Dict) # Log the dict result on pandas dataFrame.
win.mouseVisible = True # ====================== # # ===== TaskRun1 ======= # # ====================== # win.mouseVisible = False win = DoorGamePlay(Df,DfTR,win,params,params['numTaskRun1'],port,"TaskRun1") win.mouseVisible = True # ====================== # # ======== VAS 1 ========= # # ====================== # win.mouseVisible = True message = visual.TextStim(win, text="Let's rest for a bit. Press the spacebar when you are ready to keep playing.", units='norm', wrapWidth=2) message.draw();win.flip(); waitUserSpace(Df,params) VASplay(Df,win,params,"VAS 1") win.mouseVisible = False # ====================== # # ======== Text Slide ========= # # ====================== # win.mouseVisible = False img1 = visual.ImageStim(win=win,image="./img/after_VAS2.jpg",units="pix",size=params['screenSize'],opacity=1) # waitUserInput(Df,img1, win, params,'pyglet') win.flip(); # ====================== # # ===== TaskRun2 ======= # # ====================== # win = DoorGamePlay(Df,DfTR,win,params,params['numTaskRun2'],port,"TaskRun2")
def DoorGamePlay(Df, DfTR, win, params, iterNum, port, SectionName):
params["idxTR"] = 0
width = params["screenSize"][0]
height = params["screenSize"][1]
params['subTrialCounter'] = 0
if SectionName == "TaskRun1":
img1 = visual.ImageStim(win=win,
image="./instruction/start_main_game.jpg",
units="pix",
opacity=1,
size=(width, height))
img1.draw()
win.flip()
# Wait for User input.
while (JoystickInput()
)['buttons_text'] == ' ': # while presenting stimuli
time.sleep(0.001)
img1.draw()
win.flip()
while (JoystickInput()
)['buttons_text'] != ' ': # while presenting stimuli
time.sleep(0.001)
# Eyetracker start recording
if params['EyeTrackerSupport']:
message = visual.TextStim(
win,
text=
"Eyetracker Calibration will start. \n\nPress the spacebar when you are ready.",
units='norm',
wrapWidth=2)
message.draw()
win.flip()
waitUserSpace(Df, params)
iohub_config = {
'eyetracker.hw.sr_research.eyelink.EyeTracker': {
'name': 'tracker',
'model_name': 'EYELINK 1000 DESKTOP',
'runtime_settings': {
'sampling_rate': 500,
'track_eyes': 'RIGHT'
}
}
}
# Start new ioHub server.
import psychopy.iohub.client
try:
io = launchHubServer(**iohub_config)
except:
q = psychopy.iohub.client.ioHubConnection.getActiveConnection(
).quit()
io = launchHubServer(**iohub_config)
# Get the eye tracker device.
tracker = io.devices.tracker
tracker.sendCommand(
"screen_pixel_coords = 0 0 %d %d" %
(params['screenSize'][0] - 1, params['screenSize'][1] - 1))
# save screen resolution in EDF data, so Data Viewer can correctly load experimental graphics
# see Data Viewer User Manual, Section 7: Protocol for EyeLink Data to Viewer Integration
tracker.sendMessage(
"DISPLAY_COORDS = 0 0 %d %d" %
(params['screenSize'][0] - 1, params['screenSize'][1] - 1))
# Eyetracker Calibration.
c = 'c'
while c != 'space':
tracker = EyeTrackerCalibration(tracker)
win.close()
win = visual.Window(params['screenSize'],
monitor="testMonitor",
color="black",
winType='pyglet')
message = visual.TextStim(
win,
text=
"Calibration is completed. Press the spacebar when you are ready to keep playing.\n Press 'c' to do calibration again.",
units='norm',
wrapWidth=2)
message.draw()
win.flip()
c = waitUserSpaceAndC(Df, params)
win.close()
# Eyetracker start recording
tracker.setRecordingState(True)
ELstartTime = time.time()
win.close()
win = visual.Window(params['screenSize'],
monitor="testMonitor",
color="black",
winType='pyglet')
win.mouseVisible = False
width = params["screenSize"][0]
height = params["screenSize"][1]
# Read Door Open Chance file provided by Rany.
doorOpenChanceMap = np.squeeze((pd.read_csv('./input/doorOpenChance.csv',
header=None)).values)
imgList = glob.glob(params['imageDir'] + params['imageSuffix'])
totalCoin = 0
if JoystickInput() == -1:
print("There is no available Joystick.")
exit()
# Shuffle image. # https://pynative.com/python-random-shuffle/
if params['EyeTrackerSupport']:
ELIdxRecord(DfTR, params, SectionName,
time.time() - ELstartTime, "",
"After Calibration Before Door Practice Game", "", "")
tracker.sendMessage('TRIAL_RESULT 0')
aoiTimeStart = time.time() * 1000
for i in range(iterNum):
# EDF labeling (start)
if params['EyeTrackerSupport']:
tracker.sendMessage('TRIALID %d' % params["idxTR"])
ELstartTime = time.time()
params['subTrialCounter'] += 1
Dict = {
"ExperimentName":
params['expName'],
"Subject":
params['subjectID'],
"Session":
params["Session"],
"Version":
params["Version"],
"Section":
SectionName,
"Subtrial":
params['subTrialCounter'],
"SessionStartDateTime":
datetime.datetime.now().strftime("%m/%d/%y %H:%M:%S")
}
# Pick up random image.
# randN = random.randint(0, len(imgList) - 1)
if i % 49 == 0:
random.shuffle(imgList)
imgFile = imgList[i % 49]
if platform.system() == 'Windows':
p, r = re.findall(r'\d+', imgFile.split('\\')[-1])
else:
p, r = re.findall(r'\d+', imgFile.split('/')[-1])
Dict["Punishment_magnitude"] = p
Dict["Reward_magnitude"] = r
# Display the image.
c = ['']
level = Dict["Distance_start"] = params["DistanceStart"]
width = params['width_bank'][level]
height = params['height_bank'][level]
img1 = visual.ImageStim(win=win,
image=imgFile,
units="pix",
opacity=1,
size=(width, height))
img1.draw()
win.flip()
startTime = time.time()
Dict["Distance_max"] = Dict["Distance_min"] = params["DistanceStart"]
Dict["Distance_lock"] = 0
MaxTime = params['DistanceLockWaitTime'] * 1000
# Initial screen
width = params['width_bank'][level]
height = params['height_bank'][level]
img1 = visual.ImageStim(win=win,
image=imgFile,
units="pix",
opacity=1,
size=(width, height))
triggerGo(port, params, r, p, 1) # Trigger: Door onset (conflict)
count = 0
joy = JoystickInput()
position = (0, 0)
# changed = True
while count < 3: # while presenting stimuli
# If waiting time is longer than 10 sec, exit this loop.
Dict["DoorAction_RT"] = (time.time() - startTime) * 1000
if Dict["DoorAction_RT"] > MaxTime:
c[0] = "timeisUp"
break
# if (sum(joy.getAllButtons()) != 0):
if joy['buttons_text'] != ' ':
count += 1
if count >= 2:
Dict["Distance_lock"] = 1
break
# joyUserInput = joy.getY()
joy = JoystickInput()
joyUserInput = joy['y']
changed = True
if joyUserInput < -0.5 and level < 100:
level += 2
level = min(100, level)
elif joyUserInput < -0.1 - params[
'sensitivity'] * 0.1 and level < 100:
level += 1
level = min(100, level)
elif joyUserInput > 0.5 and level > 0:
level -= 2
level = max(0, level)
elif joyUserInput > 0.1 + params['sensitivity'] * 0.1 and level > 0:
level -= 1
level = max(0, level)
else:
changed = False
width = params['width_bank'][level]
height = params['height_bank'][level]
# preInput = joyUserInput
Dict["Distance_max"] = max(Dict["Distance_max"], level)
Dict["Distance_min"] = min(Dict["Distance_min"], level)
img1.size = (width, height)
img1.draw()
win.flip()
get_keypress(Df, params)
if params['EyeTrackerSupport']:
positionTmp = position
position = tracker.getPosition()
if position is None:
position = positionTmp
aoiTimeEnd = time.time() * 1000
# Door
if changed == True:
tracker.sendMessage(
'!V IAREA %d %d RECTANGLE %d %d %d %d %d %s' %
(int(aoiTimeEnd - aoiTimeStart), 0, 1, 512 -
width * 105 / 1024, 390 - height * 160 / 768, 512 +
width * 105 / 1024, 390 + height * 200 / 768, 'DOOR'))
# Reward
tracker.sendMessage(
'!V IAREA %d %d RECTANGLE %d %d %d %d %d %s' %
(int(aoiTimeEnd - aoiTimeStart), 0, 2,
512 - width * 220 / 1024, 390 - height * 155 / 768,
512 - width * 130 / 1024, 390 + height * 200 / 768,
'Reward Bar (Green bar)'))
# Punishment bar
tracker.sendMessage(
'!V IAREA %d %d RECTANGLE %d %d %d %d %d %s' %
(int(aoiTimeEnd - aoiTimeStart), 0, 3,
512 + width * 220 / 1024, 390 - height * 155 / 768,
512 + width * 130 / 1024, 390 + height * 200 / 768,
'Punishment Bar (Red bar)'))
aoiTimeStart = aoiTimeEnd
triggerGo(port, params, r, p,
2) # Trigger: Joystick lock (start anticipation)
Dict["DistanceFromDoor_SubTrial"] = level
if params['EyeTrackerSupport']:
tracker.sendMessage('TRIAL_RESULT 0')
ELIdxRecord(DfTR, params, SectionName,
time.time() - ELstartTime, i,
"Playing Door Game (Before lock).", r, p)
tracker.sendMessage('TRIALID %d' % params["idxTR"])
tracker.sendMessage('!V IMGLOAD CENTER %s %d %d %d %d' %
(imgFile, 1024 / 2, 768 / 2, width, height))
# Door
tracker.sendMessage(
'!V IAREA RECTANGLE %d %d %d %d %d %s' %
(1, 512 - width * 105 / 1024, 390 - height * 160 / 768,
512 + width * 105 / 1024, 390 + height * 200 / 768, 'DOOR'))
# Reward
tracker.sendMessage(
'!V IAREA RECTANGLE %d %d %d %d %d %s' %
(2, 512 - width * 220 / 1024, 390 - height * 155 / 768,
512 - width * 130 / 1024, 390 + height * 200 / 768,
'Reward Bar (Green bar)'))
# Punishment bar
tracker.sendMessage(
'!V IAREA RECTANGLE %d %d %d %d %d %s' %
(3, 512 + width * 220 / 1024, 390 - height * 155 / 768,
512 + width * 130 / 1024, 390 + height * 200 / 768,
'Punishment Bar (Red bar)'))
ELstartTime = time.time()
# Door Anticipation time
Dict["Door_anticipation_time"] = random.uniform(2, 4) * 1000
time.sleep(Dict["Door_anticipation_time"] / 1000)
if params['EyeTrackerSupport']:
tracker.sendMessage('TRIAL_RESULT 0')
ELIdxRecord(DfTR, params, SectionName,
time.time() - ELstartTime, i,
"After lock: Door Anticipation Time.", r, p)
tracker.sendMessage('TRIALID %d' % params["idxTR"])
# tracker.sendMessage('!V IMGLOAD CENTER %s %d %d %d %d' % ('./img/practice/combined.jpg', 1024 / 2, 768 / 2, width, height))
# tracker.sendMessage('!V IAREA RECTANGLE %d %d %d %d %d %s' % (1, 512-width*50/1024,
# 390-height*40/768,
# 512+width*50/1024,
# 390+height*50/768,
# 'Reward (Question mark)'))
ELstartTime = time.time()
Dict["Door_outcome"] = ""
Dict["Door_opened"] = ""
if random.random() > doorOpenChanceMap[level]:
Dict["Door_opened"] = "closed"
img1.draw()
win.flip()
triggerGo(port, params, r, p, 5) # Door outcome: it didn’t open
# event.waitKeys(maxWait=2)
if params['EyeTrackerSupport']:
# tracker.sendMessage('TRIAL_RESULT 0')
ELIdxRecord(DfTR, params, SectionName,
time.time() - ELstartTime, i,
"Reward screen (Door not opened) displayed.", r, p)
# tracker.sendMessage('TRIALID %d' % params["idxTR"])
ELstartTime = time.time()
else:
Dict["Door_opened"] = "opened"
if random.random() < 0.5:
Dict["Door_outcome"] = "punishment"
awardImg = "./img/outcomes/" + p + "_punishment.jpg"
img2 = visual.ImageStim(win=win,
image=awardImg,
units="pix",
opacity=1,
pos=[0, -height * 0.028],
size=(width * 0.235, height * 0.464))
message = visual.TextStim(win, text="-" + p, wrapWidth=2)
message.pos = (0, 50)
img1.draw()
img2.draw()
message.draw()
win.flip()
# img1.draw();
# img2.draw();
# win.flip()
triggerGo(port, params, r, p, 4) #Door outcome: punishment
# sound1 = sound.Sound("./img/sounds/punishment_sound.wav")
# sound1.play()
# event.waitKeys(maxWait=2)
# sound1.stop()
totalCoin -= int(p)
# displayText(win, "-" + str(p))
else:
Dict["Door_outcome"] = "reward"
awardImg = "./img/outcomes/" + r + "_reward.jpg"
img2 = visual.ImageStim(win=win,
image=awardImg,
units="pix",
opacity=1,
pos=[0, -height * 0.028],
size=(width * 0.235, height * 0.464))
message = visual.TextStim(win, text="+" + r, wrapWidth=2)
message.pos = (0, 50)
img1.draw()
img2.draw()
win.flip()
triggerGo(port, params, r, p, 3) # Door outcome: reward
totalCoin += int(r)
if params['EyeTrackerSupport']:
ELIdxRecord(DfTR, params, SectionName,
time.time() - ELstartTime, i,
"Reward screen (Door Opened) displayed.", r, p)
if params['EyeTrackerSupport']:
# imgScreenShot = './img/outscreenshot/' + str(params['idxImg']) + '.jpg'
# imgScreenShot2 = './output/img/outscreenshot/' + str(params['idxImg']) + '.jpg'
if not os.path.exists('img/outscreenshot'):
os.makedirs('img/outscreenshot')
if not os.path.exists('output/img/outscreenshot'):
os.makedirs('output/img/outscreenshot')
imgScreenShot = './img/outscreenshot/ver' + str(
Dict['Version']) + '_' + Dict["Door_opened"] + '_' + Dict[
"Door_outcome"] + '_' + str(p) + '_' + str(r) + '_' + str(
level) + '.jpg'
imgScreenShot2 = './output/img/outscreenshot/ver' + str(
Dict['Version']) + '_' + Dict["Door_opened"] + '_' + Dict[
"Door_outcome"] + '_' + str(p) + '_' + str(r) + '_' + str(
level) + '.jpg'
win.getMovieFrame(
) # Defaults to front buffer, I.e. what's on screen now.
win.saveMovieFrames(imgScreenShot)
shutil.copyfile(imgScreenShot, imgScreenShot2)
tracker.sendMessage(
'!V IMGLOAD CENTER %s %d %d %d %d' %
(imgScreenShot, 1024 / 2, 768 / 2, params["screenSize"][0],
params["screenSize"][1]))
tracker.sendMessage(
'!V IAREA RECTANGLE %d %d %d %d %d %s' %
(1, 512 - width * 105 / 1024, 390 - height * 160 / 768,
512 + width * 105 / 1024, 390 + height * 200 / 768,
'Reward/punishment/closed'))
if Dict["Door_outcome"] == "reward":
mixer.init()
mixer.music.load("./img/sounds/new_reward.mp3")
mixer.music.play()
event.waitKeys(maxWait=2)
mixer.music.stop()
# sound1 = sound.Sound("./img/sounds/reward_sound.wav")
# sound1.play()
# event.waitKeys(maxWait=2)
# sound1.stop()
elif Dict["Door_outcome"] == "punishment":
mixer.init()
mixer.music.load("./img/sounds/punishment_sound.mp3")
mixer.music.play()
event.waitKeys(maxWait=2)
mixer.music.stop()
# sound1 = sound.Sound("./img/sounds/punishment_sound.wav")
# sound1.play()
# event.waitKeys(maxWait=2)
# sound1.stop()
else:
event.waitKeys(maxWait=2)
if params['EyeTrackerSupport']:
tracker.sendMessage('TRIAL_RESULT 0')
# ITI duration
if params['EyeTrackerSupport']:
# Blank Screen
tracker.sendMessage('TRIALID %d' % params["idxTR"])
ELstartTime = time.time()
width = params["screenSize"][0]
height = params["screenSize"][1]
img1 = visual.ImageStim(win=win,
image="./img/iti.jpg",
units="pix",
opacity=1,
size=(width, height))
img1.draw()
win.flip()
tracker.sendMessage('!V IMGLOAD CENTER %s %d %d' %
("./img/iti.jpg", width / 2, height / 2))
time.sleep(1)
tracker.sendMessage('TRIAL_RESULT 0')
ELIdxRecord(DfTR, params, SectionName,
time.time() - ELstartTime, i,
"Blank screen displayed (before ITI).", "", "")
# ITI duration
tracker.sendMessage('TRIALID %d' % params["idxTR"])
ELstartTime = time.time()
startTime = time.time()
width = params["screenSize"][0]
height = params["screenSize"][1]
tracker.sendMessage(
'!V IMGLOAD CENTER %s %d %d' %
("./img/ITI_fixation.jpg", width / 2, height / 2))
tracker.sendMessage(
'!V IAREA RECTANGLE %d %d %d %d %d %s' %
(1, int(335 * width / 1024), int(217 * height / 768),
int(689 * width / 1024), int(
561 * height / 768), 'fixation treasure'))
WaitEyeGazed(win, params, tracker, False)
Dict["ITI_duration"] = time.time() - startTime
tracker.sendMessage('TRIAL_RESULT 0')
ELIdxRecord(DfTR, params, SectionName,
time.time() - ELstartTime, i, "ITI screen displayed.",
"", "")
else:
width = params["screenSize"][0]
height = params["screenSize"][1]
img1 = visual.ImageStim(win=win,
image="./img/iti.jpg",
units="pix",
opacity=1,
size=(width, height))
img1.draw()
win.flip()
Dict["ITI_duration"] = random.uniform(1.5, 3.5) * 1000
time.sleep(Dict["ITI_duration"] / 1000)
Dict["Total_coins"] = totalCoin
tableWrite(Df, params,
Dict) # Log the dict result on pandas dataFrame.
# Eyetracker finish recording
if params['EyeTrackerSupport']:
# Eyetracker stop recording
tracker.setRecordingState(False)
# open a connection to the tracker and download the result file.
trackerIO = pylink.EyeLink('100.1.1.1')
trackerIO.receiveDataFile("et_data.EDF", params[SectionName])
# Stop the ioHub Server
io.quit()
trackerIO.close()
win.mouseVisible = True
return win
def PracticeGamePlay(Df, DfTR,win, params, iterNum, port,SectionName):
# Eyetracker start recording
params["idxTR"] = 0
if params['EyeTrackerSupport']:
message = visual.TextStim(win,
text="Eyetracker Calibration will start. \n\nPress the spacebar when you are ready.",
units='norm', wrapWidth=2)
message.draw();
win.flip();
waitUserSpace(Df, params)
iohub_config = {'eyetracker.hw.sr_research.eyelink.EyeTracker':
{'name': 'tracker',
'model_name': 'EYELINK 1000 DESKTOP',
'runtime_settings': {'sampling_rate': 500,
'track_eyes': 'LEFT'}
}
}
# Start new ioHub server.
import psychopy.iohub.client
try:
io = launchHubServer(**iohub_config)
except:
q = psychopy.iohub.client.ioHubConnection.getActiveConnection().quit()
io = launchHubServer(**iohub_config)
# Get the eye tracker device.
tracker = io.devices.tracker
tracker.sendCommand("screen_pixel_coords = 0 0 %d %d" % (params['screenSize'][0] - 1, params['screenSize'][1] - 1))
# save screen resolution in EDF data, so Data Viewer can correctly load experimental graphics
# see Data Viewer User Manual, Section 7: Protocol for EyeLink Data to Viewer Integration
tracker.sendMessage("DISPLAY_COORDS = 0 0 %d %d" % (params['screenSize'][0] - 1, params['screenSize'][1] - 1))
# Eyetracker Calibration.
c = 'c'
while c != 'space':
tracker = EyeTrackerCalibration(tracker)
win.close()
win = visual.Window(params['screenSize'], monitor="testMonitor", color="black", winType='pyglet')
message = visual.TextStim(win,
text="Calibration is completed. Press the spacebar when you are ready to keep playing.\n Press 'c' to do calibration again.",
units='norm', wrapWidth=2)
message.draw();
win.flip();
c = waitUserSpaceAndC(Df, params)
win.close()
# Eyetracker start recording
tracker.setRecordingState(True)
ELstartTime = time.time()
win.close()
win = visual.Window(params['screenSize'], monitor="testMonitor", color="black", winType='pyglet')
win.mouseVisible = False
width = params["screenSize"][0]
height = params["screenSize"][1]
# Start Section Display
img1 = visual.ImageStim(win=win, image="./instruction/practice_start.jpg", units="pix", opacity=1,size=(width, height))
# waitUserInput(Df,img1, win, params,'glfw')
img1.draw();win.flip()
# Wait for User input.
while (JoystickInput())['buttons_text'] == ' ': # while presenting stimuli
time.sleep(0.001)
img1.draw();
win.flip()
while (JoystickInput())['buttons_text'] != ' ': # while presenting stimuli
time.sleep(0.001)
# Read Door Open Chance file provided by Rany.
imgList = glob.glob("./img/practice/*_door.jpg")
# Joystick Initialization
if JoystickInput() == -1:
print("There is no available Joystick.")
exit()
# Eyetracker label record
# tracker.sendMessage('TRIAL_RESULT 0') # # EDF labeling (end)
if params['EyeTrackerSupport']:
ELIdxRecord(DfTR, params, SectionName, time.time()-ELstartTime,"", "After Calibration Before Door Practice Game","","")
tracker.sendMessage('TRIAL_RESULT 0')
# joy = joystick.Joystick(0) # id must be <= nJoys - 1
aoiTimeStart = time.time() * 1000
for i in range(iterNum):
# EDF labeling (start)
if params['EyeTrackerSupport']:
tracker.sendMessage('TRIALID %d' % params["idxTR"])
ELstartTime = time.time()
Dict = {
"ExperimentName" : params['expName'],
"Subject" : params['subjectID'],
"Session" : params["Session"],
"Version" : params["Version"],
"Section" : SectionName,
"SessionStartDateTime" : datetime.datetime.now().strftime("%m/%d/%y %H:%M:%S")
}
# Pick up random image.
randN = random.randint(0, len(imgList) - 1)
imgFile = imgList[randN]
# Display the image.
c = ['']
level = Dict["Distance_start"] = params["DistanceStart"]
startTime = time.time()
Dict["Distance_max"] = Dict["Distance_min"] = params["DistanceStart"]
Dict["Distance_lock"] = 0
MaxTime = params['DistanceLockWaitTime'] * 1000
# Initial screen
width = params['width_bank'][level]
height = params['height_bank'][level]
img1 = visual.ImageStim(win=win, image=imgFile, units="pix", opacity=1, size=(width, height))
# img1.draw();
if params['EyeTrackerSupport']:
position = (0,0)
circle = visual.Circle(win=win, units="pix", fillColor='black', lineColor='white', edges=1000, pos=position,
radius=5)
# tracker.sendMessage('!V IMGLOAD CENTER %s %d %d' % (imgFile, 1024/2, 768 / 2))
triggerGo(port, params, 1, 1, 1) # Door onset (conflict)
win.flip()
count = 0
joy = JoystickInput()
while count < 4: # while presenting stimuli
# If waiting time is longer than 10 sec, exit this loop.
Dict["DoorAction_RT"] = (time.time() - startTime) * 1000
if Dict["DoorAction_RT"] > MaxTime:
c[0] = "timeisUp"
break
# if (sum(joy.getAllButtons()) != 0):
# if joy.getButton(0)!=0:
if joy['buttons_text'] != ' ':
count += 1
if count >= 4:
Dict["Distance_lock"] = 1
break
joy = JoystickInput()
joyUserInput = joy['y']
changed = True
if joyUserInput < -0.5 and level < 100:
level += 2
level = min(100,level)
elif joyUserInput < -0.1-params['sensitivity']*0.1 and level < 100:
level += 1
level = min(100,level)
elif joyUserInput > 0.5 and level > 0:
level -= 2
level = max(0,level)
elif joyUserInput > 0.1+params['sensitivity']*0.1 and level > 0:
level -= 1
level = max(0, level)
else:
changed = False
get_keypress(Df,params)
width = params['width_bank'][level]
height = params['height_bank'][level]
# preInput = joyUserInput
Dict["Distance_max"] = max(Dict["Distance_max"], level)
Dict["Distance_min"] = min(Dict["Distance_min"], level)
img1.size = (width, height)
img1.draw()
if params['EyeTrackerSupport']:
positionTmp = position
position = tracker.getPosition()
if position is None:
position = positionTmp
circle.pos = position
if params['eyeTrackCircle']:
circle.draw()
aoiTimeEnd = time.time() * 1000
if changed == True:
tracker.sendMessage('!V IAREA %d %d RECTANGLE %d %d %d %d %d %s' % (int(aoiTimeEnd-aoiTimeStart),0,
1, 512 - width * 105 / 1024,
390 - height * 160 / 768,
512 + width * 105 / 1024,
390 + height * 200 / 768, 'DOOR'))
aoiTimeStart = aoiTimeEnd
win.flip()
if params['EyeTrackerSupport']:
tracker.sendMessage('TRIAL_RESULT 0')
ELIdxRecord(DfTR, params,SectionName,time.time()-ELstartTime,i, "Playing Door Game (Before lock).","","")
tracker.sendMessage('TRIALID %d' % params["idxTR"])
tracker.sendMessage('!V IMGLOAD CENTER %s %d %d %d %d' % (imgFile, 1024/2, 768 / 2, width, height))
tracker.sendMessage('!V IAREA RECTANGLE %d %d %d %d %d %s' % (1, 512-width*105/1024,
390-height*160/768,
512+width*105/1024,
390+height*200/768,
'DOOR'))
ELstartTime = time.time()
triggerGo(port, params, 1, 1, 2) # Joystick lock (start anticipation)
Dict["DistanceFromDoor_SubTrial"] = level
# Door Anticipation time
Dict["Door_anticipation_time"] = random.uniform(2, 4) * 1000
time.sleep(Dict["Door_anticipation_time"] / 1000)
if params['EyeTrackerSupport']:
tracker.sendMessage('TRIAL_RESULT 0')
ELIdxRecord(DfTR, params,SectionName,time.time()-ELstartTime,i, "After lock: Door Anticipation Time.","","")
tracker.sendMessage('TRIALID %d' % params["idxTR"])
tracker.sendMessage('!V IMGLOAD CENTER %s %d %d %d %d' % ('./img/practice/combined.jpg', 1024 / 2, 768 / 2, width, height))
tracker.sendMessage('!V IAREA RECTANGLE %d %d %d %d %d %s' % (1, 512-width*50/1024,
390-height*40/768,
512+width*50/1024,
390+height*50/768,
'Reward (Question mark)'))
ELstartTime = time.time()
awardImg = "./img/practice/practice_outcome.jpg"
img2 = visual.ImageStim(win=win, image=awardImg, units="pix", opacity=1, pos=[0, -height * 0.028],
size=(width* 0.235, height* 0.464))
img1.draw();img2.draw();win.flip()
event.waitKeys(maxWait=2)
if params['EyeTrackerSupport']:
tracker.sendMessage('TRIAL_RESULT 0')
ELIdxRecord(DfTR, params,SectionName,time.time()-ELstartTime,i, "Reward screen displayed.","","")
if params['EyeTrackerSupport']:
# Blank screen
tracker.sendMessage('TRIALID %d' % params["idxTR"])
ELstartTime = time.time()
width = params["screenSize"][0]
height = params["screenSize"][1]
img1 = visual.ImageStim(win=win, image="./img/iti.jpg", units="pix", opacity=1, size=(width, height))
img1.draw();
win.flip()
tracker.sendMessage('!V IMGLOAD CENTER %s %d %d' % ("./img/iti.jpg", width/2, height/2))
time.sleep(1)
tracker.sendMessage('TRIAL_RESULT 0')
ELIdxRecord(DfTR, params,SectionName,time.time()-ELstartTime,i, "Blank screen displayed (before ITI).","","")
# ITI duration
tracker.sendMessage('TRIALID %d' % params["idxTR"])
ELstartTime = time.time()
startTime = time.time()
width = params["screenSize"][0]
height = params["screenSize"][1]
tracker.sendMessage('!V IMGLOAD CENTER %s %d %d' % ("./img/ITI_fixation.jpg", width/2, height/2))
tracker.sendMessage('!V IAREA RECTANGLE %d %d %d %d %d %s' % (
1, int(335 * width / 1024), int(217 * height / 768), int(689 * width / 1024), int(561 * height / 768),
'fixation treasure'))
WaitEyeGazed(win, params, tracker,'eyeTrackCircle')
Dict["ITI_duration"] = time.time() - startTime
tracker.sendMessage('TRIAL_RESULT 0')
ELIdxRecord(DfTR, params,SectionName,time.time()-ELstartTime,i, "ITI screen displayed.","","")
else:
# ITI duration
width = params["screenSize"][0]
height = params["screenSize"][1]
img1 = visual.ImageStim(win=win, image="./img/iti.jpg", units="pix", opacity=1, size=(width, height))
img1.draw();win.flip();
Dict["ITI_duration"] = random.uniform(1.5, 3.5) * 1000
time.sleep(Dict["ITI_duration"] / 1000)
tableWrite(Df, params,Dict) # Log the dict result on pandas dataFrame.
# Eyetracker finish recording
if params['EyeTrackerSupport']:
# Eyetracker stop recording
tracker.setRecordingState(False)
# open a connection to the tracker and download the result file.
trackerIO = pylink.EyeLink('100.1.1.1')
trackerIO.receiveDataFile("et_data.EDF", params[SectionName])
# Stop the ioHub Server
io.quit()
trackerIO.close()
win.mouseVisible = True
return win
def QuestionPlay(Df, win, params, SectionName):
Dict = {
'ExperimentName':
params['expName'],
"Subject":
params['subjectID'],
"Session":
params['Session'],
"Version":
params['Version'],
"Section":
SectionName,
"SessionStartDateTime":
datetime.datetime.now().strftime("%m/%d/%y %H:%M:%S")
}
width = params["screenSize"][0]
height = params["screenSize"][1]
# Question (Won)
Dict["Q_type"] = "Won"
startTime = time.time()
Dict["Q_score"], Dict["Q_RT"] = displayVAS(
Df, params, win, "How many coins do you think you won?",
['Won very few', 'Won very many'])
Dict["Q_RT"] = (time.time() - startTime) * 1000
tableWrite(Df, params, Dict) # Log the dict result on pandas dataFrame.
# Question (Lost)
Dict["Q_type"] = "Lost"
Dict["SessionStartDateTime"] = datetime.datetime.now().strftime(
"%m/%d/%y %H:%M:%S")
startTime = time.time()
Dict["Q_score"], Dict["Q_RT"] = displayVAS(
Df, params, win, "How many coins do you think you lost?",
['Lost very few', 'Lost very many'])
Dict["Q_RT"] = (time.time() - startTime) * 1000
tableWrite(Df, params, Dict) # Log the dict result on pandas dataFrame.
# Question (Monster versus Coin)
Dict["Q_type"] = "Before"
Dict["SessionStartDateTime"] = datetime.datetime.now().strftime(
"%m/%d/%y %H:%M:%S")
startTime = time.time()
Dict["Q_score"], Dict["Q_RT"] = displayVAS(
Df, params, win,
"Before the door opened, what did you think you would see?",
['Monster', 'Coins'])
Dict["Q_RT"] = (time.time() - startTime) * 1000
tableWrite(Df, params, Dict) # Log the dict result on pandas dataFrame.
# Question (Monster)
Dict["Q_type"] = "Monster"
Dict["SessionStartDateTime"] = datetime.datetime.now().strftime(
"%m/%d/%y %H:%M:%S")
startTime = time.time()
Dict["Q_score"], Dict["Q_RT"] = displayVAS(
Df, params, win,
"How often did you see the monster when the door opened?",
['Never', 'All the time'])
Dict["Q_RT"] = (time.time() - startTime) * 1000
tableWrite(Df, params, Dict) # Log the dict result on pandas dataFrame.
# Question (Coins)
Dict["Q_type"] = "Coins"
Dict["SessionStartDateTime"] = datetime.datetime.now().strftime(
"%m/%d/%y %H:%M:%S")
startTime = time.time()
Dict["Q_score"], Dict["Q_RT"] = displayVAS(
Df, params, win, "How often did you win coins when the door opened?",
['Never', 'All the time'])
Dict["Q_RT"] = (time.time() - startTime) * 1000
tableWrite(Df, params, Dict) # Log the dict result on pandas dataFrame.
# Question (Performance)
Dict["Q_type"] = "Performance"
Dict["SessionStartDateTime"] = datetime.datetime.now().strftime(
"%m/%d/%y %H:%M:%S")
startTime = time.time()
Dict["Q_score"], Dict["Q_RT"] = displayVAS(
Df, params, win, "How do you feel about how well you’ve done so far?",
["I didn't do well", "I did very well"])
Dict["Q_RT"] = (time.time() - startTime) * 1000
# Log the dict result on pandas dataFrame.
tableWrite(Df, params, Dict)
# Ending Screen
img1 = visual.ImageStim(win=win,
image="./instruction/end_slide.jpg",
units="pix",
opacity=1,
size=(width, height))
# waitUserInput(Df,img1, win, params)
img1.draw()
win.flip()
waitUserSpace(Df, params)