def test_staircaseDB(self):
nTrials = 20
stairs = data.StairHandler(startVal=0.8,
nUp=1,
nDown=3,
minVal=0,
maxVal=1,
nReversals=4,
stepSizes=[0.4, 0.2, 0.2, 0.1],
nTrials=nTrials,
stepType='db')
responsesToMake = makeBasicResponseCycles()
levels = [
0.8, 0.763994069, 0.729608671, 0.696770872, 0.665411017,
0.680910431, 0.696770872, 0.713000751, 0.729608671, 0.729608671,
0.729608671, 0.713000751, 0.713000751, 0.72125691, 0.729608671,
0.738057142, 0.746603441, 0.746603441, 0.746603441, 0.738057142
]
reversals = [0.665411017, 0.729608671, 0.713000751, 0.746603441]
self.doTrials(stairs, responsesToMake[:nTrials], levels=levels)
def test_staircaseLinear(self):
nTrials = 20
stairs = data.StairHandler(startVal=0.8,
nUp=1,
nDown=3,
minVal=0,
maxVal=1,
nReversals=4,
stepSizes=[0.1, 0.01, 0.001],
nTrials=nTrials,
stepType='lin')
responsesToMake = makeBasicResponseCycles()
levels = [
0.8, 0.7, 0.6, 0.5, 0.4, 0.41, 0.42, 0.43, 0.44, 0.44, 0.44, 0.439,
0.439, 0.44, 0.441, 0.442, 0.443, 0.443, 0.443, 0.442
]
reversals = [0.4, 0.44, 0.439, 0.443]
self.doTrials(stairs,
responsesToMake[:nTrials],
levels=levels,
reversals=reversals)
def test_applyInitialRule_False(self):
start_val = 10
step_sizes = 2
staircase = data.StairHandler(startVal=start_val,
stepSizes=step_sizes,
nReversals=2,
nUp=1,
nDown=2,
applyInitialRule=False,
stepType='lin')
responses = [0, 1, 1, 0]
intensities = [10, 12, 12, 10]
for r in responses:
try:
staircase.__next__()
staircase.addResponse(r)
except StopIteration:
break
assert staircase.data == responses
assert staircase.intensities == intensities
def test_StairHandlerLog(self):
nTrials = 20
startVal, minVal, maxVal = 0.8, 0, 1
# We try to reproduce the values from test_StairHandlerDb().
stepSizes = [0.4 / 20, 0.2 / 20, 0.2 / 20, 0.1 / 20]
nUp, nDown = 1, 3
nReversals = 4
stepType = 'log'
self.stairs = data.StairHandler(startVal=startVal,
nUp=nUp,
nDown=nDown,
minVal=minVal,
maxVal=maxVal,
nReversals=nReversals,
stepSizes=stepSizes,
nTrials=nTrials,
stepType=stepType)
self.responses = makeBasicResponseCycles(cycles=3,
nCorrect=4,
nIncorrect=4,
length=20)
self.intensities = [
0.8, 0.763994069, 0.729608671, 0.696770872, 0.665411017,
0.680910431, 0.696770872, 0.713000751, 0.729608671, 0.729608671,
0.729608671, 0.713000751, 0.713000751, 0.72125691, 0.729608671,
0.738057142, 0.746603441, 0.746603441, 0.746603441, 0.738057142
]
self.reversalPoints = [4, 10, 12, 18]
self.reversalIntensities = list(
itemgetter(*self.reversalPoints)(self.intensities))
self.simulate()
self.checkSimulationResults()
def test_StairHandlerDb(self):
nTrials = 20
startVal, minVal, maxVal = 0.8, 0, 1
stepSizes = [0.4, 0.2, 0.2, 0.1]
nUp, nDown = 1, 3
nReversals = 4
stepType = 'db'
self.stairs = data.StairHandler(startVal=startVal,
nUp=nUp,
nDown=nDown,
minVal=minVal,
maxVal=maxVal,
nReversals=nReversals,
stepSizes=stepSizes,
nTrials=nTrials,
stepType=stepType)
self.responses = makeBasicResponseCycles(cycles=3,
nCorrect=4,
nIncorrect=4,
length=20)
self.intensities = [
0.8, 0.763994069, 0.729608671, 0.696770872, 0.665411017,
0.680910431, 0.696770872, 0.713000751, 0.729608671, 0.729608671,
0.729608671, 0.713000751, 0.713000751, 0.72125691, 0.729608671,
0.738057142, 0.746603441, 0.746603441, 0.746603441, 0.738057142
]
self.reversalIntensities = [
0.665411017, 0.729608671, 0.713000751, 0.746603441
]
self.simulate()
self.checkSimulationResults()
def create_structure():
'''
This function creates the core structure of the experiment, which is
a dictionary containing all important components of the experiment.
It is used to store all the settings, experimental components like stimuli
or response screens, and participant responses.
On top of results datafiles and logs, this structure is saved into a json
file after each session, allowing to retrieve many additional information
about the experiments execution.
'''
structure = {}
gui.DlgFromDict(expInfo)
structure['expInfo'] = expInfo
structure['performTraining'] = performTraining
structure['performStaircase'] = performStaircase
structure['performSession'] = performSession
structure['EEG'] = EEG
structure['attention'] = attention
# Create clocks for the experiment
structure['globalClock'] = core.Clock()
structure['trainingClock'] = core.Clock()
structure['trialClock'] = core.Clock()
# Create a chosen response device
structure['responseDevice'] = responseDevice
structure['keyBoard'] = keyboard.Keyboard()
structure['buttonBox'] = None
structure['stairSamples'] = stairSamples
if responseDevice == 'buttonBox':
try: # to use the Cedrus response box
import pyxid2 as pyxid
except ImportError:
import pyxid
for n in range(10): # doesn't always work first time!
try:
devices = pyxid.get_xid_devices()
core.wait(0.1)
structure['buttonBox'] = devices[0]
structure['buttonBox'].clock = core.Clock()
break # found the device so can break the loop
except Exception:
pass
if not structure['buttonBox']:
logging.error('could not find a Cedrus device.')
core.quit()
# Create a filename for the results
date = data.getDateStr()
structure['expFileName'] = join(resultsFolder, expInfo['ID'] + '_' + date)
# Create an experimental window
structure['win'] = visual.Window(size=[1920, 1080],
screen=1,
fullscr=True,
checkTiming=True,
color='grey',
monitor='testMonitor',
colorSpace='rgb')
structure['frameRate'] = round(structure['win'].getActualFrameRate(), 0)
structure['expInfo']['frameRate'] = structure['frameRate']
structure['data'] = data.ExperimentHandler(
name='test', extraInfo=expInfo, dataFileName=structure['expFileName'])
structure['instructionScreen'] = visual.ImageStim(win=structure['win'],
image=None,
interpolate=True,
depth=-1.0)
crossVert = [(6, 1), (6, -1), (1, -1), (1, -6), (-1, -6), (-1, -1),
(-6, -1), (-6, 1), (-1, 1), (-1, 6), (1, 6), (1, 1)]
structure['fixationCross'] = visual.ShapeStim(win=structure['win'],
vertices=crossVert,
units='pix',
lineWidth=0,
fillColor='white')
structure['dot'] = visual.Circle(win=structure['win'],
units='pix',
size=8,
fillColor='white',
lineWidth=0)
structure['cuelocation'] = visual.ShapeStim(win=structure['win'],
name='polygon',
vertices='star7',
size=(10, 10),
units='pix',
ori=0,
pos=(0, 0),
lineWidth=0.01,
lineColor='black',
lineColorSpace='rgb',
fillColor='black',
fillColorSpace='rgb',
opacity=1,
depth=0.0,
interpolate=True)
structure['cuecentral'] = visual.ShapeStim(win=structure['win'],
name='polygon',
vertices='star7',
size=(10, 10),
units='pix',
ori=0,
pos=(0, 0),
lineWidth=0.01,
lineColor='black',
lineColorSpace='rgb',
fillColor='black',
fillColorSpace='rgb',
opacity=1,
depth=0.0,
interpolate=True)
structure['cueupperleft'] = visual.ShapeStim(win=structure['win'],
name='polygon',
vertices='star7',
size=(10, 10),
units='pix',
ori=0,
pos=(-77, 77),
lineWidth=0.01,
lineColor='black',
lineColorSpace='rgb',
fillColor='black',
fillColorSpace='rgb',
opacity=1,
depth=0.0,
interpolate=True)
structure['cueupperright'] = visual.ShapeStim(win=structure['win'],
name='polygon',
vertices='star7',
size=(10, 10),
units='pix',
ori=0,
pos=(77, 77),
lineWidth=0.01,
lineColor='black',
lineColorSpace='rgb',
fillColor='black',
fillColorSpace='rgb',
opacity=1,
depth=0.0,
interpolate=True)
structure['cuelowerleft'] = visual.ShapeStim(win=structure['win'],
name='polygon',
vertices='star7',
size=(10, 10),
units='pix',
ori=0,
pos=(-77, -77),
lineWidth=0.01,
lineColor='black',
lineColorSpace='rgb',
fillColor='black',
fillColorSpace='rgb',
opacity=1,
depth=0.0,
interpolate=True)
structure['cuelowerright'] = visual.ShapeStim(win=structure['win'],
name='polygon',
vertices='star7',
size=(10, 10),
units='pix',
ori=0,
pos=(77, -77),
lineWidth=0.01,
lineColor='black',
lineColorSpace='rgb',
fillColor='black',
fillColorSpace='rgb',
opacity=1,
depth=0.0,
interpolate=True)
structure['nocue'] = visual.ShapeStim(win=structure['win'],
vertices=crossVert,
units='pix',
lineWidth=0,
fillColor='white')
arrowVert = [(-15, 3), (-15, -3), (0, -3), (0, -9), (15, 0), (0, 9),
(0, 3)]
structure['arrow'] = visual.ShapeStim(win=structure['win'],
units='pix',
vertices=arrowVert,
fillColor='black',
lineWidth=0)
structure['gabor'] = visual.GratingStim(win=structure['win'],
name='gaborUpLeft',
units='pix',
tex='sin',
mask='gauss',
ori=45,
pos=(0, 0),
size=(128, 128),
sf=1.5 / 40.0,
phase=1.0,
color=1.0,
colorSpace='rgb',
opacity=0.2,
texRes=512,
interpolate=True,
depth=-2.0)
structure['responseScreen'] = visual.ImageStim(win=structure['win'],
image=None,
interpolate=True,
depth=-1.0)
structure['fixationShape'] = fixation_shape
structure['fixationDur'] = fixation_dur
structure['postFixationDur'] = post_fixation_dur
structure['cueDur'] = cue_dur
structure['cueISI'] = cue_ISI
structure['gaborDur'] = gabor_dur
structure['blockLength'] = block_length
# Create instruction screens
structure['welcome'] = join('materials/instructions', '1_welcome.png')
structure['training_instruction'] = join('materials/instructions',
'2_instruction.png')
structure['location_instruction'] = join('materials/instructions',
'3_location_demo.png')
structure['orientation_instruction'] = join('materials/instructions',
'4_orientation_demo.png')
structure['pas_instruction'] = join('materials/instructions',
'5_pas_demo.png')
structure['training_start'] = join('materials/instructions',
'6_training_start.png')
structure['training_end'] = join('materials/instructions',
'7_training_end.png')
structure['correct_screen'] = join('materials/instructions',
'8_correct.png')
structure['incorrect_screen'] = join('materials/instructions',
'9_incorrect.png')
structure['staircase_start'] = join('materials/instructions',
'10_staircase_start.png')
structure['session_start'] = join('materials/instructions',
'11_session_start.png')
structure['break'] = join('materials/instructions', '12_break.png')
structure['end'] = join('materials/instructions', '13_end.png')
structure['training_trials_file'] = join('materials',
'training_trials.csv')
# structure['trainingConditions'] = data.importConditions(structure['training_trials_file'])
structure['trainingConditions'] = data.importConditions(
structure['training_trials_file'], selection='0:5')
structure['trainingTrials'] = data.TrialHandler(
structure['trainingConditions'], nReps=1)
structure['data'].addLoop(structure['trainingTrials'])
structure['trials_file'] = join('materials', 'experiment_trials.csv')
structure['experimentConditions'] = data.importConditions(
structure['trials_file'])
structure['experimentTrials'] = data.TrialHandler(
structure['experimentConditions'], nReps=trial_num / 64)
structure['data'].addLoop(structure['experimentTrials'])
#structure['trials_file'] = join('materials', 'experiment_trials.csv')
#structure['experimentConditions'] = data.importConditions(structure['trials_file'])
#structure['experimentTrials'] = data.TrialHandler(structure['experimentConditions'], nReps=trial_num/64)
#structure['data'].addLoop(structure['experimentTrials'])
structure['locationResponse'] = locationResponse
structure['orientationResponse'] = orientationResponse
structure['pasResponse'] = pasResponse
structure['staircaseTrials'] = data.StairHandler(**staircase)
structure['data'].addLoop(structure['staircaseTrials'])
return structure
opacity=1,
depth=0.0)
RunningClock = core.Clock()
Nloads = GridCount**2
NumberOfReversals = 20
#staircase = data.StairHandler(startVal = 1,
# stepType = 'lin', stepSizes=1,
# nUp=1, nDown=3, # will home in on the 80% threshold
# nReversals = NumberOfReversals,minVal = 1,maxVal = 20)
staircase = data.StairHandler(
startVal=Nloads,
stepType='lin',
stepSizes=[1],
nUp=1,
nDown=3, # will home in on the 80% threshold
nReversals=NumberOfReversals,
minVal=1,
maxVal=Nloads)
# For each block change the selection list
# Need instructions and wait
textInstr1.setAutoDraw(True)
# Put the probe dot on the screen
win.flip()
# Start the probe timer
WaitingFlag = True
while WaitingFlag is True:
theseKeys = event.getKeys(keyList=['escape', '5'])
sound_1 = sound.Sound(u'NumberSounds/6.wav', secs=-1)
sound_1.setVolume(1)
# Create some handy timers
globalClock = core.Clock() # to track the time since experiment started
routineTimer = core.CountdownTimer(
) # to track time remaining of each (non-slip) routine
# --------Prepare to start Staircase "Stairs" --------
# set up handler to look after next chosen value etc
Stairs = data.StairHandler(startVal=3,
extraInfo=expInfo,
stepSizes=-1,
stepType='lin',
nReversals=0,
nTrials=14,
nUp=2,
nDown=1,
minVal=3,
maxVal=20,
originPath=-1,
name='Stairs')
thisExp.addLoop(Stairs) # add the loop to the experiment
level = thisStair = 3 # initialise some vals
for thisStair in Stairs:
currentLoop = Stairs
level = thisStair
# ------Prepare to start Routine "trial"-------
t = 0
trialClock.reset() # clock
#pause until there's a keypress
event.waitKeys()
for trialLoop in range(5):
formatString = 'Trial %i of 5.' % trialLoop
messagetrial = visual.TextStim(win, pos=[0, +vOffset], text=formatString)
messagetrial.draw()
win.flip()
event.waitKeys()
staircase = data.StairHandler(
startVal=0.5,
# Array as list alters the size of steps - do we want this?
nReversals=4,
stepType='lin',
stepSizes=[0.04, 0.02, 0.01, 0.005],
minVal=0,
maxVal=1,
nUp=1,
nDown=3, # will home in on the 80% threshold
nTrials=10)
for thisIncrement in staircase: # will continue the staircase until it terminates!
# set location of stimuli
targetSide = random.choice([-1,
1]) # will be either +1(right) or -1(left)
maskerTL.setPos([hOffset * targetSide, vOffset])
maskerTL.setContrast(0.5)
maskerTR.setPos([-hOffset * targetSide, vOffset])
maskerTR.setContrast(0.5)
maskerBL.setPos([hOffset * targetSide, -vOffset])
def run_exp():
""" Runs psychophysics experiment to determine threshold for distortion for ensemble
and individual mode.
After starting, you will be prompted for subject name and experiment type
for experiment type put either "ensemble" or "single"
"""
DIR_DATA = '../data'
save_dir = op.join(DIR_DATA, 'perceptual_experiment')
# create folder for psychophysics data if not there already
safe_mkdir(save_dir)
# params
numTrials = 60
alphaMin = 0
alphaMax = 60
alphaStart = 40
alphaSteps = [10, 5, 5, 2, 2]
images = ['church', 'dog', 'fish', 'horn', 'truck']
# set file name
info = {'Subject': 'ld', 'Experiment Type': 'ensemble'}
info['dateStr'] = data.getDateStr() # add the current time
# present a dialogue to change params
dlg = gui.DlgFromDict(info, title='Percpetual Exp', fixed=['dateStr'])
if dlg.OK:
toFile(op.join(save_dir, 'lastParams.pickle'), info) # save params to file for next time
else:
core.quit() # the user hit cancel so exit
# make a text file to save data
fileName = save_dir + '/Experiment_' + info['Experiment Type'] + '_' + info['Subject'] + '_' + info['dateStr']
dataFile = open(fileName + '.csv', 'w') # a simple text file with 'comma-separated-values'
dataFile.write('distortedSide, trialNum,image, alpha, correct, experimentType\n')
# create a window
win = visual.Window([1000, 600], monitor="testMonitor", units="deg")
# create some stimuli
dist_ind, dist_ensemble = create_distortions()
preprocessed_images = load_images()
fixation = visual.GratingStim(win=win, size=0.5, pos=[0, 0], sf=0, color=-1)
# display instructions
message1 = visual.TextStim(win, pos=[0, +3], text='Hit a key when ready.')
message2 = visual.TextStim(win, pos=[0, -3],
text="Then press left or right to indicate which image was more distorted.")
message3 = visual.TextStim(win, pos=[0, +3], text="press left or right")
message1.draw()
message2.draw()
fixation.draw()
win.flip()
event.waitKeys()
# setup stair procedure
stairs = []
info['baseImages'] = images
for imgName in info['baseImages']:
thisInfo = copy.copy(info)
thisInfo['imgName'] = imgName
thisStair = data.StairHandler(startVal=alphaStart,
extraInfo=thisInfo,
nTrials=100, nUp=1, nDown=2, nReversals=5,
minVal=alphaMin, maxVal=alphaMax,
stepSizes=alphaSteps)
stairs.append(thisStair)
for trial in np.arange(numTrials):
# shuffle stairs
shuffle(stairs)
# print('Trial Num:', trial)
for thisStair in stairs:
thisAlpha = next(thisStair) # get the alpha value for this trial
thisImage = thisStair.extraInfo['imgName'] # which image are we on
dist_ind, dist_ensemble = create_distortions()
preprocessed_images = load_images()
if info['Experiment Type'] == 'ensemble':
base_image, distorted_image = random_trial(preprocessed_images, dist_ind, dist_ensemble,
alpha=thisAlpha, img=thisImage, ensemble=1)
if info['Experiment Type'] == 'single':
base_image, distorted_image = random_trial(preprocessed_images, dist_ind, dist_ensemble,
alpha=thisAlpha, img=thisImage)
distortedImg = visual.ImageStim(win=win, image=distorted_image, units='pix', size=260, ori=180)
baseImg = visual.ImageStim(win=win, image=base_image, units='pix', size=260, ori=180)
# randomly assign side on screen to images
targetSide = np.random.choice([-1, 1])
distortedImg.setPos([250 * targetSide, 0])
baseImg.setPos([-250 * targetSide, 0])
# randomize which image is presented first
order = np.random.choice([-1, 1])
# Trial
if order == 1:
# draw first stimulus
fixation.draw()
distortedImg.draw()
win.flip()
# wait 1s
core.wait(1.0)
# draw second stimulus
fixation.draw()
baseImg.draw()
win.flip()
else:
# draw first stimulus
fixation.draw()
baseImg.draw()
win.flip()
# wait 1s
core.wait(1.0)
# draw second stimulus
fixation.draw()
distortedImg.draw()
win.flip()
# wait 1s
core.wait(1.0)
# blank screen
message3.draw()
fixation.draw()
win.flip()
# get response
thisResp = None
while thisResp == None:
allKeys = event.waitKeys()
for thisKey in allKeys:
if thisKey == 'left':
if targetSide == -1:
thisResp = 1 # correct
else:
thisResp = -1 # incorrect
elif thisKey == 'right':
if targetSide == 1:
thisResp = 1 # correct
else:
thisResp = -1 # incorrect
elif thisKey in ['q', 'escape']:
core.quit() # abort experiment
event.clearEvents() # clear other (eg mouse) events - they clog the buffer
# adjust stairs
thisStair.addData(thisResp)
# save responses
to_write = f"{targetSide:d}, {trial:d}, {thisImage:s}, {thisAlpha:.3f}, {thisResp:d}," \
f" {info['Experiment Type']} \n"
dataFile.write(to_write)
core.wait(0.5)
# close file
dataFile.close()
win.clearBuffer() # make screen black
endText = visual.TextStim(win, pos=[0, +3], text='Thanks! You have finished the experiment.')
endText.draw()
win.flip()
win.close()
core.quit()
return
stimFrames.append(
visual.PatchStim(myWin,
texRes=pixels,
mask='circle',
size=pixels * 2,
sf=1.0 / pixels,
ori=90,
tex=(noiseMatrix * info['contrastModNoise'] *
lumGratings[3])))
stairCases = []
#two staircases - one from the top, one from below - to average
stairCases.append(
data.StairHandler(startVal=info['highGamma'],
nTrials=info['nTrials'],
stepSizes=[0.5, 0.5, 0.1, 0.1, 0.1, 0.1, 0.05, 0.05],
stepType='lin',
nUp=1,
nDown=1))
stairCases.append(
data.StairHandler(startVal=info['lowGamma'],
nTrials=info['nTrials'],
stepSizes=[0.5, 0.5, 0.1, 0.1, 0.1, 0.1, 0.05, 0.05],
stepType='lin',
nUp=1,
nDown=1))
def getResponse(direction):
"""if subject said up when direction was up (+1) then increase gamma
Otherwise, decrease gamma"""
event.clearEvents() #clear the event buffer to start with
def test_json_dump_to_file(self):
s = data.StairHandler(5)
s.saveAsJson(fileName=self.tmp_dir, fileCollisionMethod='overwrite')
def test_comparison_not_equal_after_iteration(self):
s1 = data.StairHandler(5)
s2 = data.StairHandler(6)
s1.__next__()
s2.__next__()
assert s1 != s2
def test_comparison_equals(self):
s1 = data.StairHandler(5)
s2 = data.StairHandler(5)
assert s1 == s2
expInfo['dateStr'] = data.getDateStr() # add the current time
# present a dialogue to change params
dlg = gui.DlgFromDict(expInfo, title='simple JND Exp', fixed=['dateStr'])
if dlg.OK:
toFile('lastParams.pickle', expInfo) # save params to file for next time
else:
core.quit() # the user hit cancel so exit
# make a text file to save data
fileName = expInfo['observer'] + expInfo['dateStr']
dataFile = open(fileName+'.csv', 'w') # a simple text file with 'comma-separated-values'
dataFile.write('targetSide,oriIncrement,correct\n')
# create the staircase handler
staircase = data.StairHandler(startVal = 20.0,
stepType = 'db', stepSizes=[8,4,4,2],
nUp=1, nDown=3, # will home in on the 80% threshold
nTrials=1)
# create window and stimuli
win = visual.Window([800,600],allowGUI=True,
monitor='testMonitor', units='deg')
foil = visual.GratingStim(win, sf=1, size=4, mask='gauss',
ori=expInfo['refOrientation'])
target = visual.GratingStim(win, sf=1, size=4, mask='gauss',
ori=expInfo['refOrientation'])
fixation = visual.GratingStim(win, color=-1, colorSpace='rgb',
tex=None, mask='circle', size=0.2)
# and some handy clocks to keep track of time
globalClock = core.Clock()
trialClock = core.Clock()
lumGratings.append(filters.makeGrating(pixels, 0, cyclesSpace, phase=180))
stimFrames.append(visual.PatchStim(myWin, texRes=pixels, mask='circle',
size=pixels*2, sf=1.0/pixels, ori=90,
tex= (noiseMatrix*info['lumModNoise'] + lumGratings[2]*info['lumModLum'])
))
lumGratings.append(filters.makeGrating(pixels, 0, cyclesSpace, phase=270)/2.0 + 0.5)
stimFrames.append(visual.PatchStim(myWin, texRes=pixels, mask='circle',
size=pixels*2, sf=1.0/pixels, ori=90,
tex= (noiseMatrix*info['contrastModNoise']*lumGratings[3])
))
stairCases=[]
#two staircases - one from the top, one from below - to average
stairCases.append(data.StairHandler(startVal=info['startGamma'][0], nTrials=info['nTrials'],
stepSizes=[0.5,0.5,0.1,0.1,0.1,0.1,0.05,0.05],stepType='lin',
nUp=1, nDown=1))
stairCases.append(data.StairHandler(startVal=info['startGamma'][1], nTrials=info['nTrials'],
stepSizes=[0.5,0.5,0.1,0.1,0.1,0.1,0.05,0.05],stepType='lin',
nUp=1, nDown=1))
def getResponse(direction):
"""if subject said up when direction was up (+1) then increase gamma
Otherwise, decrease gamma"""
event.clearEvents()#clear the event buffer to start with
resp=None#initially
while 1:#forever until we return
for key in event.getKeys():
#quit
if key in ['escape', 'q']:
myWin.close()
def expcolornoise(noise_condition,
theta,
subject='None',
c=0.12,
sscale=2.6,
dlum=0):
# set two reference
left = theta + 20
right = theta - 20
leftRef = visual.Circle(win=win,
units='deg',
fillColorSpace='rgb255',
lineColorSpace='rgb255',
pos=[-8, 2])
leftRef.fillColor = colorpalette.newcolor(left,
c,
sscale,
dlum,
unit='degree',
subject=subject)[1]
leftRef.lineColor = leftRef.fillColor
rightRef = visual.Circle(win=win,
units='deg',
fillColorSpace='rgb255',
lineColorSpace='rgb255',
pos=[8, 2])
rightRef.fillColor = colorpalette.newcolor(right,
c,
sscale,
dlum,
unit='degree',
subject=subject)[1]
rightRef.lineColor = rightRef.fillColor
# set position and color of stimuli
sPatch = patchstim()
tPatch = patchstim()
sPatch.xys = patchpos([-1, 1], [1, 3])
tPatch.xys = patchpos([-1, 1], [-3, -1])
# create staircases
info = {
'startVal': [-3],
'steps': [[2, 1], [1, 2]]
} # set two stairs here, with different startpoints;
# later maybe make it as diffferent size?
stairs = []
for startVal in info['startVal']:
thisInfo = copy.copy(info)
thisInfo['startVal'] = startVal
for steps in info['steps']:
thisInfo['steps'] = steps
thisStair = data.StairHandler(startVal=startVal,
extraInfo=thisInfo,
nTrials=ntrial,
stepSizes=0.5,
nUp=steps[0],
nDown=steps[1],
minVal=-5,
maxVal=5)
stairs.append(thisStair)
track = np.empty((0, 6))
for trialN in range(ntrial):
random.shuffle(
stairs
) # this shuffles 'in place' (ie stairs itself is changed, nothing returned)
for thisStair in stairs:
standard = theta # standard should be fixed
# rotation = next(thisStair) # what is rotation = 0? skip this trial?
rotation = thisStair
test = standard + rotation
# choose noise condition
if noise_condition == 'L-L': # low - low noise
sPatch.colors = colorpalette.newcolor(standard,
c,
sscale,
dlum,
unit='degree',
subject=subject)[1]
tPatch.colors = colorpalette.newcolor(test,
c,
sscale,
dlum,
unit='degree',
subject=subject)[1]
elif noise_condition == 'L-H': # low - high noise: only compare stimulus has high noise
sPatch.colors = colorpalette.newcolor(standard,
c,
sscale,
dlum,
unit='degree',
subject=subject)[1]
tPatch.colors = randcolor(test,
sigma,
npatch,
c,
sscale,
dlum,
unit='degree',
subject=subject)[1]
elif noise_condition == 'H-H': # high - high noise
sPatch.colors = randcolor(standard,
sigma,
npatch,
c,
sscale,
dlum,
unit='degree',
subject=subject)[1]
tPatch.colors = randcolor(test,
sigma,
npatch,
c,
sscale,
dlum,
unit='degree',
subject=subject)[1]
else:
print("No noise condition corresponds to the input!")
core.quit()
# draw all stimuli
leftRef.draw()
rightRef.draw()
sPatch.draw()
tPatch.draw()
win.flip()
core.wait(1) # foe how long the stimuli will show
win.flip()
# get response
judge = None
while judge is None:
allkeys = event.waitKeys()
for key in allkeys: # press left -> adjust comparision stim counter-clockwise to standard stim; press right -> clockwisely
if (key == 'left' and rotation > 0) or (key == 'right'
and rotation < 0):
judge = 1 # correct
elif (key == 'left'
and rotation < 0) or (key == 'right'
and rotation > 0):
judge = 0 # incorrect
elif key == 'escape':
core.quit()
thisStair.addResponse(judge)
thisStair.saveAsExcel(path + '/stair' + str(trialN))
track = np.append(track,
[[left, right, standard, test, rotation, judge]],
axis=0)
win.close()
core.quit()
savedata(noise_condition, track)
return track
win=visual.Window([400,400])
#---------------------
#create the stimuli
#---------------------
#create staircases
stairs=[]
for thisStart in info['startPoints']:
#we need a COPY of the info for each staircase
#(or the changes here will be made to all the other staircases)
thisInfo = copy.copy(info)
#now add any specific info for this staircase
thisInfo['thisStart']=thisStart #we might want to keep track of this
thisStair = data.StairHandler(startVal=thisStart,
extraInfo=thisInfo,
nTrials=50, nUp=1, nDown=3,
minVal = 0.5, maxVal=8,
stepSizes=[4,4,2,2,1,1])
stairs.append(thisStair)
for trialN in range(info['nTrials']):
shuffle(stairs) #this shuffles 'in place' (ie stairs itself is changed, nothing returned)
#then loop through our randomised order of staircases for this repeat
for thisStair in stairs:
thisIntensity = next(thisStair)
print('start=%.2f, current=%.4f' %(thisStair.extraInfo['thisStart'], thisIntensity))
#---------------------
#run your trial and get an input
#---------------------
keys = event.waitKeys() #(we can simulate by pushing left for 'correct')
text = visual.TextStim(win=win, name='text',
text="Bat: press 'a'\n\nBet: press 'e'",
font='Arial',
pos=(0, 0), height=0.1, wrapWidth=None, ori=0,
color='white', colorSpace='rgb', opacity=1,
depth=-3.0);
# Create some handy timers
globalClock = core.Clock() # to track the time since experiment started
routineTimer = core.CountdownTimer() # to track time remaining of each (non-slip) routine
# --------Prepare to start Staircase "trials" --------
# set up handler to look after next chosen value etc
trials = data.StairHandler(startVal=10, extraInfo=expInfo,
stepSizes=[2], stepType='lin',
nReversals=1, nTrials=50,
nUp=1, nDown=3,
minVal=-50, maxVal=50,
originPath=-1, name='trials')
thisExp.addLoop(trials) # add the loop to the experiment
level = thisTrial = 10 # initialise some vals
for thisTrial in trials:
currentLoop = trials
level = thisTrial
# ------Prepare to start Routine "trial"-------
t = 0
trialClock.reset() # clock
frameN = -1
continueRoutine = True
# update component parameters for each repeat
def test_json_dump_to_file(self):
s = data.StairHandler(5)
_, path = mkstemp(dir=self.tmp_dir, suffix='.json')
s.saveAsJson(fileName=path, fileCollisionMethod='overwrite')
info['participant'] = ''
dlg = gui.DlgFromDict(info) # present dialog to collect info
if not dlg.OK:
core.quit()
info['dateStr'] = data.getDateStr() #will create str of current date/time
info['refDisp'] = 0.16 # disparity of reference stays constant at 0.16 deg
#create the base filename for our data files
#fileName = "data/{participant}_{dateStr}".format(**info)
#dataFile = open(fileName+'.csv', 'w')#a simple text file with 'comma-separated-values'
#create the staircase handler
staircase = data.StairHandler(
startVal=0.3,
stepType='lin',
stepSizes=[0.05, 0.03, 0.03, 0.02, 0.02, 0.01, 0.01],
nUp=1,
nDown=1,
minVal=0,
maxVal=0.3) #will home in on the 50% threshold
# initialise stimuli
fixation = visual.Circle(win,
size=0.25,
lineColor='white',
fillColor='lightGrey')
rds = visual.DotStim(win,
nDots=500,
fieldSize=(4, 4),
fieldShape='sqr',
dotLife=-1,
depth=-4.0,
interpolate=True)
# Create some handy timers
globalClock = core.Clock() # to track the time since experiment started
routineTimer = core.CountdownTimer(
) # to track time remaining of each (non-slip) routine
# --------Prepare to start Staircase "trials" --------
# set up handler to look after next chosen value etc
trials = data.StairHandler(startVal=0.5,
extraInfo=expInfo,
stepSizes=[0.4, 0.2, 0.2, 0.1],
stepType='log',
nReversals=0,
nTrials=50,
nUp=1,
nDown=3,
minVal=0,
maxVal=1,
originPath=-1,
name='trials')
thisExp.addLoop(trials) # add the loop to the experiment
level = thisTrial = 0.5 # initialise some vals
for thisTrial in trials:
currentLoop = trials
level = thisTrial
# ------Prepare to start Routine "trial"-------
t = 0
trialClock.reset() # clock
def test_comparison_not_equal(self):
s1 = data.StairHandler(5)
s2 = data.StairHandler(6)
assert s1 != s2
# Setting up the conditions:
condList = data.importConditions(conditionsFilePath)
stairs, completedStairs = [], []
for thisCond in condList:
thisInfo = copy.copy(thisCond)
stairLabel = 'st' + str(thisCond['startContr']) + \
'_mcBv' + str(thisCond['mcBv']) + \
'_targTon' + str(thisCond['targTon']) + \
'_ecc' + str(thisCond['targXoff2'])
if domTest: stairLabel += '_targEyeR' + str(thisCond['targEyeR'])
thisInfo['label'] = stairLabel
thisStair = data.StairHandler(startVal=thisInfo['startContr'],
extraInfo=thisInfo,
maxVal=1,
minVal=-2,
nReversals=thisInfo['nRevs'],
nUp=1,
nDown=1,
stepType='lin',
stepSizes=contrSteps[0:thisInfo['nRevs']],
name=stairLabel)
stairs.append(thisStair)
# An empty data set for storing behavioural responses:
behResp = []
# Creating a copy of the Conditions file for book-keeping and analyses:
if not os.path.exists(filePath):
os.makedirs(filePath)
shutil.copyfile(conditionsFilePath,
filePath + os.sep + os.path.basename(conditionsFilePath))
dataFileName = filePath + os.sep + fileName + '.csv'
def test_json_dump(self):
s = data.StairHandler(5)
dump = s.saveAsJson()
s.origin = ''
assert s == json_tricks.np.loads(dump)
#extraInfo = thisInfo,
pThreshold = threshCriterion, #0.25,
gamma = 1./26,
delta=0.02, #lapse rate, I suppose for Weibull function fit
method = 'quantile', #uses the median of the posterior as the final answer
stepType = 'log', #will home in on the 80% threshold. But stepType = 'log' doesn't usually work
minVal=1, maxVal = 100
)
print('created QUEST staircase')
else:
stepSizesLinear = [.2,.2,.1,.1,.05,.05]
stepSizesLog = [log(1.4,10),log(1.4,10),log(1.3,10),log(1.3,10),log(1.2,10)]
staircase = data.StairHandler(startVal = 0.1,
stepType = 'log', #if log, what do I want to multiply it by
stepSizes = stepSizesLog, #step size to use after each reversal
minVal=0, maxVal=1,
nUp=1, nDown=3, #will home in on the 80% threshold
nReversals = 2, #The staircase terminates when nTrials have been exceeded, or when both nReversals and nTrials have been exceeded
nTrials=1)
print('created conventional staircase')
if prefaceStaircaseTrialsN > len(prefaceStaircaseNoise): #repeat array to accommodate desired number of easyStarterTrials
prefaceStaircaseNoise = np.tile( prefaceStaircaseNoise, ceil( prefaceStaircaseTrialsN/len(prefaceStaircaseNoise) ) )
prefaceStaircaseNoise = prefaceStaircaseNoise[0:prefaceStaircaseTrialsN]
phasesMsg = ('Doing '+str(prefaceStaircaseTrialsN)+'trials with noisePercent= '+str(prefaceStaircaseNoise)+' then doing a max '+str(staircaseTrials)+'-trial staircase')
print(phasesMsg); logging.info(phasesMsg)
#staircaseStarterNoise PHASE OF EXPERIMENT
corrEachTrial = list() #only needed for easyStaircaseStarterNoise
staircaseTrialN = -1; mainStaircaseGoing = False
tex=None,
mask='circle',
size=0.2)
message1 = visual.TextStim(win, pos=[0, +3], text='Hit a key when ready.')
message2 = visual.TextStim(
win,
pos=[0, -3],
text="Then press left or right to identify the %.1fdegree probe." %
expInfo['refOrientation'])
# create the staircase handler
staircase = data.StairHandler(
startVal=20.0,
stepType='lin',
stepSizes=[8, 4, 4, 2, 2, 1, 1], # reduce step size every two reversals
minVal=0,
maxVal=90,
nUp=1,
nDown=3, # will home in on the 80% threshold
nTrials=50)
# display instructions and wait
message1.draw()
message2.draw()
fixation.draw()
win.flip()
# check for a keypress
event.waitKeys()
for thisIncrement in staircase: # will step through the staircase
# set location of stimuli
for trial in training:
training.addData('training.rt', random.random() * 0.5 + 0.5)
if random.random() > 0.5:
training.addData('training.key', 'left')
else:
training.addData('training.key', 'right')
exp.nextEntry()
# then run 3 repeats of a staircase
outerLoop = data.TrialHandler(trialList=[],
nReps=3,
name='stairBlock',
method='random')
exp.addLoop(outerLoop)
for thisRep in outerLoop: # the outer loop doesn't save any data
staircase = data.StairHandler(startVal=10, name='staircase', nTrials=5)
exp.addLoop(staircase)
for thisTrial in staircase:
id = random.random()
if random.random() > 0.5:
staircase.addData(1)
else:
staircase.addData(0)
exp.addData('id', id)
exp.nextEntry()
for e in exp.entries:
print(e)
print(
"Done. 'exp' experimentHandler will now (end of script) save data to testExp.csv"
)
print(" and also to testExp.psydat, which is a pickled version of `exp`")
if continueRoutine: # don't flip if this routine is over or we'll get a blank screen
win.flip()
# -------Ending Routine "instructs"-------
for thisComponent in instructsComponents:
if hasattr(thisComponent, "setAutoDraw"):
thisComponent.setAutoDraw(False)
# the Routine "instructs" was not non-slip safe, so reset the non-slip timer
routineTimer.reset()
# --------Prepare to start Staircase "Stair" --------
# set up handler to look after next chosen value etc
Stair = data.StairHandler(startVal=81, extraInfo=expInfo,
stepSizes=[1], stepType='lin',
nReversals=1, nTrials=1,
nUp=1, nDown=1,
minVal=65, maxVal=160,
originPath=-1, name='Stair')
thisExp.addLoop(Stair) # add the loop to the experiment
level = thisStair = 81 # initialise some vals
for thisStair in Stair:
currentLoop = Stair
level = thisStair
# ------Prepare to start Routine "Endogenous"-------
t = 0
EndogenousClock.reset() # clock
frameN = -1
continueRoutine = True
# update component parameters for each repeat
def task(sdist):
# Open logfile
log = logfiler.logger(expinfo['Subject ID'], 'jnd_distspace')
# Set-up staircase
staircase = data.StairHandler(startVal=10,
stepType='lin',
stepSizes=[5, 5, 5, 5, 2, 2, 1, 1],
minVal=0,
maxVal=60,
nUp=1,
nDown=3,
nTrials=75)
# Iterate through steps
for step in staircase:
# Set location
tside = np.random.choice([sdist * -1, sdist])
target.setPos([tside, 0.0])
distractor.setPos([tside * -1, 0.0])
# Set distractor color
print(step)
dcol = int(expinfo['Target Color']) + step
distractor.setFillColor(allcols[dcol])
distractor.setLineColor(allcols[dcol])
# Draw and show
target.draw()
distractor.draw()
win.flip()
core.wait(.15)
win.flip()
# Response handling
resp = event.waitKeys(keyList=['left', 'right', 'escape'])
cor = None
if (resp[0] == 'left' and tside == (sdist*-1)) \
or (resp[0] == 'right' and tside == sdist):
cor = 1
corsound.play()
else:
cor = 0
errsound.play()
# Do we quit?
if resp[0] == 'escape':
log.close()
tracker.endExperiment('C:\\edfs\\Nick\\distspace\\')
core.quit()
# Adjust next trial, save results
staircase.addResponse(cor)
trial = {
'sub': expinfo['Subject ID'],
'group': expinfo['Group'],
'tcol': expinfo['Target Color'],
'dcol': dcol,
'ddist': step,
'tside': tside,
'resp': resp[0],
'cor': cor
}
log.write(trial)
# ISI
core.wait(1)
# Clean up
log.close()
staircase.saveAsPickle('{}_jnd'.format(expinfo['Subject ID']))