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speech_categorization.py
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speech_categorization.py
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"""
Speech sounds categorization task.
"""
import time
import os
import glob
import numpy as np
from qtpy import QtWidgets
from taskontrol import rigsettings
from taskontrol import dispatcher
from taskontrol import statematrix
from taskontrol import savedata
from taskontrol import paramgui
from taskontrol import utils
from taskontrol.plugins import templates
from taskontrol.plugins import performancedynamicsplot
from taskontrol.plugins import soundclient
from taskontrol.plugins import speakercalibration
LONGTIME = 100
SOUND_DIR = rigsettings.SPEECH_SOUNDS_PATH
SOUND_FILENAME_FORMAT = 'syllable_{0}x_vot{1:03.0f}_ft{2:03.0f}.wav' # From speechsynth.py
FREQFACTOR_PATTERN = r'_(\d{1})x_'
VOT_PATTERN = r'_vot(\d{3})_'
FT_PATTERN = r'_ft(\d{3}).'
if 'outBit1' in rigsettings.OUTPUTS:
trialStartSync = ['outBit1'] # Sync signal for trial-start.
else:
trialStartSync = []
if 'outBit0' in rigsettings.OUTPUTS:
stimSync = ['outBit0'] # Sync signal for sound stimulus
else:
stimSync = []
class Paradigm(templates.Paradigm2AFC):
def __init__(self,parent=None, paramfile=None, paramdictname=None):
super(Paradigm, self).__init__(parent)
self.name = '2afc_speech'
self.soundFiles = []
# FIXME: targetSoundID does not seem necessary
self.targetSoundID = {} # Keys are filenames, items are integers to be used as soundID
self.freqFactor = 0
self.possibleVOT = 0
self.possibleFT = 0
# -- Performance dynamics plot --
performancedynamicsplot.set_pg_colors(self)
self.myPerformancePlot = performancedynamicsplot.PerformanceDynamicsPlot(nTrials=400,winsize=10)
# -- Add soundsFolder parameter to Session info --
self.params['soundsFolder'] = paramgui.StringParam('Sounds folder', value=SOUND_DIR,
enabled=False, group='Session info')
self.sessionInfo = self.params.layout_group('Session info')
self.get_sound_files() # Defines self.soundFiles, self.possibleVOT and self.possibleFT
# -- Add parameters --
self.params['timeWaterValveL'] = paramgui.NumericParam('Time valve left',value=0.03,
units='s',group='Water delivery')
self.params['timeWaterValveC'] = paramgui.NumericParam('Time valve center',value=0.03,
units='s',group='Water delivery')
self.params['timeWaterValveR'] = paramgui.NumericParam('Time valve right',value=0.03,
units='s',group='Water delivery')
waterDelivery = self.params.layout_group('Water delivery')
self.params['outcomeMode'] = paramgui.MenuParam('Outcome mode',
['sides_direct', 'direct', 'on_next_correct',
'only_if_correct', 'on_any_poke',
'passive_exposure'],
value=3,group='Choice parameters')
self.params['allowEarlyWithdrawal'] = paramgui.MenuParam('Allow early withdraw',
['off','on'], enabled=False,
value=1, group='Choice parameters')
self.params['antibiasMode'] = paramgui.MenuParam('Anti-bias mode',
['off','repeat_mistake'],
value=0,group='Choice parameters')
choiceParams = self.params.layout_group('Choice parameters')
self.params['delayToTargetMean'] = paramgui.NumericParam('Mean delay to target',value=0.3,
units='s',group='Timing parameters')
self.params['delayToTargetHalfRange'] = paramgui.NumericParam('+/-',value=0.05,
units='s',group='Timing parameters')
self.params['delayToTarget'] = paramgui.NumericParam('Delay to target',value=0.3,
units='s',group='Timing parameters',
enabled=False,decimals=3)
self.params['targetDuration'] = paramgui.NumericParam('Target duration',value=0,
decimals=3, enabled=False,
units='s',group='Timing parameters')
self.params['rewardAvailability'] = paramgui.NumericParam('Reward availability',value=4,
units='s',group='Timing parameters')
self.params['punishTimeError'] = paramgui.NumericParam('Punishment (error)',value=0,
units='s',group='Timing parameters')
self.params['punishTimeEarly'] = paramgui.NumericParam('Punishment (early)',value=0,
units='s',group='Timing parameters')
self.params['syncLight'] = paramgui.MenuParam('Sync light',
['off', 'leftLED', 'centerLED', 'rightLED'],
value=0, group='Timing parameters')
self.params['delayToSyncLight'] = paramgui.NumericParam('Delay to sync light',value=0,
units='s',group='Timing parameters')
self.params['syncLightDuration'] = paramgui.NumericParam('Sync light duration',value=0,
units='s',group='Timing parameters')
timingParams = self.params.layout_group('Timing parameters')
'''
self.params['trialsPerBlock'] = paramgui.NumericParam('Trials per block',value=300,
units='trials (0=no-switch)',
group='Switching parameters')
self.params['currentBlock'] = paramgui.MenuParam('Current block',
['mid_boundary','low_boundary','high_boundary'],
value=0,group='Switching parameters')
switchingParams = self.params.layout_group('Switching parameters')
'''
self.params['psycurveMode'] = paramgui.MenuParam('PsyCurve Mode',
['off','uniform','extreme80pc'],
value=0,group='Psychometric parameters')
self.params['psycurveNsteps'] = paramgui.MenuParam('PsyCurve N steps', ['4','6'],
value=0,group='Psychometric parameters')
psychometricParams = self.params.layout_group('Psychometric parameters')
self.params['relevantFeature'] = paramgui.MenuParam('Relevant feature',
['spectral', 'temporal', 'none'],
value=0,group='Categorization parameters')
self.params['irrelevantFeatureMode'] = paramgui.MenuParam('Irrelevant feature mode',
['fix_to_min', 'fix_to_max',
'random', 'matrix_border'],
value=0,group='Categorization parameters')
self.params['soundActionMode'] = paramgui.MenuParam('Sound-action mode',
['low_left','high_left'],
value=0,group='Categorization parameters')
categorizationParams = self.params.layout_group('Categorization parameters')
self.params['automationMode'] = paramgui.MenuParam('Automation Mode',
['off','increase_delay'],
value=0,group='Automation')
automationParams = self.params.layout_group('Automation')
# -- In this version the laser is set to last as long as the target --
self.params['laserMode'] = paramgui.MenuParam('Laser mode',
['none','bilateral'],
value=0, group='Photostimulation parameters')
self.params['laserTrial'] = paramgui.MenuParam('Laser trial', ['no','yes'],
value=0, enabled=False,
group='Photostimulation parameters')
self.params['laserOnset'] = paramgui.NumericParam('Laser onset (from sound)',value=0.0,
enabled=False,
units='s',group='Photostimulation parameters')
self.params['laserDuration'] = paramgui.NumericParam('Laser duration',value=0.4, enabled=True,
units='s',group='Photostimulation parameters')
# -- Percent trials with laser. Remaining trials will be no laser.
self.params['fractionLaserTrials'] = paramgui.NumericParam('Fraction trials with laser',value=0.25,
units='',group='Photostimulation parameters')
photostimParams = self.params.layout_group('Photostimulation parameters')
self.params['targetVOTpercent'] = paramgui.NumericParam('Target VOT percent', value=0, decimals=0,
units='percentage', enabled=False,
group='Sound parameters')
self.params['targetFTpercent'] = paramgui.NumericParam('Target FT percent', value=0, decimals=0,
units='percentage', enabled=False,
group='Sound parameters')
self.params['targetIntensityMode'] = paramgui.MenuParam('Intensity mode',
['fixed','randMinus20'],
value=0,group='Sound parameters')
# This intensity corresponds to the intensity of each component of the chord
self.params['targetMaxIntensity'] = paramgui.NumericParam('Max intensity',value=70,
units='dB-SPL',group='Sound parameters')
self.params['targetIntensity'] = paramgui.NumericParam('Intensity',value=0.0,units='dB-SPL',
enabled=False,group='Sound parameters')
self.params['targetAmplitude'] = paramgui.NumericParam('Target amplitude',value=0.0,units='[0-1]',
enabled=False,decimals=4,group='Sound parameters')
self.params['punishSoundIntensity'] = paramgui.NumericParam('Punish intensity',value=50,
units='dB-SPL',enabled=True,
group='Sound parameters')
self.params['punishSoundAmplitude'] = paramgui.NumericParam('Punish amplitude',value=0.01,
units='[0-1]',enabled=False, decimals=4,
group='Sound parameters')
self.params['soundLocation'] = paramgui.MenuParam('Sound location',
['binaural', 'left', 'right'],
value=0, group='Sound parameters')
soundParams = self.params.layout_group('Sound parameters')
self.params['nValid'] = paramgui.NumericParam('N valid',value=0,
units='',enabled=False,
group='Report')
self.params['nRewarded'] = paramgui.NumericParam('N rewarded',value=0,
units='',enabled=False,
group='Report')
reportParams = self.params.layout_group('Report')
#
self.params['experimenter'].set_value('santiago')
self.params['subject'].set_value('test')
# -- Add graphical widgets to main window --
self.centralWidget = QtWidgets.QWidget()
layoutMain = QtWidgets.QVBoxLayout()
layoutTop = QtWidgets.QVBoxLayout()
layoutBottom = QtWidgets.QHBoxLayout()
layoutCol1 = QtWidgets.QVBoxLayout()
layoutCol2 = QtWidgets.QVBoxLayout()
layoutCol3 = QtWidgets.QVBoxLayout()
layoutCol4 = QtWidgets.QVBoxLayout()
layoutMain.addLayout(layoutTop)
layoutMain.addSpacing(0)
layoutMain.addLayout(layoutBottom)
layoutTop.addWidget(self.mySidesPlot)
layoutTop.addWidget(self.myPerformancePlot)
layoutBottom.addLayout(layoutCol1)
layoutBottom.addLayout(layoutCol2)
layoutBottom.addLayout(layoutCol3)
layoutBottom.addLayout(layoutCol4)
layoutCol1.addWidget(self.saveData)
layoutCol1.addWidget(self.sessionInfo)
layoutCol1.addWidget(self.dispatcher.widget)
layoutCol2.addWidget(self.manualControl)
layoutCol2.addStretch()
layoutCol2.addWidget(waterDelivery)
layoutCol2.addStretch()
layoutCol2.addWidget(choiceParams)
layoutCol2.addStretch()
layoutCol2.addWidget(automationParams)
layoutCol2.addStretch()
layoutCol3.addWidget(timingParams)
layoutCol3.addStretch()
layoutCol3.addWidget(psychometricParams)
layoutCol3.addStretch()
layoutCol3.addWidget(categorizationParams)
layoutCol3.addStretch()
layoutCol4.addWidget(photostimParams)
layoutCol4.addStretch()
layoutCol4.addWidget(soundParams)
layoutCol4.addStretch()
layoutCol4.addWidget(reportParams)
layoutCol4.addStretch()
self.centralWidget.setLayout(layoutMain)
self.setCentralWidget(self.centralWidget)
# -- Add variables for storing results --
maxNtrials = 4000 # Preallocating space for each vector makes things easier
self.results = utils.EnumContainer()
self.results.labels['rewardSide'] = {'left':0,'right':1}
self.results['rewardSide'] = np.random.randint(2,size=maxNtrials)
self.results.labels['choice'] = {'left':0,'right':1,'none':2}
self.results['choice'] = np.empty(maxNtrials,dtype=int)
self.results.labels['outcome'] = {'correct':1,'error':0,'invalid':2,
'free':3,'nochoice':4,'aftererror':5,'aborted':6}
self.results['outcome'] = np.empty(maxNtrials,dtype=int)
# Saving outcome as bool creates an 'enum' vector, so I'm saving as 'int'
self.results['valid'] = np.zeros(maxNtrials,dtype='int8') # redundant but useful
self.results['timeTrialStart'] = np.empty(maxNtrials,dtype=float)
self.results['timeTarget'] = np.empty(maxNtrials,dtype=float)
self.results['timeCenterIn'] = np.empty(maxNtrials,dtype=float)
self.results['timeCenterOut'] = np.empty(maxNtrials,dtype=float)
self.results['timeSideIn'] = np.empty(maxNtrials,dtype=float)
# -- Load parameters from a file --
self.params.from_file(paramfile,paramdictname)
# -- Load speaker calibration --
self.spkCal = speakercalibration.Calibration(rigsettings.SPEAKER_CALIBRATION_CHORD)
self.spkNoiseCal = speakercalibration.NoiseCalibration(rigsettings.SPEAKER_CALIBRATION_NOISE)
try:
self.spkVowelCal = speakercalibration.VowelCalibration(rigsettings.SPEAKER_CALIBRATION_VOWEL)
self.VOWEL_CALIBRATION = True
except Exception as e:
print(e)
QtWidgets.QMessageBox.warning(self, "WARNING!",
"This rig has not been calibrated for speech sounds.")
self.VOWEL_CALIBRATION = False
# -- Connect to sound server and define sounds --
print('Conecting to soundserver (waiting for 200ms) ...')
time.sleep(0.2)
self.soundClient = soundclient.SoundClient()
self.soundClient.start()
# -- Prepare sounds --
self.punishSoundID = 100
#self.prepare_target_sound()
self.currentSoundID = None
# -- Specify state matrix with extratimer --
self.sm = statematrix.StateMatrix(inputs=rigsettings.INPUTS,
outputs=rigsettings.OUTPUTS,
readystate='readyForNextTrial',
extratimers=['laserTimer'])
def prepare_punish_sound(self):
punishSoundIntensity = self.params['punishSoundIntensity'].get_value()
punishSoundAmplitude = self.spkNoiseCal.find_amplitude(punishSoundIntensity).mean()
self.params['punishSoundAmplitude'].set_value(punishSoundAmplitude)
sNoise = {'type':'noise', 'duration':0.5, 'amplitude':punishSoundAmplitude}
self.soundClient.set_sound(self.punishSoundID,sNoise)
def get_sound_files(self):
import re
soundFolder = self.params['soundsFolder'].get_value()
self.soundFiles = glob.glob(os.path.join(soundFolder,'*.wav'))
nFiles = len(self.soundFiles)
eachVOT = np.empty(nFiles, dtype=int)
eachFT = np.empty(nFiles, dtype=int)
self.soundIDdict = {}
for indsf, oneFile in enumerate(self.soundFiles):
###filename = os.path.basename(oneFile)
self.soundIDdict[oneFile] = indsf+1
self.soundIDdict[indsf] = oneFile
eachVOT[indsf] = re.search(VOT_PATTERN, oneFile).group(1)
eachFT[indsf] = re.search(FT_PATTERN, oneFile).group(1)
self.possibleVOT = np.unique(eachVOT)
self.possibleFT = np.unique(eachFT)
self.freqFactor = re.search(FREQFACTOR_PATTERN, oneFile).group(1)
def prepare_target_sound(self, soundFilename):
soundLocation = self.params['soundLocation'].get_string()
if self.params['targetIntensityMode'].get_string() == 'randMinus20':
possibleIntensities = self.params['targetMaxIntensity'].get_value()+\
np.array([-20,-15,-10,-5,0])
targetIntensity = possibleIntensities[np.random.randint(len(possibleIntensities))]
else:
targetIntensity = self.params['targetMaxIntensity'].get_value()
self.params['targetIntensity'].set_value(targetIntensity)
if self.VOWEL_CALIBRATION:
targetAmp = self.spkVowelCal.find_amplitude(targetIntensity).mean()
else:
# FIXME: currently I am averaging calibration from both speakers (not good)
targetFrequency = 10000
targetAmp = self.spkCal.find_amplitude(targetFrequency,targetIntensity).mean()
self.params['targetAmplitude'].set_value(targetAmp)
if soundLocation == 'left':
soundDict = {'type':'fromfile', 'filename':soundFilename, 'amplitude':[targetAmp, 0]}
elif soundLocation == 'right':
soundDict = {'type':'fromfile', 'filename':soundFilename, 'amplitude':[0, targetAmp]}
else:
soundDict = {'type':'fromfile', 'filename':soundFilename, 'amplitude':targetAmp}
thisSound = self.soundClient.set_sound(1, soundDict)
self.params['targetDuration'].set_value(thisSound.get_duration())
def prepare_next_trial(self, nextTrial):
# TicTime = time.time() ### DEBUG
# -- Calculate results from last trial (update outcome, choice, etc) --
if nextTrial>0:
self.params.update_history(nextTrial-1)
self.calculate_results(nextTrial-1)
# -- Apply anti-bias --
if self.params['antibiasMode'].get_string()=='repeat_mistake':
if self.results['outcome'][nextTrial-1]==self.results.labels['outcome']['error']:
self.results['rewardSide'][nextTrial] = self.results['rewardSide'][nextTrial-1]
nValid = self.params['nValid'].get_value()
# === Prepare next trial ===
self.execute_automation(nextTrial)
nextCorrectChoice = self.results['rewardSide'][nextTrial]
# -- Prepare sound --
relevantFeature = self.params['relevantFeature'].get_string()
if relevantFeature == 'spectral':
targetPercentageParam = self.params['targetFTpercent']
irrelevantParam = self.params['targetVOTpercent']
elif relevantFeature == 'temporal':
targetPercentageParam = self.params['targetVOTpercent']
irrelevantParam = self.params['targetFTpercent']
elif relevantFeature == 'none':
self.params['irrelevantFeatureMode'].set_string('matrix_border')
targetPercentageParam = self.params['targetFTpercent']
irrelevantParam = self.params['targetVOTpercent']
else:
raise ValueError(f'Relevant feature "{relevantFeature}" not implemented')
psycurveMode = self.params['psycurveMode'].get_string()
psycurveNsteps = int(self.params['psycurveNsteps'].get_string())
if psycurveMode=='off':
if nextCorrectChoice==self.results.labels['rewardSide']['left']:
targetPercentage = 0
elif nextCorrectChoice==self.results.labels['rewardSide']['right']:
targetPercentage = 100
elif psycurveMode=='uniform':
randIndex = np.random.randint(psycurveNsteps//2)
possibleValues = np.round(np.linspace(0, 100, psycurveNsteps)).astype(int)
if nextCorrectChoice==self.results.labels['rewardSide']['left']:
targetPercentage = possibleValues[randIndex]
elif nextCorrectChoice==self.results.labels['rewardSide']['right']:
targetPercentage = possibleValues[randIndex+psycurveNsteps//2]
elif psycurveMode=='extreme80pc':
# -- It assumes 6 possible values. 80% trials on extremes, 20% on the rest --
randIndex = np.flatnonzero(np.random.multinomial(1,[0.8, 0.1, 0.1]))[0]
if nextCorrectChoice==self.results.labels['rewardSide']['left']:
targetPercentage = randIndex*20
elif nextCorrectChoice==self.results.labels['rewardSide']['right']:
targetPercentage = (5-randIndex)*20
targetPercentageParam.set_value(targetPercentage)
irrelevantFeatureMode = self.params['irrelevantFeatureMode'].get_string()
if irrelevantFeatureMode=='fix_to_min':
irrelevantParam.set_value(0)
elif irrelevantFeatureMode=='fix_to_max':
irrelevantParam.set_value(100)
elif irrelevantFeatureMode=='random':
if psycurveMode=='off':
psycurveNsteps = 2
possibleIrrelValues = np.round(np.linspace(0, 100, psycurveNsteps)).astype(int)
irrelevantFeaturePercent = np.random.choice(possibleIrrelValues, 1)[0]
irrelevantParam.set_value(irrelevantFeaturePercent)
elif irrelevantFeatureMode=='matrix_border':
# NOTE: this mode overwrites values for targetPercentage
self.params['relevantFeature'].set_string('none')
if psycurveMode=='off':
psycurveNsteps = 2
possibleValuesEither = np.round(np.linspace(0, 100, psycurveNsteps)).astype(int)
valsVOT, valsFT = np.meshgrid(possibleValuesEither, possibleValuesEither)
border = lambda arr: np.concatenate([arr[0,:-1], arr[:-1,-1],
arr[-1,::-1], arr[-2:0:-1,0]])
borderVOT = border(valsVOT)
borderFT = border(valsFT)
pairInd = np.random.randint(len(borderVOT))
self.params['targetVOTpercent'].set_value(borderVOT[pairInd])
self.params['targetFTpercent'].set_value(borderFT[pairInd])
VOTpc = self.params['targetVOTpercent'].get_value()
FTpc = self.params['targetFTpercent'].get_value()
filename = SOUND_FILENAME_FORMAT.format(self.freqFactor, VOTpc, FTpc)
soundFolder = self.params['soundsFolder'].get_value()
soundKey = os.path.join(soundFolder, filename)
self.currentSoundID = 1 #self.targetSoundID[soundKey]
# -- Check if it will be a laser trial --
if self.params['laserMode'].get_string()=='bilateral':
fractionLaserTrials = self.params['fractionLaserTrials'].get_value()
fractionEachType = [1-fractionLaserTrials,fractionLaserTrials]
trialTypeInd = np.random.choice([0,1], size=None, p=fractionEachType)
else:
trialTypeInd=0
self.params['laserTrial'].set_value(trialTypeInd)
self.prepare_target_sound(soundKey)
self.prepare_punish_sound()
# -- Prepare state matrix --
self.set_state_matrix(nextCorrectChoice)
self.dispatcher.ready_to_start_trial()
###print('Elapsed Time (preparing next trial): ' + str(time.time()-TicTime)) ### DEBUG
# -- Update sides plot --
self.mySidesPlot.update(self.results['rewardSide'],self.results['outcome'],nextTrial)
# -- Update performance plot --
self.myPerformancePlot.update(self.results['rewardSide'][:nextTrial],self.results.labels['rewardSide'],
self.results['outcome'][:nextTrial],self.results.labels['outcome'],
nextTrial)
def set_state_matrix(self,nextCorrectChoice):
self.sm.reset_transitions()
laserDuration = self.params['laserDuration'].get_value()
self.sm.set_extratimer('laserTimer', duration=laserDuration)
if self.params['laserTrial'].get_value():
laserOutput = ['stim1','stim2']
else:
laserOutput = []
targetDuration = self.params['targetDuration'].get_value()
relevantFeature = self.params['relevantFeature'].get_string()
stimOutput = stimSync+laserOutput
if nextCorrectChoice==self.results.labels['rewardSide']['left']:
rewardDuration = self.params['timeWaterValveL'].get_value()
#ledOutput = 'leftLED'
fromChoiceL = 'reward'
fromChoiceR = 'punish'
rewardOutput = 'leftWater'
correctSidePort = 'Lin'
elif nextCorrectChoice==self.results.labels['rewardSide']['right']:
rewardDuration = self.params['timeWaterValveR'].get_value()
#ledOutput = 'rightLED'
fromChoiceL = 'punish'
fromChoiceR = 'reward'
rewardOutput = 'rightWater'
correctSidePort = 'Rin'
else:
raise ValueError('Value of nextCorrectChoice is not appropriate')
randNum = (2*np.random.random(1)[0]-1) # In range [-1,1)
delayToTarget = self.params['delayToTargetMean'].get_value() + \
self.params['delayToTargetHalfRange'].get_value()*randNum
self.params['delayToTarget'].set_value(delayToTarget)
rewardAvailability = self.params['rewardAvailability'].get_value()
punishTimeError = self.params['punishTimeError'].get_value()
punishTimeEarly = self.params['punishTimeEarly'].get_value()
allowEarlyWithdrawal = self.params['allowEarlyWithdrawal'].get_string()
delayToSyncLight = self.params['delayToSyncLight'].get_value()
syncLightDuration = self.params['syncLightDuration'].get_value()
syncLightPortStr = self.params['syncLight'].get_string()
if syncLightPortStr=='off':
syncLightPort = []
else:
syncLightPort = [syncLightPortStr]
# -- Set state matrix --
outcomeMode = self.params['outcomeMode'].get_string()
if outcomeMode=='passive_exposure':
self.sm.add_state(name='startTrial', statetimer=0,
transitions={'Tup':'waitForCenterPoke'},
outputsOn=trialStartSync)
self.sm.add_state(name='waitForCenterPoke', statetimer=0,
transitions={'Tup':'delayPeriod'})
self.sm.add_state(name='delayPeriod', statetimer=delayToTarget,
transitions={'Tup':'playStimulus'})
self.sm.add_state(name='playStimulus', statetimer=targetDuration,
transitions={'Tup':'noChoice'},
outputsOn=stimOutput, serialOut=self.currentSoundID,
outputsOff=trialStartSync)
self.sm.add_state(name='noChoice', statetimer=delayToSyncLight,
transitions={'Tup':'syncLightOn'},
outputsOff=stimOutput)
self.sm.add_state(name='syncLightOn', statetimer=syncLightDuration,
transitions={'Tup':'syncLightOff'},
outputsOn=syncLightPort)
self.sm.add_state(name='syncLightOff', statetimer=0,
transitions={'Tup':'readyForNextTrial'},
outputsOff=syncLightPort)
elif outcomeMode=='simulated':
#stimOutput.append(ledOutput)
self.sm.add_state(name='startTrial', statetimer=0,
transitions={'Tup':'waitForCenterPoke'},
outputsOn=trialStartSync)
self.sm.add_state(name='waitForCenterPoke', statetimer=1,
transitions={'Tup':'playStimulus'})
self.sm.add_state(name='playStimulus', statetimer=targetDuration,
transitions={'Tup':'reward'},
outputsOn=stimOutput,serialOut=self.currentSoundID,
outputsOff=trialStartSync)
self.sm.add_state(name='reward', statetimer=rewardDuration,
transitions={'Tup':'stopReward'},
outputsOn=[rewardOutput],
outputsOff=stimOutput)
self.sm.add_state(name='stopReward', statetimer=0,
transitions={'Tup':'readyForNextTrial'},
outputsOff=[rewardOutput])
elif outcomeMode=='sides_direct':
self.sm.add_state(name='startTrial', statetimer=0,
transitions={'Tup':'waitForCenterPoke'},
outputsOn=trialStartSync)
self.sm.add_state(name='waitForCenterPoke', statetimer=LONGTIME,
transitions={'Cin':'playStimulus',correctSidePort:'playStimulus'})
self.sm.add_state(name='playStimulus', statetimer=targetDuration,
transitions={'Tup':'reward'},
outputsOn=stimOutput,serialOut=self.currentSoundID,
outputsOff=trialStartSync)
self.sm.add_state(name='reward', statetimer=rewardDuration,
transitions={'Tup':'stopReward'},
outputsOn=[rewardOutput],
outputsOff=stimOutput)
self.sm.add_state(name='stopReward', statetimer=0,
transitions={'Tup':'readyForNextTrial'},
outputsOff=[rewardOutput])
elif outcomeMode=='direct':
self.sm.add_state(name='startTrial', statetimer=0,
transitions={'Tup':'waitForCenterPoke'},
outputsOn=trialStartSync)
self.sm.add_state(name='waitForCenterPoke', statetimer=LONGTIME,
transitions={'Cin':'playStimulus'})
self.sm.add_state(name='playStimulus', statetimer=targetDuration,
transitions={'Tup':'reward'},
outputsOn=stimOutput,serialOut=self.currentSoundID,
outputsOff=trialStartSync)
self.sm.add_state(name='reward', statetimer=rewardDuration,
transitions={'Tup':'stopReward'},
outputsOn=[rewardOutput],
outputsOff=stimOutput)
self.sm.add_state(name='stopReward', statetimer=0,
transitions={'Tup':'readyForNextTrial'},
outputsOff=[rewardOutput])
elif outcomeMode=='on_next_correct':
self.sm.add_state(name='startTrial', statetimer=0,
transitions={'Tup':'waitForCenterPoke'},
outputsOn=trialStartSync)
self.sm.add_state(name='waitForCenterPoke', statetimer=LONGTIME,
transitions={'Cin':'delayPeriod'})
self.sm.add_state(name='delayPeriod', statetimer=delayToTarget,
transitions={'Tup':'playStimulus','Cout':'waitForCenterPoke'})
if allowEarlyWithdrawal=='on':
self.sm.add_state(name='playStimulus', statetimer=targetDuration,
transitions={'Tup':'waitForSidePoke','Cout':'waitForSidePoke',
'laserTimer':'turnOffLaserAndWaitForPoke'},
outputsOn=stimOutput, serialOut=self.currentSoundID,
outputsOff=trialStartSync)
else:
self.sm.add_state(name='playStimulus', statetimer=targetDuration,
transitions={'Tup':'waitForSidePoke','Cout':'earlyWithdrawal'},
outputsOn=stimOutput, serialOut=self.currentSoundID,
outputsOff=trialStartSync)
# NOTE: this is not ideal because it sends the system out of playStimulus
# onto waitForSidePoke (even if stim has not finished.
self.sm.add_state(name='turnOffLaserAndWaitForPoke', statetimer=0,
transitions={'Tup':'waitForSidePoke'},
outputsOff=laserOutput)
self.sm.add_state(name='waitForSidePoke', statetimer=rewardAvailability,
transitions={'Lin':'choiceLeft','Rin':'choiceRight',
'Tup':'noChoice','laserTimer':'turnOffLaserAndWaitForPoke'},
outputsOff=stimSync)
self.sm.add_state(name='keepWaitForSide', statetimer=rewardAvailability,
transitions={'Lin':'choiceLeft','Rin':'choiceRight',
'Tup':'noChoice'},
outputsOff=stimOutput)
if correctSidePort=='Lin':
self.sm.add_state(name='choiceLeft', statetimer=0,
transitions={'Tup':'reward'})
self.sm.add_state(name='choiceRight', statetimer=0,
transitions={'Tup':'keepWaitForSide'})
elif correctSidePort=='Rin':
self.sm.add_state(name='choiceLeft', statetimer=0,
transitions={'Tup':'keepWaitForSide'})
self.sm.add_state(name='choiceRight', statetimer=0,
transitions={'Tup':'reward'})
if allowEarlyWithdrawal=='on':
self.sm.add_state(name='earlyWithdrawal', statetimer=punishTimeEarly,
transitions={'Tup':'readyForNextTrial'},
outputsOff=stimOutput)
else:
self.sm.add_state(name='earlyWithdrawal', statetimer=punishTimeEarly,
transitions={'Tup':'readyForNextTrial'},
outputsOff=stimOutput,serialOut=self.punishSoundID)
self.sm.add_state(name='reward', statetimer=rewardDuration,
transitions={'Tup':'stopReward'},
outputsOn=[rewardOutput])
self.sm.add_state(name='stopReward', statetimer=0,
transitions={'Tup':'readyForNextTrial'},
outputsOff=[rewardOutput])
self.sm.add_state(name='punish', statetimer=punishTimeError,
transitions={'Tup':'readyForNextTrial'})
self.sm.add_state(name='noChoice', statetimer=0,
transitions={'Tup':'readyForNextTrial'})
elif outcomeMode=='only_if_correct':
self.sm.add_state(name='startTrial', statetimer=0,
transitions={'Tup':'waitForCenterPoke'},
outputsOn=trialStartSync)
self.sm.add_state(name='waitForCenterPoke', statetimer=LONGTIME,
transitions={'Cin':'delayPeriod'})
self.sm.add_state(name='delayPeriod', statetimer=delayToTarget,
transitions={'Tup':'playStimulus','Cout':'waitForCenterPoke'})
# Note that 'delayPeriod' may happen several times in a trial, so
# trialStartSync going off would only meaningful for the first time in the trial.
if allowEarlyWithdrawal=='on':
self.sm.add_state(name='playStimulus', statetimer=targetDuration,
transitions={'Tup':'waitForSidePoke','Cout':'waitForSidePoke',
'laserTimer':'turnOffLaserAndWaitForPoke'},
outputsOn=stimOutput, serialOut=self.currentSoundID,
outputsOff=trialStartSync,
trigger=['laserTimer'])
else:
### NOT IMPLEMENTED ###
self.sm.add_state(name='playStimulus', statetimer=targetDuration,
transitions={'Tup':'waitForSidePoke','Cout':'earlyWithdrawal'},
outputsOn=stimOutput, serialOut=self.currentSoundID,
outputsOff=trialStartSync)
self.sm.add_state(name='turnOffLaserAndWaitForPoke', statetimer=0,
transitions={'Tup':'waitForSidePoke'},
outputsOff=laserOutput)
self.sm.add_state(name='waitForSidePoke', statetimer=rewardAvailability,
transitions={'Lin':'choiceLeft','Rin':'choiceRight',
'Tup':'noChoice','laserTimer':'turnOffLaserAndWaitForPoke'},
outputsOff=stimSync)
if correctSidePort=='Lin':
self.sm.add_state(name='choiceLeft', statetimer=0,
transitions={'Tup':'reward'}, outputsOff=laserOutput)
self.sm.add_state(name='choiceRight', statetimer=0,
transitions={'Tup':'punish'}, outputsOff=laserOutput)
elif correctSidePort=='Rin':
self.sm.add_state(name='choiceLeft', statetimer=0,
transitions={'Tup':'punish'}, outputsOff=laserOutput)
self.sm.add_state(name='choiceRight', statetimer=0,
transitions={'Tup':'reward'}, outputsOff=laserOutput)
self.sm.add_state(name='earlyWithdrawal', statetimer=punishTimeEarly,
transitions={'Tup':'readyForNextTrial'},
outputsOff=stimOutput,serialOut=self.punishSoundID)
self.sm.add_state(name='reward', statetimer=rewardDuration,
transitions={'Tup':'stopReward'},
outputsOn=[rewardOutput])
self.sm.add_state(name='stopReward', statetimer=0,
transitions={'Tup':'readyForNextTrial'},
outputsOff=[rewardOutput]+stimOutput)
self.sm.add_state(name='punish', statetimer=punishTimeError,
transitions={'Tup':'readyForNextTrial'})
self.sm.add_state(name='noChoice', statetimer=0,
transitions={'Tup':'readyForNextTrial'})
else:
raise TypeError('outcomeMode={0} has not been implemented'.format(outcomeMode))
###print(self.sm) ### DEBUG
self.dispatcher.set_state_matrix(self.sm)
def calculate_results(self,trialIndex):
# -- Find outcomeMode for this trial --
outcomeModeID = self.params.history['outcomeMode'][trialIndex]
outcomeModeString = self.params['outcomeMode'].get_items()[outcomeModeID]
eventsThisTrial = self.dispatcher.events_one_trial(trialIndex)
statesThisTrial = eventsThisTrial[:,2]
#print(eventsThisTrial)
# -- Find beginning of trial --
startTrialStateID = self.sm.statesNameToIndex['startTrial']
# FIXME: Next line seems inefficient. Is there a better way?
startTrialInd = np.flatnonzero(statesThisTrial==startTrialStateID)[0]
self.results['timeTrialStart'][trialIndex] = eventsThisTrial[startTrialInd,0]
# ===== Calculate times of events =====
# -- Check if it's an aborted trial --
lastEvent = eventsThisTrial[-1,:]
if lastEvent[1]==-1 and lastEvent[2]==0:
self.results['timeTarget'][trialIndex] = np.nan
self.results['timeCenterIn'][trialIndex] = np.nan
self.results['timeCenterOut'][trialIndex] = np.nan
self.results['timeSideIn'][trialIndex] = np.nan
# -- Otherwise evaluate times of important events --
else:
# -- Store time of stimulus --
targetStateID = self.sm.statesNameToIndex['playStimulus']
targetEventInd = np.flatnonzero(statesThisTrial==targetStateID)[0]
self.results['timeTarget'][trialIndex] = eventsThisTrial[targetEventInd,0]
# -- Find center poke-in time --
if outcomeModeString in ['on_next_correct','only_if_correct']:
seqCin = [self.sm.statesNameToIndex['waitForCenterPoke'],
self.sm.statesNameToIndex['delayPeriod'],
self.sm.statesNameToIndex['playStimulus']]
elif outcomeModeString in ['passive_exposure','sides_direct','direct']:
seqCin = [self.sm.statesNameToIndex['waitForCenterPoke'],
self.sm.statesNameToIndex['playStimulus']]
else:
print('CenterIn time cannot be calculated for this Outcome Mode.')
seqPos = np.flatnonzero(utils.find_state_sequence(statesThisTrial,seqCin))
timeValue = eventsThisTrial[seqPos[0]+1,0] if len(seqPos) else np.nan
self.results['timeCenterIn'][trialIndex] = timeValue
############# FIXME: create a state for Cout so it's easy to get timting ########
# -- Find center poke-out time --
if len(seqPos):
cInInd = seqPos[0]+1
cOutInd = np.flatnonzero(eventsThisTrial[cInInd:,1]==self.sm.eventsDict['Cout'])
timeValue = eventsThisTrial[cOutInd[0]+cInInd,0] if len(cOutInd) else np.nan
else:
timeValue = np.nan
self.results['timeCenterOut'][trialIndex] = timeValue
# -- Find side poke time --
if outcomeModeString in ['on_next_correct','only_if_correct']:
leftInInd = utils.find_transition(statesThisTrial,
self.sm.statesNameToIndex['waitForSidePoke'],
self.sm.statesNameToIndex['choiceLeft'])
rightInInd = utils.find_transition(statesThisTrial,
self.sm.statesNameToIndex['waitForSidePoke'],
self.sm.statesNameToIndex['choiceRight'])
if len(leftInInd):
timeValue = eventsThisTrial[leftInInd[0],0]
elif len(rightInInd):
timeValue = eventsThisTrial[rightInInd[0],0]
else:
timeValue = np.nan
elif outcomeModeString in ['passive_exposure','sides_direct','direct']:
timeValue = np.nan
self.results['timeSideIn'][trialIndex] = timeValue
# ===== Calculate choice and outcome =====
# -- Check if it's an aborted trial --
lastEvent = eventsThisTrial[-1,:]
if lastEvent[1]==-1 and lastEvent[2]==0:
self.results['outcome'][trialIndex] = self.results.labels['outcome']['aborted']
self.results['choice'][trialIndex] = self.results.labels['choice']['none']
# -- Otherwise evaluate 'choice' and 'outcome' --
else:
if outcomeModeString in ['passive_exposure','sides_direct','direct']:
self.results['outcome'][trialIndex] = self.results.labels['outcome']['free']
self.results['choice'][trialIndex] = self.results.labels['choice']['none']
self.params['nValid'].add(1)
self.params['nRewarded'].add(1)
self.results['valid'][trialIndex] = 1
if outcomeModeString=='on_next_correct' or outcomeModeString=='only_if_correct':
if self.sm.statesNameToIndex['choiceLeft'] in eventsThisTrial[:,2]:
self.results['choice'][trialIndex] = self.results.labels['choice']['left']
elif self.sm.statesNameToIndex['choiceRight'] in eventsThisTrial[:,2]:
self.results['choice'][trialIndex] = self.results.labels['choice']['right']
else:
self.results['choice'][trialIndex] = self.results.labels['choice']['none']
self.results['outcome'][trialIndex] = \
self.results.labels['outcome']['nochoice']
if self.sm.statesNameToIndex['reward'] in eventsThisTrial[:,2]:
self.results['outcome'][trialIndex] = \
self.results.labels['outcome']['correct']
self.params['nRewarded'].add(1)
if outcomeModeString=='on_next_correct' and \
self.sm.statesNameToIndex['keepWaitForSide'] in eventsThisTrial[:,2]:
self.results['outcome'][trialIndex] = \
self.results.labels['outcome']['aftererror']
else:
if self.sm.statesNameToIndex['earlyWithdrawal'] in eventsThisTrial[:,2]:
self.results['outcome'][trialIndex] = \
self.results.labels['outcome']['invalid']
elif self.sm.statesNameToIndex['punish'] in eventsThisTrial[:,2]:
self.results['outcome'][trialIndex] = \
self.results.labels['outcome']['error']
# -- Check if it was a valid trial --
if self.sm.statesNameToIndex['waitForSidePoke'] in eventsThisTrial[:,2]:
self.params['nValid'].add(1)
self.results['valid'][trialIndex] = 1
def execute_automation(self,nextTrial):
automationMode = self.params['automationMode'].get_string()
nValid = self.params['nValid'].get_value()
if automationMode=='increase_delay':
if nValid>0 and self.results['valid'][nextTrial-1] and not nValid%10:
self.params['delayToTargetMean'].add(0.010)
def closeEvent(self, event):
'''
Executed when closing the main window.
This method is inherited from QtWidgets.QMainWindow, which explains
its camelCase naming.
'''
self.soundClient.shutdown()
self.dispatcher.die()
event.accept()
if __name__ == '__main__':
(app,paradigm) = paramgui.create_app(Paradigm)