def __finishTrial__(self, trialDict):
"""
Perform some finalization after we we have parsed a trial
Arguments:
trialDict -- a trial dictionary
"""
nPhase = len(self.traceDict)
i = 1
if self.traceImg or self.tracePlot:
plt.clf()
plt.close()
plt.figure(figsize=(12,12))
plt.subplots_adjust(hspace=.5, wspace=.5)
for phase, trace in self.traceDict.iteritems():
a = np.array(trace, dtype=float)
if len(a) == 0:
continue
origA = a.copy()
if self.blinkReconstruct:
a[:,2] = TraceKit.blinkReconstruct(a[:,2])
if self.traceSmoothParams != None:
a[:,0] = TraceKit.smooth(a[:,0], **self.traceSmoothParams)
a[:,1] = TraceKit.smooth(a[:,1], **self.traceSmoothParams)
a[:,2] = TraceKit.smooth(a[:,2], **self.traceSmoothParams)
self.traceDict[phase] = a
path = os.path.join(self.traceFolder, '%s-%.5d-%s.npy' \
% (trialDict['file'], trialDict['trialId'], phase))
if not os.path.exists(self.traceFolder):
print('Creating traceFolder: %s' % self.traceFolder)
os.makedirs(self.traceFolder)
np.save(path, a)
trialDict['__trace_%s__' % phase] = path
if self.traceImg or self.tracePlot:
plt.subplot(nPhase, 3, i)
i += 1
plt.title('X(%s)' % phase)
plt.plot(a[:,0])
if self.traceSmoothParams != None:
plt.plot(origA[:,0])
plt.subplot(nPhase, 3, i)
i += 1
plt.title('Y(%s)' % phase)
plt.plot(a[:,1])
if self.traceSmoothParams != None:
plt.plot(origA[:,1])
plt.subplot(nPhase, 3, i)
i += 1
plt.title('Pupil(%s)' % phase)
plt.plot(a[:,2])
if self.traceSmoothParams != None or self.blinkReconstruct:
plt.plot(origA[:,2])
if self.traceImg or self.tracePlot:
plt.suptitle(path)
if self.traceImg:
path = os.path.join(self.traceFolder, 'png', '%s-%.5d-%s.png' \
% (trialDict['file'], trialDict['trialId'], phase))
if not os.path.exists(os.path.join(self.traceFolder, 'png')):
print('Creating traceImgFolder: %s' % os.path.join( \
self.traceFolder, 'png'))
if not os.path.exists(os.path.join(self.traceFolder, 'png')):
os.makedirs(os.path.join(self.traceFolder, 'png'))
plt.savefig(path)
if self.tracePlot:
plt.show()
def parseLine(self, trialDict, l):
"""
desc:
Parses a single line from the EyeLink .asc file.
arguments:
trialDict:
desc: Trial information.
type: dict
l:
desc: A white-space-splitted line.
type: list
"""
trialDict['subject_nr'] = int(trialDict['file'][2:4])
# The active period is the moment from the first round until the winner
# is announced. This way we don't count the extra time taken by the
# preview and end animation.
if 'start_round' in l and l[3] == 0:
self.active = True
self.startTime = l[1]
if 'status=winner' in l:
self.active = False
self.endTime = l[1]
# Check for check fixation during the active period.
if self.active:
fix = self.toFixation(l)
if fix != None:
fixErr = np.sqrt( (fix['x']-xc)**2 + (fix['y']-yc)**2 )
trialDict['maxFixErr'] = max(trialDict['maxFixErr'], fixErr)
self.fixList.append( (fix['x'], fix['y']) )
if 'fixation_lost' in l:
trialDict['nFixLost'] += 1
# Get target coordinates
# MSG 18895724 item id="B" status=init likelihood=1 ecc=375
# angle=0.785398163397 size=99 brightness=-1 color=green opacity=0.5
# x=265.165042945 y=265.16504
if 'target' in trialDict and ('id="%s"' % trialDict['target']) in l:
if 'targetX' not in trialDict:
# The x and y coordinates are sometimes chopped off, because the
# logging string is too long. Therefore, we recalculate them
# from the radius and eccentricity.
for i in l:
if type(i) != str:
continue
if 'ecc' in i:
r = float(i[4:])
if 'angle' in i:
a = float(i[6:])
x = np.cos(a) * r
y = np.sin(a) * r
# If possible, doubcheck the coordinates for strings that have
# not been chopped off.
try:
_x = float(l[-2][2:])
_y = float(l[-1][2:])
assert(int(_x) == int(x))
assert(int(_y) == int(y))
except:
print 'Failed to verify'
trialDict['targetX'] = x
trialDict['targetY'] = y
# For Exp 1:
# MSG 7093294 var correct 1
# For Exp 2+:
# MSG 7093294 var correct_selection 1
if ('correct' in l or 'correct_selection' in l) and l[4] in (0, 1):
self.correct = l[4]
# Collect pupil trace
# MSG 18625682 start_round 0
if 'start_round' in l:
self.tracePhase = 'dummy'
self.startRoundTime = l[1]
# Determine whether the target is bright or dark
if self.tracePhase != None and 'item' in l:
if 'id="%s"' % trialDict['target'] in l:
if 'brightness=1.0' in l:
self.phaseType = 'bright'
elif 'brightness=-1.0' in l:
self.phaseType = 'dark'
else:
raise Exception('Incorrect brightness!')
if 'end_invert' in l:
self.endInvertTime.append(l[1] - self.startRoundTime)
if 'end_adaptation' in l:
self.endAdaptationTime.append(l[1] - self.startRoundTime)
if 'end_collection' in l:
self.endCollectionTime.append(l[1] - self.startRoundTime)
if 'end_round' in l:
if 'dummy' in self.traceDict:
a = np.array(self.traceDict['dummy'], dtype=float)
a[:,2] = tk.blinkReconstruct(a[:,2])
global rnd
path = 'traces/subject%0d-%04d-%s.npy' % \
(trialDict['subject_nr'], rnd, self.phaseType)
rnd += 1
print(path)
np.save(path, a)
del self.traceDict['dummy']
else:
print('Warning: No trace collected!')
self.tracePhase = None
self.endRoundTime.append(l[1] - self.startRoundTime)
self.roundId += 1
# Collect item information and likelihood ratios
# MSG 1806804 item id="B" status=init likelihood=1 ecc=310
# angle=-0.785398163397 size=64 brightness=1 color=green opacity=0.5
# x=219.203102168
if self.tracePhase != None:
# Process item
if len(l) > 2 and l[2] == 'item':
_dict = {}
for s in l[3:]:
_l = s.split('=')
if len(_l) != 2:
continue
_dict[_l[0]] = _l[1].strip('"')
if _dict['id'] == trialDict['target']:
_id = 'target'
else:
_id = _dict['id']
if _id not in self.likelihoodTraces:
self.likelihoodTraces[_id] = []
self.likelihoodTraces[_id].append(_dict['likelihood'])
