def __init__(self, path='data', ext='.asc', startTrialKey='start_trial',
endTrialKey='stop_trial', variableKey='var', dtype='|S128', maxN=None,
maxTrialId=None, requireEndTrial=True, traceFolder='traces',
offlineDriftCorr=False, skipList=[], blinkReconstruct=False, only=None,
acceptNonMatchingColumns=True):
"""
Constructor. Reads all Eyelink ASCII files from a specific folder.
Keyword arguments:
path -- the folder containing the csv files (default='data')
ext -- the extension of the csv files (default='.csv')
startTrialKey -- the start trial keyword (default='start_trial')
endTrialKey -- the stop trial keyword (default='stop_trial')
variableKey -- the variable keyword (default='var')
dtype -- the numpy dtype to be used (default='|S128')
maxN -- the maximum number of subjects to process
(default=None)
maxTrialId -- the maximum number of trials to process
(default=None)
requireEndTrial -- indicates whether an exception should be raised if a
trial hasn't been neatly closed. Otherwise the trial
is simply disregarded. (default=True)
traceFolder -- the folder to save the gaze traces. Traces are saved
as 3d numpy arrays (x, y, pupil size) in .npy
format. To start collecting traces, set
`self.tracePhase` to a value. Use the value
'__baseline__' to use an automatic baseline.
(default='traces')
offlineDriftCorr -- Indicates whether coordinates should be
corrected based on the drift-correction check,
in case the 'active' drift correctrion is
disabled (as on the Eyelink 1000).
(default=False)
skipList -- A list of trialIDs that should not be processed.
(default=[])
blinkReconstruct -- Indicates whether pupil size should be
interpolated during blinks. (default=False)
only -- A list of files that should be analyzed, or None
to analyze all files. Mostly useful for debugging
purposes. (default=None)
acceptNonMatchingColumns --- Boolean indicating whether or not to
raise an exception if current dm and
to-be-added dm
do not have identical column headers.
If set to True, the intersection of
column headers is used and the check
is not carried out. If set to False,
the the check is carried out.
(default=True)
"""
self.startTrialKey = startTrialKey
self.endTrialKey = endTrialKey
self.variableKey = variableKey
self.dtype = dtype
self.requireEndTrial = requireEndTrial
self.maxTrialId = maxTrialId
self.tracePhase = None
self.traceFolder = traceFolder
self.traceSmoothParams = None
self.offlineDriftCorr = offlineDriftCorr
self.driftAdjust = 0,0
self.skipList = skipList
self.blinkReconstruct = blinkReconstruct
self.acceptNonMatchingColumns = acceptNonMatchingColumns
self.traceImg = '--traceimg' in sys.argv
self.tracePlot = '--traceplot' in sys.argv
print '\nScanning \'%s\'' % path
self.dm = None
nFile = 0
for fname in os.listdir(path):
if only != None and fname not in only:
print 'Skipping %s ...' % fname
continue
if os.path.splitext(fname)[1] == ext:
sys.stdout.write('Reading %s ...' % fname)
sys.stdout.flush()
a = self.parseFile(os.path.join(path, fname))
dm = DataMatrix(a)
if self.dm == None:
self.dm = dm
else:
# If column headers are not identical:
if self.dm.columns() != dm.columns():
# Determine warning message:
warningMsg = "The column headers are not identical. Difference:\n%s"\
% "\n".join(list(set(self.dm.columns()).\
symmetric_difference(set(dm.columns()))))
# Determine whether to only print the warning,
# or to raise an exception:
if not acceptNonMatchingColumns:
raise Exception(warningMsg)
if acceptNonMatchingColumns:
print warningMsg
self.dm += dm
print '(%d rows)' % len(dm)
nFile += 1
if maxN != None and nFile >= maxN:
break
print '%d files\n' % nFile
