def proc_src_condition_unit(spikeunit, sweepLen, side, ADperiod, respWin,
damaIndexes, timeStamps, filename):
'''Get the unit in a condition in a src file that has been processed by
the official matlab function. See proc_src for details'''
if not damaIndexes:
damaIndexes = [0] * len(spikeunit)
timeStamps = [0] * len(spikeunit)
trains = []
for sweep, damaIndex, timeStamp in zip(spikeunit, damaIndexes, timeStamps):
timeStamp = brainwaresrcio.convert_brainwaresrc_timestamp(timeStamp)
train = proc_src_condition_unit_repetition(sweep, damaIndex, timeStamp,
sweepLen, side, ADperiod,
respWin, filename)
trains.append(train)
return trains
def proc_src_condition_unit(spikeunit, sweepLen, side, ADperiod, respWin,
damaIndexes, timeStamps, filename):
'''Get the unit in a condition in a src file that has been processed by
the official matlab function. See proc_src for details'''
if not damaIndexes:
damaIndexes = [0] * len(spikeunit)
timeStamps = [0] * len(spikeunit)
trains = []
for sweep, damaIndex, timeStamp in zip(spikeunit, damaIndexes,
timeStamps):
timeStamp = brainwaresrcio.convert_brainwaresrc_timestamp(timeStamp)
train = proc_src_condition_unit_repetition(sweep, damaIndex,
timeStamp, sweepLen,
side, ADperiod, respWin,
filename)
trains.append(train)
return trains
def proc_src_comments(srcfile, filename):
'''Get the comments in an src file that has been#!N
processed by the official
matlab function. See proc_src for details'''
comm_seg = Segment(name='Comments', file_origin=filename)
commentarray = srcfile['comments'].flatten()[0]
senders = [res[0] for res in commentarray['sender'].flatten()]
texts = [res[0] for res in commentarray['text'].flatten()]
timeStamps = [res[0, 0] for res in commentarray['timeStamp'].flatten()]
timeStamps = np.array(timeStamps, dtype=np.float32)
t_start = timeStamps.min()
timeStamps = pq.Quantity(timeStamps - t_start, units=pq.d).rescale(pq.s)
texts = np.array(texts, dtype='S')
senders = np.array(senders, dtype='S')
t_start = brainwaresrcio.convert_brainwaresrc_timestamp(t_start.tolist())
comments = Event(times=timeStamps, labels=texts, senders=senders)
comm_seg.events = [comments]
comm_seg.rec_datetime = t_start
return comm_seg
def proc_src_comments(srcfile, filename):
'''Get the comments in an src file that has been#!N
processed by the official
matlab function. See proc_src for details'''
comm_seg = Segment(name='Comments', file_origin=filename)
commentarray = srcfile['comments'].flatten()[0]
senders = [res[0] for res in commentarray['sender'].flatten()]
texts = [res[0] for res in commentarray['text'].flatten()]
timeStamps = [res[0, 0] for res in commentarray['timeStamp'].flatten()]
timeStamps = np.array(timeStamps, dtype=np.float32)
t_start = timeStamps.min()
timeStamps = pq.Quantity(timeStamps - t_start, units=pq.d).rescale(pq.s)
texts = np.array(texts, dtype='S')
senders = np.array(senders, dtype='S')
t_start = brainwaresrcio.convert_brainwaresrc_timestamp(t_start.tolist())
comments = EventArray(times=timeStamps, labels=texts, senders=senders)
comm_seg.eventarrays = [comments]
comm_seg.rec_datetime = t_start
return comm_seg
def proc_src_comments(srcfile, filename):
'''Get the comments in an src file that has been#!N
processed by the official
matlab function. See proc_src for details'''
comm_seg = Segment(name='Comments', file_origin=filename)
commentarray = srcfile['comments'].flatten()[0]
senders = [res[0] for res in commentarray['sender'].flatten()]
texts = [res[0] for res in commentarray['text'].flatten()]
timeStamps = [res[0, 0] for res in commentarray['timeStamp'].flatten()]
for sender, text, timeStamp in zip(senders, texts, timeStamps):
time = pq.Quantity(timeStamp, units=pq.d)
timeStamp = brainwaresrcio.convert_brainwaresrc_timestamp(timeStamp)
commentevent = Event(time=time,
label=str(text),
sender=str(sender),
name='Comment', file_origin=filename,
description='container for a comment',
timestamp=timeStamp)
comm_seg.events.append(commentevent)
return comm_seg
def proc_src_comments(srcfile, filename):
'''Get the comments in an src file that has been#!N
processed by the official
matlab function. See proc_src for details'''
comm_seg = Segment(name='Comments', file_origin=filename)
commentarray = srcfile['comments'].flatten()[0]
senders = [res[0] for res in commentarray['sender'].flatten()]
texts = [res[0] for res in commentarray['text'].flatten()]
timeStamps = [res[0, 0] for res in commentarray['timeStamp'].flatten()]
for sender, text, timeStamp in zip(senders, texts, timeStamps):
time = pq.Quantity(timeStamp, units=pq.d)
timeStamp = brainwaresrcio.convert_brainwaresrc_timestamp(timeStamp)
commentevent = Event(time=time,
label=str(text),
sender=str(sender),
name='Comment',
file_origin=filename,
description='container for a comment',
timestamp=timeStamp)
comm_seg.events.append(commentevent)
return comm_seg
