def readOneChannelEventOrSpike(self, fid, channel_num, header, lazy=True):
# return SPikeTrain or EventArray
channelHeader = header.channelHeaders[channel_num]
if channelHeader.firstblock < 0: return
if channelHeader.kind not in [2, 3, 4, 5, 6, 7, 8]: return
## Step 1 : type of blocks
if channelHeader.kind in [2, 3, 4]:
# Event data
fmt = [('tick', 'i4')]
elif channelHeader.kind in [5]:
# Marker data
fmt = [('tick', 'i4'), ('marker', 'i4')]
elif channelHeader.kind in [6]:
# AdcMark data
fmt = [('tick', 'i4'), ('marker', 'i4'),
('adc', 'S%d' % channelHeader.n_extra)]
elif channelHeader.kind in [7]:
# RealMark data
fmt = [('tick', 'i4'), ('marker', 'i4'),
('real', 'S%d' % channelHeader.n_extra)]
elif channelHeader.kind in [8]:
# TextMark data
fmt = [('tick', 'i4'), ('marker', 'i4'),
('label', 'S%d' % channelHeader.n_extra)]
dt = np.dtype(fmt)
## Step 2 : first read for allocating mem
fid.seek(channelHeader.firstblock)
totalitems = 0
for _ in range(channelHeader.blocks):
blockHeader = HeaderReader(fid, np.dtype(blockHeaderDesciption))
totalitems += blockHeader.items
if blockHeader.succ_block > 0:
fid.seek(blockHeader.succ_block)
#~ print 'totalitems' , totalitems
if lazy:
if channelHeader.kind in [2, 3, 4, 5, 8]:
ea = EventArray()
ea.annotate(channel_index=channel_num)
ea.lazy_shape = totalitems
return [ea]
elif channelHeader.kind in [6, 7]:
sptr = SpikeTrain(
[] * pq.s,
t_stop=1e99) # correct value for t_stop to be put in later
sptr.annotate(channel_index=channel_num, ced_unit=0)
sptr.lazy_shape = totalitems
return [sptr]
else:
alltrigs = np.zeros(totalitems, dtype=dt)
## Step 3 : read
fid.seek(channelHeader.firstblock)
pos = 0
for _ in range(channelHeader.blocks):
blockHeader = HeaderReader(fid,
np.dtype(blockHeaderDesciption))
# read all events in block
trigs = np.fromstring(fid.read(blockHeader.items *
dt.itemsize),
dtype=dt)
alltrigs[pos:pos + trigs.size] = trigs
pos += trigs.size
if blockHeader.succ_block > 0:
fid.seek(blockHeader.succ_block)
## Step 3 convert in neo standard class : eventarrays or spiketrains
alltimes = alltrigs['tick'].astype(
'f') * header.us_per_time * header.dtime_base * pq.s
if channelHeader.kind in [2, 3, 4, 5, 8]:
#events
ea = EventArray()
ea.annotate(channel_index=channel_num)
ea.times = alltimes
if channelHeader.kind >= 5:
# Spike2 marker is closer to label sens of neo
ea.labels = alltrigs['marker'].astype('S32')
if channelHeader.kind == 8:
ea.annotate(extra_labels=alltrigs['label'])
return [ea]
elif channelHeader.kind in [6, 7]:
# spiketrains
# waveforms
if channelHeader.kind == 6:
waveforms = np.fromstring(alltrigs['adc'].tostring(),
dtype='i2')
waveforms = waveforms.astype(
'f4'
) * channelHeader.scale / 6553.6 + channelHeader.offset
elif channelHeader.kind == 7:
waveforms = np.fromstring(alltrigs['real'].tostring(),
dtype='f4')
if header.system_id >= 6 and channelHeader.interleave > 1:
waveforms = waveforms.reshape(
(alltimes.size, -1, channelHeader.interleave))
waveforms = waveforms.swapaxes(1, 2)
else:
waveforms = waveforms.reshape((alltimes.size, 1, -1))
if header.system_id in [1, 2, 3, 4, 5]:
sample_interval = (channelHeader.divide *
header.us_per_time *
header.time_per_adc) * 1e-6
else:
sample_interval = (channelHeader.l_chan_dvd *
header.us_per_time * header.dtime_base)
if channelHeader.unit in unit_convert:
unit = pq.Quantity(1, unit_convert[channelHeader.unit])
else:
#print channelHeader.unit
try:
unit = pq.Quantity(1, channelHeader.unit)
except:
unit = pq.Quantity(1, '')
if len(alltimes) > 0:
t_stop = alltimes.max(
) # can get better value from associated AnalogSignal(s) ?
else:
t_stop = 0.0
if not self.ced_units:
sptr = SpikeTrain(alltimes,
waveforms=waveforms * unit,
sampling_rate=(1. / sample_interval) *
pq.Hz,
t_stop=t_stop)
sptr.annotate(channel_index=channel_num, ced_unit=0)
return [sptr]
sptrs = []
for i in set(alltrigs['marker'] & 255):
sptr = SpikeTrain(
alltimes[alltrigs['marker'] == i],
waveforms=waveforms[alltrigs['marker'] == i] * unit,
sampling_rate=(1. / sample_interval) * pq.Hz,
t_stop=t_stop)
sptr.annotate(channel_index=channel_num, ced_unit=i)
sptrs.append(sptr)
return sptrs
def readOneChannelEventOrSpike(self , fid, channel_num, header ,lazy = True):
# return SPikeTrain or EventArray
channelHeader = header.channelHeaders[channel_num]
if channelHeader.firstblock <0: return
if channelHeader.kind not in [2, 3, 4 , 5 , 6 ,7, 8]: return
## Step 1 : type of blocks
if channelHeader.kind in [2, 3, 4]:
# Event data
fmt = [('tick' , 'i4') ]
elif channelHeader.kind in [5]:
# Marker data
fmt = [('tick' , 'i4') , ('marker' , 'i4') ]
elif channelHeader.kind in [6]:
# AdcMark data
fmt = [('tick' , 'i4') , ('marker' , 'i4') , ('adc' , 'S%d' %channelHeader.n_extra )]
elif channelHeader.kind in [7]:
# RealMark data
fmt = [('tick' , 'i4') , ('marker' , 'i4') , ('real' , 'S%d' %channelHeader.n_extra )]
elif channelHeader.kind in [8]:
# TextMark data
fmt = [('tick' , 'i4') , ('marker' , 'i4') , ('label' , 'S%d'%channelHeader.n_extra)]
dt = np.dtype(fmt)
## Step 2 : first read for allocating mem
fid.seek(channelHeader.firstblock)
totalitems = 0
for _ in range(channelHeader.blocks) :
blockHeader = HeaderReader(fid, np.dtype(blockHeaderDesciption))
totalitems += blockHeader.items
if blockHeader.succ_block > 0 :
fid.seek(blockHeader.succ_block)
#~ print 'totalitems' , totalitems
if lazy :
if channelHeader.kind in [2, 3, 4 , 5 , 8]:
ea = EventArray( )
ea.annotate(channel_index = channel_num)
ea.lazy_shape = totalitems
return ea
elif channelHeader.kind in [6 ,7]:
sptr = SpikeTrain([ ]*pq.s, t_stop=1e99) # correct value for t_stop to be put in later
sptr.annotate(channel_index = channel_num)
sptr.lazy_shape = totalitems
return sptr
else:
alltrigs = np.zeros( totalitems , dtype = dt)
## Step 3 : read
fid.seek(channelHeader.firstblock)
pos = 0
for _ in range(channelHeader.blocks) :
blockHeader = HeaderReader(fid, np.dtype(blockHeaderDesciption))
# read all events in block
trigs = np.fromstring( fid.read( blockHeader.items*dt.itemsize) , dtype = dt)
alltrigs[pos:pos+trigs.size] = trigs
pos += trigs.size
if blockHeader.succ_block > 0 :
fid.seek(blockHeader.succ_block)
## Step 3 convert in neo standard class : eventarrays or spiketrains
alltimes = alltrigs['tick'].astype('f')*header.us_per_time * header.dtime_base*pq.s
if channelHeader.kind in [2, 3, 4 , 5 , 8]:
#events
ea = EventArray( )
ea.annotate(channel_index = channel_num)
ea.times = alltimes
if channelHeader.kind >= 5:
# Spike2 marker is closer to label sens of neo
ea.labels = alltrigs['marker'].astype('S32')
if channelHeader.kind == 8:
ea.annotate(extra_labels = alltrigs['label'])
return ea
elif channelHeader.kind in [6 ,7]:
# spiketrains
# waveforms
if channelHeader.kind == 6 :
waveforms = np.fromstring(alltrigs['adc'].tostring() , dtype = 'i2')
waveforms = waveforms.astype('f4') *channelHeader.scale/ 6553.6 + channelHeader.offset
elif channelHeader.kind == 7 :
waveforms = np.fromstring(alltrigs['real'].tostring() , dtype = 'f4')
if header.system_id>=6 and channelHeader.interleave>1:
waveforms = waveforms.reshape((alltimes.size,-1,channelHeader.interleave))
waveforms = waveforms.swapaxes(1,2)
else:
waveforms = waveforms.reshape(( alltimes.size,1, -1))
if header.system_id in [1,2,3,4,5]:
sample_interval = (channelHeader.divide*header.us_per_time*header.time_per_adc)*1e-6
else :
sample_interval = (channelHeader.l_chan_dvd*header.us_per_time*header.dtime_base)
if channelHeader.unit in unit_convert:
unit = pq.Quantity(1, unit_convert[channelHeader.unit] )
else:
#print channelHeader.unit
try:
unit = pq.Quantity(1, channelHeader.unit )
except:
unit = pq.Quantity(1, '')
if len(alltimes) > 0:
t_stop = alltimes.max() # can get better value from associated AnalogSignal(s) ?
else:
t_stop = 0.0
sptr = SpikeTrain(alltimes,
waveforms = waveforms*unit,
sampling_rate = (1./sample_interval)*pq.Hz,
t_stop = t_stop
)
sptr.annotate(channel_index = channel_num)
return sptr
