/usr/share/pyshared/neo/io/tdtio.py is in python-neo 0.3.3-1.
This file is owned by root:root, with mode 0o644.
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"""
Class for reading data from from Tucker Davis TTank format.
Terminology:
TDT hold data with tanks (actually a directory). And tanks hold sub block (sub directories).
Tanks correspond to neo.Block and tdt block correspond to neo.Segment.
Note the name Block is ambiguous because it does not refer to same thing in TDT terminilogy and neo.
Depend on:
Supported : Read
Author: sgarcia
"""
import os
import struct
import sys
import numpy as np
import quantities as pq
from neo.io.baseio import BaseIO
from neo.core import Block, Segment, AnalogSignal, SpikeTrain, EventArray
from neo.io.tools import create_many_to_one_relationship, iteritems
PY3K = (sys.version_info[0] == 3)
class TdtIO(BaseIO):
"""
Class for reading data from from Tucker Davis TTank format.
Usage:
>>> from neo import io
>>> r = io.TdtIO(dirname='aep_05')
>>> bl = r.read_block(lazy=False, cascade=True)
>>> print bl.segments
[<neo.core.segment.Segment object at 0x1060a4d10>]
>>> print bl.segments[0].analogsignals
[<AnalogSignal(array([ 2.18811035, 2.19726562, 2.21252441, ..., 1.33056641,
1.3458252 , 1.3671875 ], dtype=float32) * pA, [0.0 s, 191.2832 s], sampling rate: 10000.0 Hz)>]
>>> print bl.segments[0].eventarrays
[]
"""
is_readable = True
is_writable = False
supported_objects = [Block, Segment , AnalogSignal, EventArray ]
readable_objects = [Block]
writeable_objects = []
has_header = False
is_streameable = False
read_params = {
Block : [
],
}
write_params = None
name = 'TDT'
extensions = [ ]
mode = 'dir'
def __init__(self , dirname = None) :
"""
This class read a WinEDR wcp file.
**Arguments**
Arguments:
dirname: path of the TDT tank (a directory)
"""
BaseIO.__init__(self)
self.dirname = dirname
if self.dirname.endswith('/'):
self.dirname = self.dirname[:-1]
def read_block(self,
lazy = False,
cascade = True,
):
bl = Block()
tankname = os.path.basename(self.dirname)
bl.file_origin = tankname
if not cascade : return bl
for blockname in os.listdir(self.dirname):
if blockname == 'TempBlk': continue
subdir = os.path.join(self.dirname,blockname)
if not os.path.isdir(subdir): continue
seg = Segment(name = blockname)
bl.segments.append( seg)
global_t_start = None
# Step 1 : first loop for counting - tsq file
tsq = open(os.path.join(subdir, tankname+'_'+blockname+'.tsq'), 'rb')
hr = HeaderReader(tsq, TsqDescription)
allsig = { }
allspiketr = { }
allevent = { }
while 1:
h= hr.read_f()
if h==None:break
channel, code , evtype = h['channel'], h['code'], h['evtype']
if Types[evtype] == 'EVTYPE_UNKNOWN':
pass
elif Types[evtype] == 'EVTYPE_MARK' :
if global_t_start is None:
global_t_start = h['timestamp']
elif Types[evtype] == 'EVTYPE_SCALER' :
# TODO
pass
elif Types[evtype] == 'EVTYPE_STRON' or \
Types[evtype] == 'EVTYPE_STROFF':
# EVENTS
if code not in allevent:
allevent[code] = { }
if channel not in allevent[code]:
ea = EventArray(name = code , channel_index = channel)
# for counting:
ea.lazy_shape = 0
ea.maxlabelsize = 0
allevent[code][channel] = ea
allevent[code][channel].lazy_shape += 1
strobe, = struct.unpack('d' , struct.pack('q' , h['eventoffset']))
strobe = str(strobe)
if len(strobe)>= allevent[code][channel].maxlabelsize:
allevent[code][channel].maxlabelsize = len(strobe)
#~ ev = Event()
#~ ev.time = h['timestamp'] - global_t_start
#~ ev.name = code
#~ # it the strobe attribute masked with eventoffset
#~ strobe, = struct.unpack('d' , struct.pack('q' , h['eventoffset']))
#~ ev.label = str(strobe)
#~ seg._events.append( ev )
elif Types[evtype] == 'EVTYPE_SNIP' :
if code not in allspiketr:
allspiketr[code] = { }
if channel not in allspiketr[code]:
allspiketr[code][channel] = { }
if h['sortcode'] not in allspiketr[code][channel]:
sptr = SpikeTrain([ ], units = 's',
name = str(h['sortcode']),
#t_start = global_t_start,
t_start = 0.*pq.s,
t_stop = 0.*pq.s, # temporary
left_sweep = (h['size']-10.)/2./h['frequency'] * pq.s,
sampling_rate = h['frequency'] * pq.Hz,
)
#~ sptr.channel = channel
#sptr.annotations['channel_index'] = channel
sptr.annotate(channel_index = channel)
# for counting:
sptr.lazy_shape = 0
sptr.pos = 0
sptr.waveformsize = h['size']-10
#~ sptr.name = str(h['sortcode'])
#~ sptr.t_start = global_t_start
#~ sptr.sampling_rate = h['frequency']
#~ sptr.left_sweep = (h['size']-10.)/2./h['frequency']
#~ sptr.right_sweep = (h['size']-10.)/2./h['frequency']
#~ sptr.waveformsize = h['size']-10
allspiketr[code][channel][h['sortcode']] = sptr
allspiketr[code][channel][h['sortcode']].lazy_shape += 1
elif Types[evtype] == 'EVTYPE_STREAM':
if code not in allsig:
allsig[code] = { }
if channel not in allsig[code]:
#~ print 'code', code, 'channel', channel
anaSig = AnalogSignal([] * pq.V,
name=code,
sampling_rate=
h['frequency'] * pq.Hz,
t_start=(h['timestamp'] -
global_t_start) * pq.s,
channel_index=channel)
anaSig.lazy_dtype = np.dtype(DataFormats[h['dataformat']])
anaSig.pos = 0
# for counting:
anaSig.lazy_shape = 0
#~ anaSig.pos = 0
allsig[code][channel] = anaSig
allsig[code][channel].lazy_shape += (h['size']*4-40)/anaSig.dtype.itemsize
if not lazy:
# Step 2 : allocate memory
for code, v in iteritems(allsig):
for channel, anaSig in iteritems(v):
v[channel] = anaSig.duplicate_with_new_array(np.zeros((anaSig.lazy_shape) , dtype = anaSig.lazy_dtype)*pq.V )
v[channel].pos = 0
for code, v in iteritems(allevent):
for channel, ea in iteritems(v):
ea.times = np.empty( (ea.lazy_shape) ) * pq.s
ea.labels = np.empty( (ea.lazy_shape), dtype = 'S'+str(ea.maxlabelsize) )
ea.pos = 0
for code, v in iteritems(allspiketr):
for channel, allsorted in iteritems(v):
for sortcode, sptr in iteritems(allsorted):
new = SpikeTrain(np.zeros( (sptr.lazy_shape), dtype = 'f8' ) *pq.s ,
name = sptr.name,
t_start = sptr.t_start,
t_stop = sptr.t_stop,
left_sweep = sptr.left_sweep,
sampling_rate = sptr.sampling_rate,
waveforms = np.ones( (sptr.lazy_shape, 1, sptr.waveformsize) , dtype = 'f') * pq.mV ,
)
new.annotations.update(sptr.annotations)
new.pos = 0
new.waveformsize = sptr.waveformsize
allsorted[sortcode] = new
# Step 3 : searh sev (individual data files) or tev (common data file)
# sev is for version > 70
if os.path.exists(os.path.join(subdir, tankname+'_'+blockname+'.tev')):
tev = open(os.path.join(subdir, tankname+'_'+blockname+'.tev'), 'rb')
else:
tev = None
for code, v in iteritems(allsig):
for channel, anaSig in iteritems(v):
if PY3K:
signame = anaSig.name.decode('ascii')
else:
signame = anaSig.name
filename = os.path.join(subdir, tankname+'_'+blockname+'_'+signame+'_ch'+str(anaSig.channel_index)+'.sev')
if os.path.exists(filename):
anaSig.fid = open(filename, 'rb')
else:
anaSig.fid = tev
for code, v in iteritems(allspiketr):
for channel, allsorted in iteritems(v):
for sortcode, sptr in iteritems(allsorted):
sptr.fid = tev
# Step 4 : second loop for copyin chunk of data
tsq.seek(0)
while 1:
h= hr.read_f()
if h==None:break
channel, code , evtype = h['channel'], h['code'], h['evtype']
if Types[evtype] == 'EVTYPE_STREAM':
a = allsig[code][channel]
dt = a.dtype
s = int((h['size']*4-40)/dt.itemsize)
a.fid.seek(h['eventoffset'])
a[ a.pos:a.pos+s ] = np.fromstring( a.fid.read( s*dt.itemsize ), dtype = a.dtype)
a.pos += s
elif Types[evtype] == 'EVTYPE_STRON' or \
Types[evtype] == 'EVTYPE_STROFF':
ea = allevent[code][channel]
ea.times[ea.pos] = (h['timestamp'] - global_t_start) * pq.s
strobe, = struct.unpack('d' , struct.pack('q' , h['eventoffset']))
ea.labels[ea.pos] = str(strobe)
ea.pos += 1
elif Types[evtype] == 'EVTYPE_SNIP':
sptr = allspiketr[code][channel][h['sortcode']]
sptr.t_stop = (h['timestamp'] - global_t_start) * pq.s
sptr[sptr.pos] = (h['timestamp'] - global_t_start) * pq.s
sptr.waveforms[sptr.pos, 0, :] = np.fromstring( sptr.fid.read( sptr.waveformsize*4 ), dtype = 'f4') * pq.V
sptr.pos += 1
# Step 5 : populating segment
for code, v in iteritems(allsig):
for channel, anaSig in iteritems(v):
seg.analogsignals.append( anaSig )
for code, v in iteritems(allevent):
for channel, ea in iteritems(v):
seg.eventarrays.append( ea )
for code, v in iteritems(allspiketr):
for channel, allsorted in iteritems(v):
for sortcode, sptr in iteritems(allsorted):
seg.spiketrains.append( sptr )
create_many_to_one_relationship(bl)
return bl
TsqDescription = [
('size','i'),
('evtype','i'),
('code','4s'),
('channel','H'),
('sortcode','H'),
('timestamp','d'),
('eventoffset','q'),
('dataformat','i'),
('frequency','f'),
]
Types = {
0x0 : 'EVTYPE_UNKNOWN',
0x101:'EVTYPE_STRON',
0x102:'EVTYPE_STROFF',
0x201:'EVTYPE_SCALER',
0x8101:'EVTYPE_STREAM',
0x8201:'EVTYPE_SNIP',
0x8801: 'EVTYPE_MARK',
}
DataFormats = {
0 : np.float32,
1 : np.int32,
2 : np.int16,
3 : np.int8,
4 : np.float64,
#~ 5 : ''
}
class HeaderReader():
def __init__(self,fid ,description ):
self.fid = fid
self.description = description
def read_f(self, offset =None):
if offset is not None :
self.fid.seek(offset)
d = { }
for key, fmt in self.description :
buf = self.fid.read(struct.calcsize(fmt))
if len(buf) != struct.calcsize(fmt) : return None
val = struct.unpack(fmt , buf)
if len(val) == 1:
val = val[0]
else :
val = list(val)
#~ if 's' in fmt :
#~ val = val.replace('\x00','')
d[key] = val
return d
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