def classify_Spindles(self):
f=avg_q.avg_q_file(self.filteredfile,'BrainVision')
self.Spindles=[] # Tuples (start_s,duration_ms,Spindle_info dict)
for collapsedchannel,(start,end) in self.Spindleranges:
duration_ms=(end-start)/self.sfreq*1000
# Count the zero crossings
detector=avg_q.Detector.Detector(self.avg_q_instance)
epochsource=avg_q.Epochsource(f,'100ms','%gms' % (duration_ms+200)) # Add 100ms on both ends
epochsource.set_trigpoints('%gs' % (start/self.sfreq))
detector.add_Epochsource(epochsource)
detector.add_transform('''
write_crossings ALL 0 stdout
''')
crossings=detector.detect()
trigger_dict=avg_q.Detector.get_trigger_dict(crossings)
Spindle_info={} # Will contain lists [freq_Hz,amplitude]
for channel,cr in trigger_dict.items():
period_s=2*(cr[-1][0]-cr[0][0])/(len(cr)-1)/detector.sfreq
Spindle_info[channel]=[1.0/period_s]
script=avg_q.Script(self.avg_q_instance)
script.add_Epochsource(epochsource)
script.add_transform('''
calc abs
trim -a 0 0
write_generic -P -N stdout string
''')
for line in script.runrdr():
channel,amp=line.split('\t')
Spindle_info[channel].append(float(amp))
self.Spindles.append((start/self.sfreq,duration_ms,Spindle_info))
def average_ECG(self):
'''Average ECG events with rejection.
Returns the number of accepted ECGs.'''
if os.path.exists(self.avgECGfile):
ascfile=avg_q.avg_q_file(self.avgECGfile)
return self.avg_q_instance.get_description(ascfile,'nrofaverages')
self.detect_ECG()
epochsource=avg_q.Epochsource(self.Epochsource_list[0].infile,self.ECG_beforetrig, self.ECG_aftertrig)
epochsource.set_trigpoints(self.ECGtriggers)
script=avg_q.Script(self.avg_q_instance)
script.add_Epochsource(epochsource)
if self.protect_channels is not None and len(self.protect_channels)>0:
script.add_transform('''
scale_by -n ?%(protect_channels)s 0
''' % {
'protect_channels': channel_list2arg(self.protect_channels),
})
script.add_transform('''
baseline_subtract
reject_bandwidth %(reject_bandwidth)f
''' % {
'reject_bandwidth': self.ECG_reject_bandwidth,
})
script.set_collect('average')
script.add_postprocess('''
query nrofaverages stdout
writeasc -b %(avgECGfile)s
''' % {
'avgECGfile': self.avgECGfile})
rdr=script.runrdr()
nrofaverages=0
for line in rdr:
nrofaverages=int(line)
return nrofaverages
def sessionaverage_HEOG(self, HEOGfiles):
'''Average the HEOG files. The output file self.sessionaverage_HEOGfile is default_sessionaverage_HEOGfile
in the current directory, unless set differently by the caller.
Returns the total number of averages.'''
if not self.sessionaverage_HEOGfile:
self.sessionaverage_HEOGfile = os.path.join(
self.indir, default_sessionaverage_HEOGfile)
if os.path.exists(self.sessionaverage_HEOGfile):
ascfile = avg_q.avg_q_file(self.sessionaverage_HEOGfile)
return self.avg_q_instance.get_description(ascfile, 'nrofaverages')
nrofaverages = 0
for fromepoch in range(1, 3):
readasc = ''
for HEOGfile in HEOGfiles:
if os.path.exists(HEOGfile):
readasc += 'readasc -f %d -e 1 %s\n' % (fromepoch,
HEOGfile)
if readasc != '':
self.avg_q_instance.write(readasc + '''
average -W
Post:
query nrofaverages stdout
writeasc -a -b %s
-
''' % self.sessionaverage_HEOGfile)
rdr = self.avg_q_instance.runrdr()
for line in rdr:
nrofaverages += int(line)
return nrofaverages
def sessionaverage_ECG(self,ECGfiles):
'''Average the ECG files. The output file self.sessionaverage_ECGfile is default_sessionaverage_ECGfile
in the current directory, unless set differently by the caller.
Returns the total number of averages.'''
if not self.sessionaverage_ECGfile:
self.sessionaverage_ECGfile=os.path.join(self.indir,default_sessionaverage_ECGfile)
if os.path.exists(self.sessionaverage_ECGfile):
ascfile=avg_q.avg_q_file(self.sessionaverage_ECGfile)
return self.avg_q_instance.get_description(ascfile,'nrofaverages')
readasc=''
for ECGfile in ECGfiles:
if os.path.exists(ECGfile):
readasc+='readasc %s\n' % ECGfile
nrofaverages=0
if readasc!='':
self.avg_q_instance.write(readasc+'''
average -W
Post:
query nrofaverages stdout
writeasc -b %s
-
''' % self.sessionaverage_ECGfile)
rdr=self.avg_q_instance.runrdr()
for line in rdr:
nrofaverages=int(line)
return nrofaverages
def classify_Spindles(self):
f = avg_q.avg_q_file(self.filteredfile, 'BrainVision')
self.Spindles = [] # Tuples (start_s,duration_ms,Spindle_info dict)
for collapsedchannel, (start, end) in self.Spindleranges:
duration_ms = (end - start) / self.sfreq * 1000
# Count the zero crossings
detector = avg_q.Detector.Detector(self.avg_q_instance)
epochsource = avg_q.Epochsource(
f, '100ms',
'%gms' % (duration_ms + 200)) # Add 100ms on both ends
epochsource.set_trigpoints('%gs' % (start / self.sfreq))
detector.add_Epochsource(epochsource)
detector.add_transform('''
write_crossings ALL 0 stdout
''')
crossings = detector.detect()
trigger_dict = avg_q.Detector.get_trigger_dict(crossings)
Spindle_info = {} # Will contain lists [freq_Hz,amplitude]
for channel, cr in trigger_dict.items():
period_s = 2 * (cr[-1][0] - cr[0][0]) / (len(cr) -
1) / detector.sfreq
Spindle_info[channel] = [1.0 / period_s]
script = avg_q.Script(self.avg_q_instance)
script.add_Epochsource(epochsource)
script.add_transform('''
calc abs
trim -a 0 0
write_generic -P -N stdout string
''')
for line in script.runrdr():
channel, amp = line.split('\t')
Spindle_info[channel].append(float(amp))
self.Spindles.append(
(start / self.sfreq, duration_ms, Spindle_info))
def sessionaverage_HEOG(self,HEOGfiles):
'''Average the HEOG files. The output file self.sessionaverage_HEOGfile is default_sessionaverage_HEOGfile
in the current directory, unless set differently by the caller.
Returns the total number of averages.'''
if not self.sessionaverage_HEOGfile:
self.sessionaverage_HEOGfile=os.path.join(self.indir,default_sessionaverage_HEOGfile)
if os.path.exists(self.sessionaverage_HEOGfile):
ascfile=avg_q.avg_q_file(self.sessionaverage_HEOGfile)
return self.avg_q_instance.get_description(ascfile,'nrofaverages')
nrofaverages=0
for fromepoch in range(1,3):
readasc=''
for HEOGfile in HEOGfiles:
if os.path.exists(HEOGfile):
readasc+='readasc -f %d -e 1 %s\n' % (fromepoch,HEOGfile)
if readasc!='':
self.avg_q_instance.write(readasc+'''
average -W
Post:
query nrofaverages stdout
writeasc -a -b %s
-
''' % self.sessionaverage_HEOGfile)
rdr=self.avg_q_instance.runrdr()
for line in rdr:
nrofaverages+=int(line)
return nrofaverages
def average_EOG(self):
'''Average EOG events with strict checks for duration and surroundings.
Returns the number of accepted EOGs.'''
if os.path.exists(self.avgEOGfile):
ascfile = avg_q.avg_q_file(self.avgEOGfile)
return self.avg_q_instance.get_description(ascfile, 'nrofaverages')
self.detect_VEOG()
epochsource = avg_q.Epochsource(self.Epochsource_list[0].infile,
self.VEOG_beforetrig,
self.VEOG_aftertrig,
offset=self.VEOG_offset)
epochsource.set_trigpoints(self.VEOGtriggers)
script = avg_q.Script(self.avg_q_instance)
script.add_Epochsource(epochsource)
if self.protect_channels is not None and len(
self.protect_channels) > 0:
script.add_transform('''
scale_by -n ?%(protect_channels)s 0
''' % {
'protect_channels':
channel_list2arg(self.protect_channels),
})
if self.preprocess:
script.add_transform(self.preprocess)
# Note that we require the VEOG signal to be "close to baseline" before and after the maximum
script.add_transform(
'''
baseline_subtract
push
%(get_VEOG_script)s
trim -x 0 100 400 500
calc abs
reject_bandwidth -m %(max_VEOG_amp_outside_window)f
pop
''' % {
'get_VEOG_script': self.get_VEOG_script,
'max_VEOG_amp_outside_window': self.VEOG_minamp
})
script.set_collect('average')
script.add_postprocess('''
query nrofaverages stdout
writeasc -b %(avgEOGfile)s
''' % {'avgEOGfile': self.avgEOGfile})
rdr = script.runrdr()
nrofaverages = 0
for line in rdr:
nrofaverages = int(line)
return nrofaverages
def average_EOG(self):
'''Average EOG events with strict checks for duration and surroundings.
Returns the number of accepted EOGs.'''
if os.path.exists(self.avgEOGfile):
ascfile=avg_q.avg_q_file(self.avgEOGfile)
return self.avg_q_instance.get_description(ascfile,'nrofaverages')
self.detect_VEOG()
epochsource=avg_q.Epochsource(self.Epochsource_list[0].infile,self.VEOG_beforetrig, self.VEOG_aftertrig, offset=self.VEOG_offset)
epochsource.set_trigpoints(self.VEOGtriggers)
script=avg_q.Script(self.avg_q_instance)
script.add_Epochsource(epochsource)
if self.protect_channels is not None and len(self.protect_channels)>0:
script.add_transform('''
scale_by -n ?%(protect_channels)s 0
''' % {
'protect_channels': channel_list2arg(self.protect_channels),
})
if self.preprocess:
script.add_transform(self.preprocess)
# Note that we require the VEOG signal to be "close to baseline" before and after the maximum
script.add_transform('''
baseline_subtract
push
%(get_VEOG_script)s
trim -x 0 100 400 500
calc abs
reject_bandwidth -m %(max_VEOG_amp_outside_window)f
pop
''' % {
'get_VEOG_script': self.get_VEOG_script,
'max_VEOG_amp_outside_window': self.VEOG_minamp
})
script.set_collect('average')
script.add_postprocess('''
query nrofaverages stdout
writeasc -b %(avgEOGfile)s
''' % {
'avgEOGfile': self.avgEOGfile})
rdr=script.runrdr()
nrofaverages=0
for line in rdr:
nrofaverages=int(line)
return nrofaverages
def __init__(self, epochs=None):
self.epochs = epochs
self.branch = []
self.infile = avg_q.avg_q_file()
# Only used to transfer trigpoints to avg_q.Epochsource
self.trigpoints = None
def __init__(self, epochs=None): self.epochs=epochs self.branch=[] self.infile=avg_q.avg_q_file() # Only used to transfer trigpoints to avg_q.Epochsource self.trigpoints=None
