def freqfilt_eeg(fn_in,fn_out,btype="lp",fl=None,fh=None,border=3,windowed=False):
eeg = eegpy.open_eeg(fn_in)
out = eegpy.F32(fn_out,"w+",shape=eeg.shape,cNames=eeg.channel_names,Fs=eeg.Fs)
if btype == "lp":
if not windowed:
out[:,:] = filtfilt_low(fl,eeg[:,:],Fs=eeg.Fs,border=border)
else:
for i in range(0,out.num_datapoints,100000):
out[i:min(i+100000,out.num_datapoints),:] = filtfilt_low(fl,eeg[i:min(i+100000,out.num_datapoints),:],Fs=eeg.Fs,border=border)
elif btype == "hp":
#for i_c in range(eeg.num_channels):
if not windowed:
out[:,:] = filtfilt_high(fh,eeg[:,:],Fs=eeg.Fs,border=border)
else:
for i in range(0,out.num_datapoints,100000):
out[i:min(i+100000,out.num_datapoints),:] = filtfilt_high(fh,eeg[i:min(i+100000,out.num_datapoints),:],Fs=eeg.Fs,border=border)
elif btype == "bp":
if not windowed:
out[:,:] = filtfilt_band(fl,fh,eeg[:,:],Fs=eeg.Fs,border=border)
else:
for i in range(0,out.num_datapoints,100000):
out[i:min(i+100000,out.num_datapoints),:] = filtfilt_band(fl,fh,eeg[i:min(i+100000,out.num_datapoints),:],Fs=eeg.Fs,border=border)
elif btype == "bs":
if not windowed:
out[:,:] = filtfilt_bandstop(fl,fh,eeg[:,:],Fs=eeg.Fs,border=border)
else:
for i in range(0,out.num_datapoints,100000):
out[i:min(i+100000,out.num_datapoints),:] = filtfilt_bandstop(fl,fh,eeg[i:min(i+100000,out.num_datapoints),:],Fs=eeg.Fs,border=border)
def calculate(self, cond_name=None):
"""After doing the setup, this method actually calculates the ERPs.
If no argument is supplied, then the data for all conditions are calculated."""
if cond_name == None:
cnames = self._times.keys()
else:
cnames = [cond_name]
#self.check_for_artifacts()
for c in cnames:
logger.debug("Condition %s" % c)
#assert self._datadict.has_key(c) and self._is_calculated.has_key(c), "Key in dictionary missing!"
f = self.eeg
#TODO: check timepoints
ndp = f.numDatapoints
tps_ok = True
logger.debug("datapoints: %s, input: %s" % (ndp, str(f)))
for t in self._times[c]:
#if debug:
# print "t = ", t
if t+self._start_end[0]<0 or t+self._start_end[1]>ndp:
tps_ok=False
break
if tps_ok:
#getData
data = f.get_data_for_events(self._times[c],self._start_end)
if self._lp_freq!=None:
data = filtfilt_low(self._lp_freq,data,Fs=f.Fs)
#Baseline-Korrektur
data -= self._get_baseline_data(data).mean(axis=0)
#calculate average
self._datadict[c] = data[:,:,~self._is_artifact[c]].mean(axis=2)
#print "Shape datadict:", self._datadict[c].shape
self._is_calculated[c] = True
else:
raise ValueError("Some problem with the timepoints occured." +
"Number of datapoints: %i, Max. timepoint: %i" %(ndp, max(self._times[c])))
def final_lowpass(self, f=90):
"""Performs simple lowpass, removing sharp edges"""
eeg = self.eeg
eeg[:] = filtfilt_low(f,eeg[:],Fs=eeg.Fs)
def final_lowpass(self, f=None):
"""Performs simple lowpass, removing sharp edges"""
if f == None:
f = self._f_flp
eeg = self._data
eeg[:] = filtfilt_low(f,eeg[:],Fs=self._Fs)
