def run(self):
self.init_results()
# TODELAY: split apart collecting of features and training lda?
# however then you would not get progress output during training
# only at very end
for bp_nr, filt_band in enumerate(self.filterbands):
self.print_filter(bp_nr)
bandpassed_cnt = bandpass_cnt(self.cnt, filt_band[0], filt_band[1], filt_order=self.filt_order)
if self.standardize_filt_cnt:
bandpassed_cnt = exponential_standardize_cnt(bandpassed_cnt)
epo = segment_dat_fast(bandpassed_cnt, marker_def=self.marker_def, ival=self.segment_ival)
for fold_nr in xrange(len(self.folds)):
self.run_fold(epo, bp_nr, fold_nr)
def run(self):
self.init_results()
# TODELAY: split apart collecting of features and training lda?
# however then you would not get progress output during training
# only at very end
for bp_nr, filt_band in enumerate(self.filterbands):
self.print_filter(bp_nr)
bandpassed_cnt = bandpass_cnt(self.cnt,
filt_band[0],
filt_band[1],
filt_order=self.filt_order)
if self.standardize_filt_cnt:
bandpassed_cnt = exponential_standardize_cnt(bandpassed_cnt)
epo = segment_dat_fast(bandpassed_cnt,
marker_def=self.marker_def,
ival=self.segment_ival)
for fold_nr in xrange(len(self.folds)):
self.run_fold(epo, bp_nr, fold_nr)
def fill_filterbank_data(self, full_epo_data):
for filterband_i in xrange(len(self.filterbands)):
low_freq, high_freq= self.filterbands[filterband_i]
log.info("Filterband {:d} of {:d}, from {:5.2f} to {:5.2f}".format(
filterband_i + 1, len(self.filterbands), low_freq, high_freq))
bandpassed_cnt = bandpass_cnt(self.signal_processor.cnt,
low_freq, high_freq, filt_order=3)
epo = segment_dat_fast(bandpassed_cnt,
marker_def={'1 - Right Hand': [1], '2 - Left Hand': [2],
'3 - Rest': [3], '4 - Feet': [4]},
ival=self.signal_processor.segment_ival)
epo.data = np.float32(epo.data)
epo = select_epochs(epo, self.rejected_trials, invert=True)
full_epo_data[:,:,:,filterband_i] = epo.data
del epo.data
del bandpassed_cnt
self.filterband_axes = epo.axes + [self.filterbands.tolist()]
self.filterband_names = epo.names + ['filterband']
self.filterband_units = epo.units + ['Hz']
def load_and_preprocess_data(self):
# First create eog set for blink rejection
self.eog_set.load_signal_and_markers()
self.eog_set.segment_into_trials()
self.eog_set.remove_continuous_signal()
# Then create bandpassed set for variance rejection
# in case low or high cut hz is given
if self.low_cut_hz is not None and self.high_cut_hz is not None:
self.cnt = bandpass_cnt(self.cnt, self.low_cut_hz, self.high_cut_hz,
self.filt_order)
elif self.low_cut_hz is not None:
self.cnt = highpass_cnt(self.cnt, self.low_cut_hz, self.filt_order)
elif self.high_cut_hz is not None:
self.cnt = lowpass_cnt(self.cnt, self.high_cut_hz, self.filt_order)
else:
assert self.low_cut_hz is None and self.high_cut_hz is None
# Finally create trials
self.epo = segment_dat_fast(self.cnt, marker_def=self.marker_def,
ival=self.rejection_var_ival)
del self.cnt # No longer needed
def load_and_preprocess_data(self):
# First create eog set for blink rejection
self.eog_set.load_signal_and_markers()
self.eog_set.segment_into_trials()
self.eog_set.remove_continuous_signal()
# Then create bandpassed set for variance rejection
# in case low or high cut hz is given
if self.low_cut_hz is not None and self.high_cut_hz is not None:
self.cnt = bandpass_cnt(self.cnt, self.low_cut_hz,
self.high_cut_hz, self.filt_order)
elif self.low_cut_hz is not None:
self.cnt = highpass_cnt(self.cnt, self.low_cut_hz, self.filt_order)
elif self.high_cut_hz is not None:
self.cnt = lowpass_cnt(self.cnt, self.high_cut_hz, self.filt_order)
else:
assert self.low_cut_hz is None and self.high_cut_hz is None
# Finally create trials
self.epo = segment_dat_fast(self.cnt,
marker_def=self.marker_def,
ival=self.rejection_var_ival)
del self.cnt # No longer needed
