def _convert_to_raw(self, data, s):
fs = 500
ch_names = [
'Fp1', 'F5', 'F3', 'F1', 'Fz', 'FC5', 'FC3', 'FC1', 'FCz', 'C5',
'C3', 'C1', 'Cz', 'CP5', 'CP3', 'CP1', 'CPz', 'P5', 'P3', 'P1',
'Pz'
]
ch_types = ['eeg'] * 21
info = create_info(ch_names, fs, ch_types)
info['description'] = 'PGHealthy'
x = data['Signals'] * 1e-6
raw = RawArray(x, info)
epoch_start = np.array(data['Epoch_start']).T
N = len(epoch_start)
events = np.c_[epoch_start, np.zeros(N), np.ones(N) * (s + 1)]
events = events.astype(np.int)
raw.set_montage('standard_1005')
mapping = {v: k for k, v in self.event_id.items()}
onsets = events[:, 0] / raw.info['sfreq']
durations = np.zeros_like(onsets) # assumes instantaneous events
descriptions = [mapping[ev_id] for ev_id in events[:, 2]]
annot_from_events = Annotations(onset=onsets,
duration=durations,
description=descriptions)
raw.notch_filter(50, verbose=False)
return raw.set_annotations(annot_from_events)
trange=T_RANGE,
l_freq=LO_FREQ,
h_freq=HI_FREQ)
from mne.io import RawArray
from mne import create_info
from integration import stream_channels
raw = RawArray(data=debug_data[0],
info=create_info(stream_channels, 500, 'eeg'))
raw = raw.filter(LO_FREQ,
HI_FREQ,
method='fir',
fir_design='firwin',
phase='zero')
raw = raw.notch_filter(50)
# raw = raw.drop_channels([ch for ch in raw.ch_names if ch not in GOODS])
# print(raw.ch_names)
# raw = raw.reorder_channels(sorted(raw.ch_names))
# print(raw.ch_names)
raw = raw.crop(tmin=11.)
raw = raw.resample(125)
# raw = raw.reorder_channels(sorted(raw.ch_names))
# print(raw.ch_names)
realtime = raw.get_data(picks=sorted(GOODS)) * 1000
raw = raw.reorder_channels(sorted(raw.ch_names))
# print(raw.ch_names)
ordered = raw.get_data(picks=GOODS) * 1000
# print(realtime[0])
