def test_get_event_data():
"""Test emulation of realtime data stream."""
raw = read_raw_fif(raw_fname, preload=True, verbose=False)
picks = pick_types(raw.info,
meg='grad',
eeg=False,
eog=True,
stim=True,
exclude=raw.info['bads'])
event_id, tmin, tmax = 2, -0.1, 0.3
epochs = Epochs(raw,
events,
event_id=event_id,
tmin=tmin,
tmax=tmax,
picks=picks,
baseline=None,
preload=True,
proj=False)
data = epochs.get_data()[0, :, :]
rt_client = MockRtClient(raw)
rt_data = rt_client.get_event_data(event_id=event_id,
tmin=tmin,
tmax=tmax,
picks=picks,
stim_channel='STI 014')
assert_array_equal(rt_data, data)
def test_get_event_data():
"""Test emulation of realtime data stream."""
event_id, tmin, tmax = 2, -0.1, 0.3
epochs = Epochs(
raw, events, event_id=event_id, tmin=tmin, tmax=tmax, picks=picks, baseline=None, preload=True, proj=False
)
data = epochs.get_data()[0, :, :]
rt_client = MockRtClient(raw)
rt_data = rt_client.get_event_data(event_id=event_id, tmin=tmin, tmax=tmax, picks=picks, stim_channel="STI 014")
assert_array_equal(rt_data, data)
def test_get_event_data():
"""Test emulation of realtime data stream."""
raw = mne.io.Raw(raw_fname, preload=True, verbose=False)
picks = mne.pick_types(raw.info, meg="grad", eeg=False, eog=True, stim=True, exclude=raw.info["bads"])
event_id, tmin, tmax = 2, -0.1, 0.3
epochs = Epochs(
raw, events, event_id=event_id, tmin=tmin, tmax=tmax, picks=picks, baseline=None, preload=True, proj=False
)
data = epochs.get_data()[0, :, :]
rt_client = MockRtClient(raw)
rt_data = rt_client.get_event_data(event_id=event_id, tmin=tmin, tmax=tmax, picks=picks, stim_channel="STI 014")
assert_array_equal(rt_data, data)
def test_get_event_data():
"""Test emulation of realtime data stream."""
event_id, tmin, tmax = 2, -0.1, 0.3
epochs = Epochs(raw,
events,
event_id=event_id,
tmin=tmin,
tmax=tmax,
picks=picks,
baseline=None,
preload=True,
proj=False)
data = epochs.get_data()[0, :, :]
rt_client = MockRtClient(raw)
rt_data = rt_client.get_event_data(event_id=event_id,
tmin=tmin,
tmax=tmax,
picks=picks,
stim_channel='STI 014')
assert_array_equal(rt_data, data)
score_lv, score_rv, score_x = [], [], []
command = [sys.executable, 'rt_feedback_client.py']
with running_subprocess(command,
after='kill',
stdout=subprocess.PIPE,
stderr=subprocess.PIPE):
for ii in range(n_trials):
# Tell the stim_client about the next stimuli
stim_server.add_trigger(ev_list[ii])
# Collecting data
if ii == 0:
X = rt_client.get_event_data(event_id=ev_list[ii],
tmin=-0.2,
tmax=0.5,
picks=picks,
stim_channel='STI 014')[None, ...]
y = ev_list[ii]
else:
X_temp = rt_client.get_event_data(event_id=ev_list[ii],
tmin=-0.2,
tmax=0.5,
picks=picks,
stim_channel='STI 014')
X_temp = X_temp[np.newaxis]
X = np.concatenate((X, X_temp), axis=0)
time.sleep(isi) # simulating the isi
y = np.append(y, ev_list[ii])
# Start decoding after collecting sufficient data
# Just some initially decided events to be simulated
# Rest will decided on the fly
ev_list = [4, 3, 4, 3, 4, 3, 4, 3, 4, 3, 4]
score_c1, score_c2, score_x = [], [], []
for ii in range(50):
# Tell the stim_client about the next stimuli
stim_server.add_trigger(ev_list[ii])
# Collecting data
if ii == 0:
X = rt_client.get_event_data(
event_id=ev_list[ii], tmin=-0.2, tmax=0.5, picks=picks, stim_channel="STI 014"
)[None, ...]
y = ev_list[ii]
else:
X_temp = rt_client.get_event_data(
event_id=ev_list[ii], tmin=-0.2, tmax=0.5, picks=picks, stim_channel="STI 014"
)
X_temp = X_temp[np.newaxis, ...]
X = np.concatenate((X, X_temp), axis=0)
time.sleep(1) # simulating the isi
y = np.append(y, ev_list[ii])
# Start decoding after collecting sufficient data
if ii >= 10:
