def test_fieldtrip_rtepochs(free_tcp_port, tmpdir):
"""Test FieldTrip RtEpochs."""
raw_tmax = 7
raw = read_raw_fif(raw_fname, preload=True)
raw.crop(tmin=0, tmax=raw_tmax)
events_offline = find_events(raw, stim_channel='STI 014')
event_id = list(np.unique(events_offline[:, 2]))
tmin, tmax = -0.2, 0.5
epochs_offline = Epochs(raw, events_offline, event_id=event_id,
tmin=tmin, tmax=tmax)
epochs_offline.drop_bad()
isi_max = (np.max(np.diff(epochs_offline.events[:, 0])) /
raw.info['sfreq']) + 1.0
neuromag2ft_fname = op.realpath(op.join(os.environ['NEUROMAG2FT_ROOT'],
'neuromag2ft'))
# Works with neuromag2ft-3.0.2
cmd = (neuromag2ft_fname, '--file', raw_fname, '--speed', '8.0',
'--bufport', str(free_tcp_port))
with running_subprocess(cmd, after='terminate', verbose=False):
data_rt = None
events_ids_rt = None
with pytest.warns(RuntimeWarning, match='Trying to guess it'):
with FieldTripClient(host='localhost', port=free_tcp_port,
tmax=raw_tmax, wait_max=2) as rt_client:
# get measurement info guessed by MNE-Python
raw_info = rt_client.get_measurement_info()
assert ([ch['ch_name'] for ch in raw_info['chs']] ==
[ch['ch_name'] for ch in raw.info['chs']])
# create the real-time epochs object
epochs_rt = RtEpochs(rt_client, event_id, tmin, tmax,
stim_channel='STI 014', isi_max=isi_max)
epochs_rt.start()
time.sleep(0.5)
for ev_num, ev in enumerate(epochs_rt.iter_evoked()):
if ev_num == 0:
data_rt = ev.data[None, :, :]
events_ids_rt = int(
ev.comment) # comment attribute contains event_id
else:
data_rt = np.concatenate(
(data_rt, ev.data[None, :, :]), axis=0)
events_ids_rt = np.append(events_ids_rt,
int(ev.comment))
_call_base_epochs_public_api(epochs_rt, tmpdir)
epochs_rt.stop(stop_receive_thread=True)
assert_array_equal(events_ids_rt, epochs_rt.events[:, 2])
assert_array_equal(data_rt, epochs_rt.get_data())
assert len(epochs_rt) == len(epochs_offline)
assert_array_equal(events_ids_rt, epochs_offline.events[:, 2])
assert_allclose(epochs_rt.get_data(), epochs_offline.get_data(),
rtol=1.e-5, atol=1.e-8) # defaults of np.isclose
def test_fieldtrip_client(free_tcp_port):
"""Test fieldtrip_client."""
neuromag2ft_fname = op.realpath(op.join(os.environ['NEUROMAG2FT_ROOT'],
'neuromag2ft'))
# Works with neuromag2ft-3.0.2
cmd = (neuromag2ft_fname, '--file', raw_fname, '--speed', '8.0',
'--bufport', str(free_tcp_port))
time.sleep(0.5)
with running_subprocess(cmd, after='terminate', verbose=False):
# Start the FieldTrip buffer
with pytest.warns(RuntimeWarning):
with FieldTripClient(host='localhost', port=free_tcp_port,
tmax=5, wait_max=2) as rt_client:
tmin_samp1 = rt_client.tmin_samp
time.sleep(1) # Pause measurement
# Start the FieldTrip buffer again
with pytest.warns(RuntimeWarning):
with FieldTripClient(host='localhost', port=free_tcp_port,
tmax=5, wait_max=2) as rt_client:
raw_info = rt_client.get_measurement_info()
tmin_samp2 = rt_client.tmin_samp
picks = pick_types(raw_info, meg='grad', eeg=False,
stim=False, eog=False)
epoch = rt_client.get_data_as_epoch(n_samples=5, picks=picks)
n_channels, n_samples = epoch.get_data().shape[1:]
epoch2 = rt_client.get_data_as_epoch(n_samples=5, picks=picks)
n_channels2, n_samples2 = epoch2.get_data().shape[1:]
# case of picks=None
epoch = rt_client.get_data_as_epoch(n_samples=5)
assert tmin_samp2 > tmin_samp1
assert n_samples == 5
assert n_samples2 == 5
assert n_channels == len(picks)
assert n_channels2 == len(picks)
rt_client = MockRtClient(raw)
# Constructing the pipeline for classification
# don't highpass filter because of short signal length of epochs
scaler = preprocessing.StandardScaler()
vectorizer = Vectorizer()
clf = SVC(C=1, kernel='linear')
concat_classifier = Pipeline([('vector', vectorizer), ('scaler', scaler),
('svm', clf)])
ev_list = list(rng.randint(3, 5, n_start)) # some random starting events
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],
'sample_audvis_raw.fif'))
# select the left-auditory condition
event_id, tmin, tmax = 1, -0.2, 0.5
# user must provide list of bad channels because
# FieldTrip header object does not provide that
bads = ['MEG 2443', 'EEG 053']
_, ax = plt.subplots(2, 1, figsize=(8, 8)) # create subplots
speedup = 10
command = ["neuromag2ft", "--file",
"{}/MEG/sample/sample_audvis_raw.fif".format(data_path),
"--speed", str(speedup)]
with running_subprocess(command, after='kill',
stdout=subprocess.PIPE, stderr=subprocess.PIPE):
with FieldTripClient(host='localhost', port=1972,
tmax=30, wait_max=5, info=info) as rt_client:
# get measurement info guessed by MNE-Python
raw_info = rt_client.get_measurement_info()
# select gradiometers
picks = mne.pick_types(raw_info, meg='grad', eeg=False, eog=True,
stim=True, exclude=bads)
# create the real-time epochs object and start acquisition
rt_epochs = RtEpochs(rt_client, event_id, tmin, tmax,
stim_channel='STI 014', picks=picks,
reject=dict(grad=4000e-13, eog=150e-6),
decim=1, isi_max=2.0, proj=None)