def test_psdestimator():
"""Test methods of PSDEstimator."""
raw = io.read_raw_fif(raw_fname)
events = read_events(event_name)
picks = pick_types(raw.info,
meg=True,
stim=False,
ecg=False,
eog=False,
exclude='bads')
picks = picks[1:13:3]
epochs = Epochs(raw,
events,
event_id,
tmin,
tmax,
picks=picks,
baseline=(None, 0),
preload=True)
epochs_data = epochs.get_data()
psd = PSDEstimator(2 * np.pi, 0, np.inf)
y = epochs.events[:, -1]
X = psd.fit_transform(epochs_data, y)
assert (X.shape[0] == epochs_data.shape[0])
assert_array_equal(psd.fit(epochs_data, y).transform(epochs_data), X)
# Test init exception
pytest.raises(ValueError, psd.fit, epochs, y)
pytest.raises(ValueError, psd.transform, epochs)
def test_psdestimator():
"""Test methods of PSDEstimator
"""
raw = io.Raw(raw_fname, preload=False)
events = read_events(event_name)
picks = pick_types(
raw.info, meg=True, stim=False, ecg=False, eog=False, exclude='bads')
picks = picks[1:13:3]
epochs = Epochs(
raw,
events,
event_id,
tmin,
tmax,
picks=picks,
baseline=(None, 0),
preload=True)
epochs_data = epochs.get_data()
psd = PSDEstimator(2 * np.pi, 0, np.inf)
y = epochs.events[:, -1]
X = psd.fit_transform(epochs_data, y)
assert_true(X.shape[0] == epochs_data.shape[0])
assert_array_equal(psd.fit(epochs_data, y).transform(epochs_data), X)
# Test init exception
assert_raises(ValueError, psd.fit, epochs, y)
assert_raises(ValueError, psd.transform, epochs, y)
# psde.transform = [channels x freqs]
psd = psde.transform(w)
return psd
if __name__ == '__main__':
sr = StreamReceiver(window_size=w_seconds,
amp_name=amp_name,
amp_serial=amp_serial)
sfreq = sr.sample_rate
psde = PSDEstimator(sfreq=sfreq,
fmin=fmin,
fmax=fmax,
bandwidth=None,
adaptive=False,
low_bias=True,
n_jobs=1,
normalization='length',
verbose=None)
ch_names = sr.get_channel_names()
fq_res = 1 / w_seconds
hz_list = []
f = fmin
while f < fmax:
hz_list.append(f)
f += fq_res
picks = [ch_names.index(ch) for ch in channel_picks]
psd = get_psd(sr, psde, picks).T # freq x ch
assert len(hz_list) == psd.shape[0], (len(hz_list), psd.shape[0])
cv2.namedWindow("img", cv2.WINDOW_AUTOSIZE)