def test_stockwell_api():
"""Test stockwell functions."""
raw = read_raw_fif(raw_fname)
event_id, tmin, tmax = 1, -0.2, 0.5
event_name = op.join(base_dir, 'test-eve.fif')
events = read_events(event_name)
epochs = Epochs(raw, events, # XXX pick 2 has epochs of zeros.
event_id, tmin, tmax, picks=[0, 1, 3])
for fmin, fmax in [(None, 50), (5, 50), (5, None)]:
with warnings.catch_warnings(record=True): # zero papdding
power, itc = tfr_stockwell(epochs, fmin=fmin, fmax=fmax,
return_itc=True)
if fmax is not None:
assert_true(power.freqs.max() <= fmax)
with warnings.catch_warnings(record=True): # padding
power_evoked = tfr_stockwell(epochs.average(), fmin=fmin,
fmax=fmax, return_itc=False)
# for multitaper these don't necessarily match, but they seem to
# for stockwell... if this fails, this maybe could be changed
# just to check the shape
assert_array_almost_equal(power_evoked.data, power.data)
assert_true(isinstance(power, AverageTFR))
assert_true(isinstance(itc, AverageTFR))
assert_equal(power.data.shape, itc.data.shape)
assert_true(itc.data.min() >= 0.0)
assert_true(itc.data.max() <= 1.0)
assert_true(np.log(power.data.max()) * 20 <= 0.0)
assert_true(np.log(power.data.max()) * 20 <= 0.0)
def test_stockwell_api():
"""Test stockwell functions."""
raw = read_raw_fif(raw_fname)
event_id, tmin, tmax = 1, -0.2, 0.5
event_name = op.join(base_dir, 'test-eve.fif')
events = read_events(event_name)
epochs = Epochs(raw, events, # XXX pick 2 has epochs of zeros.
event_id, tmin, tmax, picks=[0, 1, 3])
for fmin, fmax in [(None, 50), (5, 50), (5, None)]:
with warnings.catch_warnings(record=True): # zero papdding
power, itc = tfr_stockwell(epochs, fmin=fmin, fmax=fmax,
return_itc=True)
if fmax is not None:
assert (power.freqs.max() <= fmax)
with warnings.catch_warnings(record=True): # padding
power_evoked = tfr_stockwell(epochs.average(), fmin=fmin,
fmax=fmax, return_itc=False)
# for multitaper these don't necessarily match, but they seem to
# for stockwell... if this fails, this maybe could be changed
# just to check the shape
assert_array_almost_equal(power_evoked.data, power.data)
assert (isinstance(power, AverageTFR))
assert (isinstance(itc, AverageTFR))
assert_equal(power.data.shape, itc.data.shape)
assert (itc.data.min() >= 0.0)
assert (itc.data.max() <= 1.0)
assert (np.log(power.data.max()) * 20 <= 0.0)
assert (np.log(power.data.max()) * 20 <= 0.0)
def test_stockwell_api():
"""Test stockwell functions"""
epochs = Epochs(
raw,
events, # XXX pick 2 has epochs of zeros.
event_id,
tmin,
tmax,
picks=[0, 1, 3],
baseline=(None, 0))
for fmin, fmax in [(None, 50), (5, 50), (5, None)]:
power, itc = tfr_stockwell(epochs,
fmin=fmin,
fmax=fmax,
return_itc=True)
if fmax is not None:
assert_true(power.freqs.max() <= fmax)
power_evoked = tfr_stockwell(epochs.average(),
fmin=fmin,
fmax=fmax,
return_itc=False)
# for multitaper these don't necessarily match, but they seem to
# for stockwell... if this fails, this maybe could be changed
# just to check the shape
assert_array_almost_equal(power_evoked.data, power.data)
assert_true(isinstance(power, AverageTFR))
assert_true(isinstance(itc, AverageTFR))
assert_equal(power.data.shape, itc.data.shape)
assert_true(itc.data.min() >= 0.0)
assert_true(itc.data.max() <= 1.0)
assert_true(np.log(power.data.max()) * 20 <= 0.0)
assert_true(np.log(power.data.max()) * 20 <= 0.0)
def test_stockwell_ctf():
"""Test that Stockwell can be calculated on CTF data."""
raw = read_raw_fif(raw_ctf_fname)
raw.apply_gradient_compensation(3)
events = make_fixed_length_events(raw, duration=0.5)
evoked = Epochs(raw, events, tmin=-0.2, tmax=0.3, decim=10,
preload=True, verbose='error').average()
tfr_stockwell(evoked, verbose='error') # smoke test
def test_stockwell_ctf():
"""Test that Stockwell can be calculated on CTF data."""
raw = read_raw_fif(raw_ctf_fname)
raw.apply_gradient_compensation(3)
events = make_fixed_length_events(raw, duration=0.5)
evoked = Epochs(raw, events, tmin=-0.2, tmax=0.3, decim=10,
preload=True, verbose='error').average()
tfr_stockwell(evoked, verbose='error') # smoke test
def test_stockwell_api():
"""Test stockwell functions."""
raw = read_raw_fif(raw_fname)
event_id, tmin, tmax = 1, -0.2, 0.5
event_name = op.join(base_dir, 'test-eve.fif')
events = read_events(event_name)
epochs = Epochs(
raw,
events, # XXX pick 2 has epochs of zeros.
event_id,
tmin,
tmax,
picks=[0, 1, 3])
for fmin, fmax in [(None, 50), (5, 50), (5, None)]:
with pytest.warns(RuntimeWarning, match='padding'):
power, itc = tfr_stockwell(epochs,
fmin=fmin,
fmax=fmax,
return_itc=True)
if fmax is not None:
assert (power.freqs.max() <= fmax)
with pytest.warns(RuntimeWarning, match='padding'):
power_evoked = tfr_stockwell(epochs.average(),
fmin=fmin,
fmax=fmax,
return_itc=False)
# for multitaper these don't necessarily match, but they seem to
# for stockwell... if this fails, this maybe could be changed
# just to check the shape
assert_array_almost_equal(power_evoked.data, power.data)
assert (isinstance(power, AverageTFR))
assert (isinstance(itc, AverageTFR))
assert_equal(power.data.shape, itc.data.shape)
assert (itc.data.min() >= 0.0)
assert (itc.data.max() <= 1.0)
assert (np.log(power.data.max()) * 20 <= 0.0)
assert (np.log(power.data.max()) * 20 <= 0.0)
with pytest.raises(TypeError, match='ndarray'):
tfr_array_stockwell('foo', 1000.)
data = np.random.RandomState(0).randn(1, 1024)
with pytest.raises(ValueError, match='3D with shape'):
tfr_array_stockwell(data, 1000.)
data = data[np.newaxis]
power, itc, freqs = tfr_array_stockwell(data, 1000., return_itc=True)
assert_allclose(itc, np.ones_like(itc))
assert power.shape == (1, len(freqs), data.shape[-1])
assert_array_less(0, power)
def test_stockwell_api():
"""Test stockwell functions"""
epochs = Epochs(raw, events, # XXX pick 2 has epochs of zeros.
event_id, tmin, tmax, picks=[0, 1, 3], baseline=(None, 0))
for fmin, fmax in [(None, 50), (5, 50), (5, None)]:
power, itc = tfr_stockwell(epochs, fmin=fmin, fmax=fmax,
return_itc=True)
if fmax is not None:
assert_true(power.freqs.max() <= fmax)
power_evoked = tfr_stockwell(epochs.average(), fmin=fmin, fmax=fmax,
return_itc=False)
# for multitaper these don't necessarily match, but they seem to
# for stockwell... if this fails, this maybe could be changed
# just to check the shape
assert_array_almost_equal(power_evoked.data, power.data)
assert_true(isinstance(power, AverageTFR))
assert_true(isinstance(itc, AverageTFR))
assert_equal(power.data.shape, itc.data.shape)
assert_true(itc.data.min() >= 0.0)
assert_true(itc.data.max() <= 1.0)
assert_true(np.log(power.data.max()) * 20 <= 0.0)
assert_true(np.log(power.data.max()) * 20 <= 0.0)
def test_stockwell_api():
"""test stockwell functions"""
epochs = Epochs(raw, events, # XXX pick 2 has epochs of zeros.
event_id, tmin, tmax, picks=[0, 1, 3], baseline=(None, 0))
for fmin, fmax in [(None, 50), (5, 50), (5, None)]:
power, itc = tfr_stockwell(epochs, fmin=fmin, fmax=fmax,
return_itc=True)
if fmax is not None:
assert_true(power.freqs.max() <= fmax)
assert_true(isinstance(power, AverageTFR))
assert_true(isinstance(itc, AverageTFR))
assert_equals(power.data.shape, itc.data.shape)
assert_true(itc.data.min() >= 0.0)
assert_true(itc.data.max() <= 1.0)
assert_true(np.log(power.data.max()) * 20 <= 0.0)
assert_true(np.log(power.data.max()) * 20 <= 0.0)
