def test_source_psd_epochs():
"""Test multi-taper source PSD computation in label from epochs"""
raw = fiff.Raw(fname_data)
inverse_operator = read_inverse_operator(fname_inv)
label = read_label(fname_label)
event_id, tmin, tmax = 1, -0.2, 0.5
lambda2, method = 1. / 9., 'dSPM'
bandwidth = 8.
fmin, fmax = 0, 100
picks = fiff.pick_types(raw.info, meg=True, eeg=False, stim=True,
ecg=True, eog=True, include=['STI 014'],
exclude='bads')
reject = dict(grad=4000e-13, mag=4e-12, eog=150e-6)
events = find_events(raw)
epochs = Epochs(raw, events, event_id, tmin, tmax, picks=picks,
baseline=(None, 0), reject=reject)
# only look at one epoch
epochs.drop_bad_epochs()
one_epochs = epochs[:1]
# return list
stc_psd = compute_source_psd_epochs(one_epochs, inverse_operator,
lambda2=lambda2, method=method,
pick_normal=True, label=label,
bandwidth=bandwidth,
fmin=fmin, fmax=fmax)[0]
# return generator
stcs = compute_source_psd_epochs(one_epochs, inverse_operator,
lambda2=lambda2, method=method,
pick_normal=True, label=label,
bandwidth=bandwidth,
fmin=fmin, fmax=fmax,
return_generator=True)
for stc in stcs:
stc_psd_gen = stc
assert_array_almost_equal(stc_psd.data, stc_psd_gen.data)
# compare with direct computation
stc = apply_inverse_epochs(one_epochs, inverse_operator,
lambda2=lambda2, method=method,
pick_normal=True, label=label)[0]
sfreq = epochs.info['sfreq']
psd, freqs = multitaper_psd(stc.data, sfreq=sfreq, bandwidth=bandwidth,
fmin=fmin, fmax=fmax)
assert_array_almost_equal(psd, stc_psd.data)
assert_array_almost_equal(freqs, stc_psd.times)
def test_multitaper_psd():
""" Test multi-taper PSD computation """
n_times = 1000
x = np.random.randn(5, n_times)
sfreq = 500
for adaptive, n_jobs in zip((False, True, True), (1, 1, 2)):
psd, freqs = multitaper_psd(x, sfreq, adaptive=adaptive, n_jobs=n_jobs)
freqs_ni, psd_ni, _ = ni.algorithms.spectral.multi_taper_psd(x, sfreq,
adaptive=adaptive, jackknife=False)
# for some reason nitime returns n_times + 1 frequency points
# causing the value at 0 to be different
assert_array_almost_equal(psd[:, 1:], psd_ni[:, 1:-1], decimal=3)
assert_array_almost_equal(freqs, freqs_ni[:-1])
def test_multitaper_psd():
""" Test multi-taper PSD computation """
n_times = 1000
x = np.random.randn(5, n_times)
sfreq = 500
for adaptive, n_jobs in zip((False, True, True), (1, 1, 2)):
psd, freqs = multitaper_psd(x, sfreq, adaptive=adaptive, n_jobs=n_jobs)
freqs_ni, psd_ni, _ = ni.algorithms.spectral.multi_taper_psd(
x, sfreq, adaptive=adaptive, jackknife=False)
# for some reason nitime returns n_times + 1 frequency points
# causing the value at 0 to be different
assert_array_almost_equal(psd[:, 1:], psd_ni[:, 1:-1], decimal=3)
assert_array_almost_equal(freqs, freqs_ni[:-1])
def test_multitaper_psd():
""" Test multi-taper PSD computation """
import nitime as ni
n_times = 1000
x = np.random.randn(5, n_times)
sfreq = 500
assert_raises(ValueError, multitaper_psd, x, sfreq, normalization='foo')
ni_5 = (LooseVersion(ni.__version__) >= LooseVersion('0.5'))
norm = 'full' if ni_5 else 'length'
for adaptive, n_jobs in zip((False, True, True), (1, 1, 2)):
psd, freqs = multitaper_psd(x, sfreq, adaptive=adaptive, n_jobs=n_jobs,
normalization=norm)
freqs_ni, psd_ni, _ = ni.algorithms.spectral.multi_taper_psd(
x, sfreq, adaptive=adaptive, jackknife=False)
# for some reason nitime returns n_times + 1 frequency points
# causing the value at 0 to be different
assert_array_almost_equal(psd[:, 1:], psd_ni[:, 1:-1], decimal=3)
assert_array_almost_equal(freqs, freqs_ni[:-1])
def test_multitaper_psd():
""" Test multi-taper PSD computation """
import nitime as ni
n_times = 1000
x = np.random.randn(5, n_times)
sfreq = 500
assert_raises(ValueError, multitaper_psd, x, sfreq, normalization='foo')
ni_5 = (LooseVersion(ni.__version__) >= LooseVersion('0.5'))
norm = 'full' if ni_5 else 'length'
for adaptive, n_jobs in zip((False, True, True), (1, 1, 2)):
psd, freqs = multitaper_psd(x,
sfreq,
adaptive=adaptive,
n_jobs=n_jobs,
normalization=norm)
freqs_ni, psd_ni, _ = ni.algorithms.spectral.multi_taper_psd(
x, sfreq, adaptive=adaptive, jackknife=False)
# for some reason nitime returns n_times + 1 frequency points
# causing the value at 0 to be different
assert_array_almost_equal(psd[:, 1:], psd_ni[:, 1:-1], decimal=3)
assert_array_almost_equal(freqs, freqs_ni[:-1])
def test_source_psd_epochs():
"""Test multi-taper source PSD computation in label from epochs"""
raw = io.Raw(fname_data)
inverse_operator = read_inverse_operator(fname_inv)
label = read_label(fname_label)
event_id, tmin, tmax = 1, -0.2, 0.5
lambda2, method = 1. / 9., 'dSPM'
bandwidth = 8.
fmin, fmax = 0, 100
picks = pick_types(raw.info, meg=True, eeg=False, stim=True,
ecg=True, eog=True, include=['STI 014'],
exclude='bads')
reject = dict(grad=4000e-13, mag=4e-12, eog=150e-6)
events = find_events(raw, stim_channel='STI 014')
epochs = Epochs(raw, events, event_id, tmin, tmax, picks=picks,
baseline=(None, 0), reject=reject)
# only look at one epoch
epochs.drop_bad_epochs()
one_epochs = epochs[:1]
inv = prepare_inverse_operator(inverse_operator, nave=1,
lambda2=1. / 9., method="dSPM")
# return list
stc_psd = compute_source_psd_epochs(one_epochs, inv,
lambda2=lambda2, method=method,
pick_ori="normal", label=label,
bandwidth=bandwidth,
fmin=fmin, fmax=fmax,
prepared=True)[0]
# return generator
stcs = compute_source_psd_epochs(one_epochs, inv,
lambda2=lambda2, method=method,
pick_ori="normal", label=label,
bandwidth=bandwidth,
fmin=fmin, fmax=fmax,
return_generator=True,
prepared=True)
for stc in stcs:
stc_psd_gen = stc
assert_array_almost_equal(stc_psd.data, stc_psd_gen.data)
# compare with direct computation
stc = apply_inverse_epochs(one_epochs, inv,
lambda2=lambda2, method=method,
pick_ori="normal", label=label,
prepared=True)[0]
sfreq = epochs.info['sfreq']
psd, freqs = multitaper_psd(stc.data, sfreq=sfreq, bandwidth=bandwidth,
fmin=fmin, fmax=fmax)
assert_array_almost_equal(psd, stc_psd.data)
assert_array_almost_equal(freqs, stc_psd.times)
# Check corner cases caused by tiny bandwidth
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
compute_source_psd_epochs(one_epochs, inv,
lambda2=lambda2, method=method,
pick_ori="normal", label=label,
bandwidth=0.01, low_bias=True,
fmin=fmin, fmax=fmax,
return_generator=False,
prepared=True)
compute_source_psd_epochs(one_epochs, inv,
lambda2=lambda2, method=method,
pick_ori="normal", label=label,
bandwidth=0.01, low_bias=False,
fmin=fmin, fmax=fmax,
return_generator=False,
prepared=True)
assert_true(len(w) >= 2)
assert_true(any('not properly use' in str(ww.message) for ww in w))
assert_true(any('Bandwidth too small' in str(ww.message) for ww in w))
def test_source_psd_epochs():
"""Test multi-taper source PSD computation in label from epochs"""
raw = fiff.Raw(fname_data)
inverse_operator = read_inverse_operator(fname_inv)
label = read_label(fname_label)
event_id, tmin, tmax = 1, -0.2, 0.5
lambda2, method = 1. / 9., 'dSPM'
bandwidth = 8.
fmin, fmax = 0, 100
picks = fiff.pick_types(raw.info,
meg=True,
eeg=False,
stim=True,
ecg=True,
eog=True,
include=['STI 014'],
exclude='bads')
reject = dict(grad=4000e-13, mag=4e-12, eog=150e-6)
events = find_events(raw, stim_channel='STI 014')
epochs = Epochs(raw,
events,
event_id,
tmin,
tmax,
picks=picks,
baseline=(None, 0),
reject=reject)
# only look at one epoch
epochs.drop_bad_epochs()
one_epochs = epochs[:1]
# return list
stc_psd = compute_source_psd_epochs(one_epochs,
inverse_operator,
lambda2=lambda2,
method=method,
pick_ori="normal",
label=label,
bandwidth=bandwidth,
fmin=fmin,
fmax=fmax)[0]
# return generator
stcs = compute_source_psd_epochs(one_epochs,
inverse_operator,
lambda2=lambda2,
method=method,
pick_ori="normal",
label=label,
bandwidth=bandwidth,
fmin=fmin,
fmax=fmax,
return_generator=True)
for stc in stcs:
stc_psd_gen = stc
assert_array_almost_equal(stc_psd.data, stc_psd_gen.data)
# compare with direct computation
stc = apply_inverse_epochs(one_epochs,
inverse_operator,
lambda2=lambda2,
method=method,
pick_ori="normal",
label=label)[0]
sfreq = epochs.info['sfreq']
psd, freqs = multitaper_psd(stc.data,
sfreq=sfreq,
bandwidth=bandwidth,
fmin=fmin,
fmax=fmax)
assert_array_almost_equal(psd, stc_psd.data)
assert_array_almost_equal(freqs, stc_psd.times)
def test_source_psd_epochs():
"""Test multi-taper source PSD computation in label from epochs"""
raw = io.Raw(fname_data)
inverse_operator = read_inverse_operator(fname_inv)
label = read_label(fname_label)
event_id, tmin, tmax = 1, -0.2, 0.5
lambda2, method = 1. / 9., 'dSPM'
bandwidth = 8.
fmin, fmax = 0, 100
picks = pick_types(raw.info,
meg=True,
eeg=False,
stim=True,
ecg=True,
eog=True,
include=['STI 014'],
exclude='bads')
reject = dict(grad=4000e-13, mag=4e-12, eog=150e-6)
events = find_events(raw, stim_channel='STI 014')
epochs = Epochs(raw,
events,
event_id,
tmin,
tmax,
picks=picks,
baseline=(None, 0),
reject=reject)
# only look at one epoch
epochs.drop_bad_epochs()
one_epochs = epochs[:1]
inv = prepare_inverse_operator(inverse_operator,
nave=1,
lambda2=1. / 9.,
method="dSPM")
# return list
stc_psd = compute_source_psd_epochs(one_epochs,
inv,
lambda2=lambda2,
method=method,
pick_ori="normal",
label=label,
bandwidth=bandwidth,
fmin=fmin,
fmax=fmax,
prepared=True)[0]
# return generator
stcs = compute_source_psd_epochs(one_epochs,
inv,
lambda2=lambda2,
method=method,
pick_ori="normal",
label=label,
bandwidth=bandwidth,
fmin=fmin,
fmax=fmax,
return_generator=True,
prepared=True)
for stc in stcs:
stc_psd_gen = stc
assert_array_almost_equal(stc_psd.data, stc_psd_gen.data)
# compare with direct computation
stc = apply_inverse_epochs(one_epochs,
inv,
lambda2=lambda2,
method=method,
pick_ori="normal",
label=label,
prepared=True)[0]
sfreq = epochs.info['sfreq']
psd, freqs = multitaper_psd(stc.data,
sfreq=sfreq,
bandwidth=bandwidth,
fmin=fmin,
fmax=fmax)
assert_array_almost_equal(psd, stc_psd.data)
assert_array_almost_equal(freqs, stc_psd.times)
# Check corner cases caused by tiny bandwidth
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
compute_source_psd_epochs(one_epochs,
inv,
lambda2=lambda2,
method=method,
pick_ori="normal",
label=label,
bandwidth=0.01,
low_bias=True,
fmin=fmin,
fmax=fmax,
return_generator=False,
prepared=True)
compute_source_psd_epochs(one_epochs,
inv,
lambda2=lambda2,
method=method,
pick_ori="normal",
label=label,
bandwidth=0.01,
low_bias=False,
fmin=fmin,
fmax=fmax,
return_generator=False,
prepared=True)
assert_true(len(w) >= 2)
assert_true(any('not properly use' in str(ww.message) for ww in w))
assert_true(any('Bandwidth too small' in str(ww.message) for ww in w))
