def label_psd(epoch_vector, fs=None):
'''Calculate the source level power spectral density from the label epochs'''
# from scipy.signal import welch
# freq_bins, epoch_spectra = welch(epoch_vector, fs=fs, window='hanning')
from mne.time_frequency.multitaper import psd_array_multitaper
epoch_spectra, freq_bins = psd_array_multitaper(epoch_vector,
fs,
fmin=1, fmax=45,
bandwidth=2,
n_jobs=1,
adaptive=True,
low_bias=True)
return freq_bins, np.median(epoch_spectra, axis=0)
def test_source_psd_epochs():
"""Test multi-taper source PSD computation in label from epochs."""
raw = read_raw_fif(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()
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 = psd_array_multitaper(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(method):
"""Test multi-taper source PSD computation in label from epochs."""
raw = read_raw_fif(fname_data)
inverse_operator = read_inverse_operator(fname_inv)
label = read_label(fname_label)
event_id, tmin, tmax = 1, -0.2, 0.5
lambda2 = 1. / 9.
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()
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_allclose(stc_psd.data, stc_psd_gen.data, atol=1e-7)
# 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 = psd_array_multitaper(stc.data, sfreq=sfreq,
bandwidth=bandwidth, fmin=fmin,
fmax=fmax)
assert_allclose(psd, stc_psd.data, atol=1e-7)
assert_allclose(freqs, stc_psd.times)
# Check corner cases caused by tiny bandwidth
with pytest.raises(ValueError, match='use a value of at least'):
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)
average_random_phase_height_sorted = average_random_phase[position_sorted_indices, :, :]
std_random_phase_height_sorted = std_random_phase[position_sorted_indices, :, :]
average_modular_height_sorted = average_modular[position_sorted_indices, :, :]
std_modular_height_sorted = std_modular[position_sorted_indices, :, :]
average_amplitude_height_sorted = average_amplitude[position_sorted_indices, :, :]
std_amplitude_height_sorted = std_amplitude[position_sorted_indices, :, :]
# </editor-fold>
# -------------------------------------------------
# <editor-fold desc="VISUALISE">
psd_imf, fs = mt.psd_array_multitaper(imfs[:, :, :20000],
sfreq=const_comm.SAMPLING_FREQUENCY/imf_subsampling_factor,
fmin=1, fmax=3000, bandwidth=6, verbose=0)
peak_freqs = fs[np.argmax(psd_imf[:, :, :], axis=2)]
peak_freqs = np.mean(peak_freqs[:2, :], axis=0)
plt.figure(40)
plot_indices = np.arange(0, 12)
for i in plot_indices:
plt.subplot(len(plot_indices), 1, i+1)
plt.plot(fs, psd_imf[40, i, :])
show = [average_phase_height_sorted, std_phase_height_sorted]
min_imf_to_show = 13
def test_source_psd_epochs():
"""Test multi-taper source PSD computation in label from epochs."""
raw = read_raw_fif(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()
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 = psd_array_multitaper(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 pytest.raises(ValueError, match='use a value of at least'):
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)
