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import os.path as op
import numpy as np
from numpy.testing import assert_array_almost_equal
from nose.tools import assert_true
from mne.datasets import sample
from mne import io, find_events, Epochs, pick_types
from mne.label import read_label
from mne.minimum_norm.inverse import (read_inverse_operator,
apply_inverse_epochs)
from mne.minimum_norm.time_frequency import (source_band_induced_power,
source_induced_power,
compute_source_psd,
compute_source_psd_epochs)
from mne.time_frequency import multitaper_psd
data_path = sample.data_path(download=False)
fname_inv = op.join(data_path, 'MEG', 'sample',
'sample_audvis-meg-oct-6-meg-inv.fif')
fname_data = op.join(data_path, 'MEG', 'sample',
'sample_audvis_raw.fif')
fname_label = op.join(data_path, 'MEG', 'sample', 'labels', 'Aud-lh.label')
@sample.requires_sample_data
def test_tfr_with_inverse_operator():
"""Test time freq with MNE inverse computation"""
tmin, tmax, event_id = -0.2, 0.5, 1
# Setup for reading the raw data
raw = io.Raw(fname_data)
events = find_events(raw, stim_channel='STI 014')
inverse_operator = read_inverse_operator(fname_inv)
raw.info['bads'] += ['MEG 2443', 'EEG 053'] # bads + 2 more
# picks MEG gradiometers
picks = pick_types(raw.info, meg=True, eeg=False, eog=True,
stim=False, exclude='bads')
# Load condition 1
event_id = 1
events3 = events[:3] # take 3 events to keep the computation time low
epochs = Epochs(raw, events3, event_id, tmin, tmax, picks=picks,
baseline=(None, 0), reject=dict(grad=4000e-13, eog=150e-6),
preload=True)
# Compute a source estimate per frequency band
bands = dict(alpha=[10, 10])
label = read_label(fname_label)
stcs = source_band_induced_power(epochs, inverse_operator, bands,
n_cycles=2, use_fft=False, pca=True,
label=label)
stc = stcs['alpha']
assert_true(len(stcs) == len(list(bands.keys())))
assert_true(np.all(stc.data > 0))
assert_array_almost_equal(stc.times, epochs.times)
stcs_no_pca = source_band_induced_power(epochs, inverse_operator, bands,
n_cycles=2, use_fft=False,
pca=False, label=label)
assert_array_almost_equal(stcs['alpha'].data, stcs_no_pca['alpha'].data)
# Compute a source estimate per frequency band
epochs = Epochs(raw, events[:10], event_id, tmin, tmax, picks=picks,
baseline=(None, 0), reject=dict(grad=4000e-13, eog=150e-6),
preload=True)
frequencies = np.arange(7, 30, 2) # define frequencies of interest
power, phase_lock = source_induced_power(epochs, inverse_operator,
frequencies, label, baseline=(-0.1, 0),
baseline_mode='percent', n_cycles=2, n_jobs=1)
assert_true(np.all(phase_lock > 0))
assert_true(np.all(phase_lock <= 1))
assert_true(np.max(power) > 10)
@sample.requires_sample_data
def test_source_psd():
"""Test source PSD computation in label"""
raw = io.Raw(fname_data)
inverse_operator = read_inverse_operator(fname_inv)
label = read_label(fname_label)
tmin, tmax = 0, 20 # seconds
fmin, fmax = 55, 65 # Hz
n_fft = 2048
stc = compute_source_psd(raw, inverse_operator, lambda2=1. / 9.,
method="dSPM", tmin=tmin, tmax=tmax,
fmin=fmin, fmax=fmax, pick_ori="normal",
n_fft=n_fft, label=label, overlap=0.1)
assert_true(stc.times[0] >= fmin * 1e-3)
assert_true(stc.times[-1] <= fmax * 1e-3)
# Time max at line frequency (60 Hz in US)
assert_true(59e-3 <= stc.times[np.argmax(np.sum(stc.data, axis=0))]
<= 61e-3)
@sample.requires_sample_data
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]
# 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)
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