def test_yule_walker():
"""Test Yule-Walker against statsmodels."""
from statsmodels.regression.linear_model import yule_walker as sm_yw
d = np.random.randn(100)
sm_rho, sm_sigma = sm_yw(d, order=2)
rho, sigma = _yule_walker(d[np.newaxis], order=2)
assert_array_almost_equal(sm_sigma, sigma)
assert_array_almost_equal(sm_rho, rho)
def test_yule_walker():
"""Test Yule-Walker against statsmodels."""
from statsmodels.regression.linear_model import yule_walker as sm_yw
d = np.random.randn(100)
sm_rho, sm_sigma = sm_yw(d, order=2)
rho, sigma = _yule_walker(d[np.newaxis], order=2)
assert_array_almost_equal(sm_sigma, sigma)
assert_array_almost_equal(sm_rho, rho)
window_epoch = window_epoch.copy().resample(sfreq=500)
# hjort-csd centered at c3 at 500Hz
csd = compute_current_source_density(window_epoch,
sphere=sphere_center)
csd_data = csd.get_data()
# fir forward-backward filter 8-12 Hz
from mne.filter import create_filter
filt = create_filter(data=csd_data,
sfreq=sfreq,
l_freq=8,
h_freq=12,
method='iir')
csd_filtered = csd.filter(l_freq=8, h_freq=12, method='iir')
# trimming of 64 ms start and end
# AR prediction Yule-Walker order = 30
from mne.time_frequency.ar import _yule_walker
a, e = _yule_walker(csd_filtered.get_data(), order=30)
# prediction of 128 ms (64 trimmed + 64 future)
# hilbert of the 128 ms signal
# POWER
# power spectrum of hjort c3 from the 500ms window
# AR with Yule-Walker order =200